├── src
└── subsurface
│ ├── __init__.py
│ ├── multphaseflow
│ ├── __init__.py
│ ├── misc
│ │ ├── __init__.py
│ │ ├── system_tools
│ │ │ ├── __init__.py
│ │ │ └── environ_var.py
│ │ ├── ecl_common.py
│ │ └── grid
│ │ │ ├── __init__.py
│ │ │ ├── unstruct.py
│ │ │ ├── sector.py
│ │ │ └── cornerpoint.py
│ └── opm.py
│ └── rockphysics
│ ├── __init__.py
│ ├── standardrp.py
│ └── softsandrp.py
├── Example
├── README.md
├── README_11_0.png
├── README_12_0.png
├── README_13_0.png
├── README_14_0.png
└── 3WELL.mako
├── tests
└── test_import.py
├── pyproject.toml
├── .gitignore
├── README.md
└── LICENSE
/src/subsurface/__init__.py:
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1 |
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/src/subsurface/multphaseflow/__init__.py:
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1 |
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/Example/README.md:
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1 | Here lives the example [notebook](README.ipynb)
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/src/subsurface/multphaseflow/misc/__init__.py:
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1 | """More tools."""
2 |
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/src/subsurface/rockphysics/__init__.py:
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1 | """Compute elastic properties."""
2 |
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/src/subsurface/multphaseflow/misc/system_tools/__init__.py:
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1 | """Multiprocessing and environment management."""
2 |
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/Example/README_11_0.png:
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https://raw.githubusercontent.com/Python-Ensemble-Toolbox/SimulatorWrap/main/Example/README_11_0.png
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/Example/README_12_0.png:
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https://raw.githubusercontent.com/Python-Ensemble-Toolbox/SimulatorWrap/main/Example/README_12_0.png
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/Example/README_13_0.png:
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https://raw.githubusercontent.com/Python-Ensemble-Toolbox/SimulatorWrap/main/Example/README_13_0.png
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/Example/README_14_0.png:
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https://raw.githubusercontent.com/Python-Ensemble-Toolbox/SimulatorWrap/main/Example/README_14_0.png
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/tests/test_import.py:
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1 | import unittest
2 |
3 |
4 | class MyTestCase(unittest.TestCase):
5 | def test_something(self):
6 | self.assertEqual(True, True) # add assertion here
7 |
8 |
9 | if __name__ == '__main__':
10 | unittest.main()
11 |
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/pyproject.toml:
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1 | [build-system]
2 | requires = ["setuptools>=61.0"]
3 | build-backend = "setuptools.build_meta"
4 |
5 | [project]
6 | name = "subsurface"
7 | version = "0.0.1"
8 | authors = [
9 | { name="Kristian Fossum", email="krfo@norceresearch.no" },
10 | ]
11 | description = "A python package containing some usefull simulator wrappers."
12 | readme = "README.md"
13 | requires-python = ">=3.8"
14 | license = {file = "LICENSE"}
15 | dependencies = ["numpy", "scipy","mako","mat73","scikit-learn"
16 | ]
17 |
18 | [project.urls]
19 | Homepage = "https://github.com/Python-Ensemble-Toolbox/SimulatorWrap"
20 | Issues = "https://github.com/Python-Ensemble-Toolbox/SimulatorWrap/ issues"
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/src/subsurface/multphaseflow/misc/ecl_common.py:
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1 | """Common definitions for all import filters
2 |
3 | >>> from .ecl_common import Phase, Prop
4 | """
5 |
6 |
7 | # Enumeration of the phases that can exist in a simulation.
8 | #
9 | # The names are abbreviations and should really be called oleic, aqueous and
10 | # gaseous, if we wanted to be correct and type more.
11 | #
12 | # The value that is returned is the Eclipse moniker, for backwards
13 | # compatibility with code that uses this directly.
14 | Phase = type('Phase', (object,), {
15 | 'oil': 'OIL',
16 | 'wat': 'WAT',
17 | 'gas': 'GAS',
18 | })
19 |
20 |
21 | # Properties that can be queried from an output file.
22 | #
23 | # The property forms the first part of a "selector", which is a tuple
24 | # containing the necessary information to setup the name of the property
25 | # to read.
26 | Prop = type('Prop', (object,), {
27 | 'pres': 'P', # pressure
28 | 'sat': 'S', # saturation
29 | 'mole': 'x', # mole fraction
30 | 'dens': 'D', # density
31 | 'temp': 'T', # temperature
32 | 'leak': 'L', # leaky well
33 | })
34 |
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/src/subsurface/multphaseflow/misc/grid/__init__.py:
--------------------------------------------------------------------------------
1 | """\
2 | Generic read module which determines format from extension.
3 | """
4 | import logging
5 | import os.path as pth
6 |
7 |
8 | # module specific log; add a null handler so that we won't get an
9 | # error if the main program hasn't set up a log
10 | log = logging.getLogger(__name__) # pylint: disable=invalid-name
11 | log.addHandler(logging.NullHandler())
12 |
13 |
14 | def read_grid(filename, cache_dir=None):
15 | """\
16 | :param filename: Name of the grid file to read, including path
17 | :type filename: str
18 | :param cache_dir: Path to a directory where a cache of the grid
19 | may be stored to ensure faster read next time.
20 | :type cache_dir: str
21 | """
22 | # allow shortcut to home directories to be used in paths
23 | fullname = pth.expanduser(filename)
24 |
25 | # split the filename into directory, name and extension
26 | base, ext = pth.splitext(fullname)
27 |
28 | if ext.lower() == '.grdecl':
29 | from misc import grdecl as grdecl
30 | log.info("Reading corner point grid from \"%s\"", fullname)
31 | grid = grdecl.read(fullname)
32 |
33 | elif ext.lower() == '.egrid':
34 | # in case we only have a simulation available, with the binary
35 | # output from the restart, we can read this directly
36 | from misc import ecl as ecl
37 | log.info("Reading binary Eclipse grid from \"%s\"", fullname)
38 | egrid = ecl.EclipseGrid(base)
39 | grid = {'DIMENS': egrid.shape[::-1],
40 | 'COORD': egrid.coord,
41 | 'ZCORN': egrid.zcorn,
42 | 'ACTNUM': egrid.actnum}
43 |
44 | elif ext.lower() == '.pickle':
45 | # direct import of pickled file (should not do this, prefer to read
46 | # it through a cache directory
47 | import pickle
48 | log.info("Reading binary grid dump from \"%s\"", fullname)
49 | with open(fullname, 'rb') as f:
50 | grid = pickle.load(f)
51 |
52 | else:
53 | raise ValueError(
54 | "File format with extension \"{0}\" is unknown".format(ext))
55 |
56 | return grid
57 |
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/.gitignore:
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1 | # Byte-compiled / optimized / DLL files
2 | __pycache__/
3 | *.py[cod]
4 | *$py.class
5 |
6 | # C extensions
7 | *.so
8 |
9 | # Distribution / packaging
10 | .Python
11 | build/
12 | develop-eggs/
13 | dist/
14 | downloads/
15 | eggs/
16 | .eggs/
17 | lib/
18 | lib64/
19 | parts/
20 | sdist/
21 | var/
22 | wheels/
23 | share/python-wheels/
24 | *.egg-info/
25 | .installed.cfg
26 | *.egg
27 | MANIFEST
28 |
29 | # PyInstaller
30 | # Usually these files are written by a python script from a template
31 | # before PyInstaller builds the exe, so as to inject date/other infos into it.
32 | *.manifest
33 | *.spec
34 |
35 | # Installer logs
36 | pip-log.txt
37 | pip-delete-this-directory.txt
38 |
39 | # Unit test / coverage reports
40 | htmlcov/
41 | .tox/
42 | .nox/
43 | .coverage
44 | .coverage.*
45 | .cache
46 | nosetests.xml
47 | coverage.xml
48 | *.cover
49 | *.py,cover
50 | .hypothesis/
51 | .pytest_cache/
52 | cover/
53 |
54 | # Translations
55 | *.mo
56 | *.pot
57 |
58 | # Django stuff:
59 | *.log
60 | local_settings.py
61 | db.sqlite3
62 | db.sqlite3-journal
63 |
64 | # Flask stuff:
65 | instance/
66 | .webassets-cache
67 |
68 | # Scrapy stuff:
69 | .scrapy
70 |
71 | # Sphinx documentation
72 | docs/_build/
73 |
74 | # PyBuilder
75 | .pybuilder/
76 | target/
77 |
78 | # Jupyter Notebook
79 | .ipynb_checkpoints
80 |
81 | # IPython
82 | profile_default/
83 | ipython_config.py
84 |
85 | # pyenv
86 | # For a library or package, you might want to ignore these files since the code is
87 | # intended to run in multiple environments; otherwise, check them in:
88 | # .python-version
89 |
90 | # pipenv
91 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
92 | # However, in case of collaboration, if having platform-specific dependencies or dependencies
93 | # having no cross-platform support, pipenv may install dependencies that don't work, or not
94 | # install all needed dependencies.
95 | #Pipfile.lock
96 |
97 | # poetry
98 | # Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
99 | # This is especially recommended for binary packages to ensure reproducibility, and is more
100 | # commonly ignored for libraries.
101 | # https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
102 | #poetry.lock
103 |
104 | # pdm
105 | # Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
106 | #pdm.lock
107 | # pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
108 | # in version control.
109 | # https://pdm.fming.dev/latest/usage/project/#working-with-version-control
110 | .pdm.toml
111 | .pdm-python
112 | .pdm-build/
113 |
114 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
115 | __pypackages__/
116 |
117 | # Celery stuff
118 | celerybeat-schedule
119 | celerybeat.pid
120 |
121 | # SageMath parsed files
122 | *.sage.py
123 |
124 | # Environments
125 | .env
126 | .venv
127 | env/
128 | venv/
129 | ENV/
130 | env.bak/
131 | venv.bak/
132 |
133 | # Spyder project settings
134 | .spyderproject
135 | .spyproject
136 |
137 | # Rope project settings
138 | .ropeproject
139 |
140 | # mkdocs documentation
141 | /site
142 |
143 | # mypy
144 | .mypy_cache/
145 | .dmypy.json
146 | dmypy.json
147 |
148 | # Pyre type checker
149 | .pyre/
150 |
151 | # pytype static type analyzer
152 | .pytype/
153 |
154 | # Cython debug symbols
155 | cython_debug/
156 |
157 | # PyCharm
158 | # JetBrains specific template is maintained in a separate JetBrains.gitignore that can
159 | # be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
160 | # and can be added to the global gitignore or merged into this file. For a more nuclear
161 | # option (not recommended) you can uncomment the following to ignore the entire idea folder.
162 | #.idea/
163 |
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/src/subsurface/multphaseflow/misc/grid/unstruct.py:
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1 | """\
2 | Convert cornerpoint grids to unstructured grids
3 |
4 | :example:
5 | import pyresito.grid.unstruct as us
6 | import pyresito.io.grdecl as grdecl
7 |
8 | g = grdecl.read('~/proj/cmgtools/bld/overlap.grdecl')
9 | """
10 | # pylint: disable=too-few-public-methods, multiple-statements
11 | import numpy as np
12 |
13 |
14 | class Ridge (object):
15 | """A ridge consists of two points, anchored in each their pillar. We only
16 | need to store the z-values, because the x- and y- values are determined by
17 | the pillar themselves.
18 | """
19 | __slots__ = ['left', 'right']
20 |
21 | def __init__(self, left, right):
22 | self.left = left
23 | self.right = right
24 |
25 | def is_not_below(self, other):
26 | """Weak ordering of ridges based on vertical placement.
27 |
28 | :param other: Ridge to be compared to this object.
29 | :type other: :class:`Ridge`
30 | :returns: True if no point on self is below any on the other,
31 | None if the ridges cross, and False if there is a point
32 | on the other ridge that is above any on self.
33 | :rtype: Boolean
34 | """
35 | # test each side separately. if self is at the same level as other,
36 | # this should count positively towards the test (i.e. it is regarded
37 | # as "at least as high"), so use less-or-equal.
38 | left_above = other.left <= self.left
39 | right_above = other.right <= self.right
40 |
41 | # if both sides are at least as high, then self is regarded as at
42 | # least as high as other, and vice versa. if one side is lower and
43 | # one side is higher, then the ridges cross.
44 | if left_above:
45 | return True if right_above else None
46 | else:
47 | return None if right_above else False
48 |
49 |
50 | class Face (object):
51 | """A (vertical) face consists of two ridges, because all of the faces in a
52 | hexahedron can be seen as (possibly degenerate) quadrilaterals.
53 | """
54 | __slots__ = ['top', 'btm']
55 |
56 | def __init__(self, top, btm):
57 | self.top = top
58 | self.btm = btm
59 |
60 | def is_above(self, other):
61 | """Weak ordering of faces based on vertical placement.
62 |
63 | :param other: Face to be compared to this object.
64 | :type other: :class:`Face`
65 | :returns: True if all points in face self is above all points in
66 | face other, False otherwise
67 | :rtype: Boolean
68 | """
69 | # if the bottom of self is aligned with the top of other, then the
70 | # face itself is considered to be above. since the ridge test also
71 | # has an indeterminate result, we test explicitly like this
72 | return True if self.btm.is_not_below(other.top) else False
73 |
74 |
75 | def conv(grid):
76 | """Convert a cornerpoint grid to an unstructured grid.
77 |
78 | :param grid: Cornerpoint grid to be converted.
79 | :type grid: dict, with 'COORD', 'ZCORN', 'ACTNUM'
80 | :returns: Unstructured grid
81 | :rtype: dict
82 | """
83 | # extract the properties of interest from the cornerpoint grid
84 | zcorn = grid['ZCORN']
85 | actnum = grid['ACTNUM']
86 | ni, nj, nk = grid['DIMENS']
87 |
88 | # zcorn has now dimensionality (k, b, j, f, i, r) and actnum is (k, j, i);
89 | # permute the cubes to get the (b, k)-dimensions varying quickest, to avoid
90 | # page faults when we move along pillars/columns
91 | zcorn = np.transpose(zcorn, axes=[2, 3, 4, 5, 1, 0])
92 | actnum = np.transpose(actnum, axes=[1, 2, 0])
93 |
94 | # memory allocation: number of unique cornerpoints along each pillar, and
95 | # the index of each cornerpoint into the global list of vertices
96 | num_cp = np.empty((nj + 1, ni + 1), dtype=np.int32)
97 | ndx_cp = np.empty((nk, 2, nj, 2, ni, 2), dtype=np.int32)
98 |
99 | # each pillar is connected to at most 2*2 columns (front/back, right/left),
100 | # and each column has at most 2*nk (one top and one bottom) corners
101 | corn_z = np.empty((2, 2, 2, nk), dtype=np.float32)
102 | corn_i = np.empty((2, 2, 2, nk), dtype=np.int32)
103 | corn_j = np.empty((2, 2, 2, nk), dtype=np.int32)
104 | corn_a = np.empty((2, 2, 2, nk), dtype=np.bool)
105 |
106 | # get all unique points that are hinged to a certain pillar (p, q)
107 | for q, p in np.ndindex((nj + 1, ni + 1)):
108 | # reset number of corners found for this column
109 | num_corn_z = 0
110 |
111 | for f, r in np.ndindex((2, 2)): # front/back, right/left
112 | # calculate the cell index of the column at this position
113 | j = q - f
114 | i = p - r
115 |
116 | for b in range(2): # bottom/top
117 |
118 | # copy depth values for this corner; notice that we have
119 | # pivoted the zcorn matrix so that values going upwards are in
120 | # last dim.
121 | corn_z[f, r, b, :] = zcorn[j, f, i, r, b, :]
122 |
123 | # same for active numbers, but this is reused for top/bottom;
124 | # if the cell is inactive, then both top and bottom point are.
125 | corn_a[f, r, b, :] = actnum[j, i, :]
126 |
127 | # save the original indices into these auxiliary arrays so that
128 | # we can figure out where each point came from after they are
129 | # sorted
130 | corn_i[f, r, b] = i
131 | corn_j[f, r, b] = j
132 |
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/Example/3WELL.mako:
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1 | <%!
2 | import numpy as np
3 | import datetime as dt
4 | %>
5 | -- *------------------------------------------*
6 | -- * *
7 | -- * base grid model with input parameters *
8 | -- * *
9 | -- *------------------------------------------*
10 | RUNSPEC
11 |
12 | TITLE
13 | 3 WELL MODEL
14 |
15 | DIMENS
16 | -- NDIVIX NDIVIY NDIVIZ
17 | 100 100 1 /
18 |
19 | -- Gradient option
20 | -- AJGRADNT
21 |
22 | -- Gradients readeable
23 | -- UNCODHMD
24 |
25 | --BLACKOIL
26 | OIL
27 | WATER
28 |
29 | METRIC
30 |
31 | TABDIMS
32 | -- NTSFUN NTPVT NSSFUN NPPVT NTFIP NRPVT NTENDP
33 | 1 1 35 30 5 30 1 /
34 |
35 | EQLDIMS
36 | -- NTEQUL NDRXVD NDPRVD
37 | 1 5 100 /
38 |
39 | WELLDIMS
40 | -- NWMAXZ NCWMAX NGMAXZ MWGMAX
41 | 10 1 2 20 /
42 |
43 | VFPPDIMS
44 | -- MXMFLO MXMTHP MXMWFR MXMGFR MXMALQ NMMVFT
45 | 10 10 10 10 1 1 /
46 |
47 | VFPIDIMS
48 | -- MXSFLO MXSTHP NMSVFT
49 | 10 10 1 /
50 |
51 | AQUDIMS
52 | -- MXNAQN MXNAQC NIFTBL NRIFTB NANAQU NCAMAX
53 | 0 0 1 36 2 200/
54 |
55 | START
56 | 09 FEB 1994 /
57 |
58 | NSTACK
59 | 25 /
60 |
61 | NOECHO
62 |
63 | GRID
64 | INIT
65 |
66 | INCLUDE
67 | '../TRUEPERMX.INC'
68 | /
69 |
70 |
71 | COPY
72 | 'PERMX' 'PERMY' /
73 | 'PERMX' 'PERMZ' /
74 | /
75 |
76 | DX
77 | 10000*10 /
78 | DY
79 | 10000*10 /
80 | DZ
81 | 10000*10 /
82 |
83 | TOPS
84 | 10000*2355 /
85 |
86 | PORO
87 | 10000*0.18 /
88 |
89 |
90 | PROPS ===============================================================
91 |
92 | -- Two-phase (water-oil) rel perm curves
93 | -- Sw Krw Kro Pcow
94 | SWOF
95 | 0.1500 0.0 1.0000 0.0
96 | 0.2000 0.0059 0.8521 0.0
97 | 0.2500 0.0237 0.7160 0.0
98 | 0.3000 0.0533 0.5917 0.0
99 | 0.3500 0.0947 0.4793 0.0
100 | 0.4000 0.1479 0.3787 0.0
101 | 0.4500 0.2130 0.2899 0.0
102 | 0.5000 0.2899 0.2130 0.0
103 | 0.5500 0.3787 0.1479 0.0
104 | 0.6000 0.4793 0.0947 0.0
105 | 0.6500 0.5917 0.0533 0.0
106 | 0.7000 0.7160 0.0237 0.0
107 | 0.7500 0.8521 0.0059 0.0
108 | 0.8000 1.0000 0.0 0.0
109 | /
110 |
111 | --PVCDO
112 | -- REF.PRES. FVF COMPRESSIBILITY REF.VISC. VISCOSIBILITY
113 | -- 234 1.065 6.65e-5 5.0 1.9e-3 /
114 |
115 | -- In a e300 run we must use PVDO
116 | PVDO
117 | 220 1.065 5.0
118 | 240 1.06499 5.0 /
119 |
120 | DENSITY
121 | 912.0 1000.0 0.8266
122 | /
123 |
124 | PVTW
125 | 234.46 1.0042 5.43E-05 0.5 1.11E-04 /
126 |
127 |
128 | -- ROCK COMPRESSIBILITY
129 | --
130 | -- REF. PRES COMPRESSIBILITY
131 | ROCK
132 | 235 0.00045 /
133 |
134 |
135 |
136 | REGIONS ===============================================================
137 |
138 | ENDBOX
139 |
140 | SOLUTION ===============================================================
141 |
142 |
143 | -- DATUM DATUM OWC OWC GOC GOC RSVD RVVD SOLN
144 | -- DEPTH PRESS DEPTH PCOW DEPTH PCOG TABLE TABLE METH
145 | EQUIL
146 | 2355.00 200.46 3000 0.00 2355.0 0.000 0 0 /
147 |
148 |
149 | RPTSOL
150 | 'PRES' 'SWAT' /
151 |
152 | RPTRST
153 | BASIC=2 /
154 |
155 |
156 |
157 | SUMMARY ================================================================
158 |
159 | RUNSUM
160 |
161 | EXCEL
162 |
163 | --RPTONLY
164 | FOPT
165 | FGPT
166 | FWPT
167 | FWIT
168 |
169 | WWIR
170 | 'INJ-1'
171 | /
172 |
173 | WOPR
174 | 'PRO-1'
175 | /
176 |
177 | WWPR
178 | 'PRO-1'
179 | /
180 |
181 | SCHEDULE =============================================================
182 |
183 |
184 | RPTSCHED
185 | 'NEWTON=2' /
186 |
187 | RPTRST
188 | BASIC=2 /
189 |
190 | -- AJGWELLS
191 | -- 'INJ-1' 'WWIR' /
192 | -- 'PRO-1' 'WLPR' /
193 | --/
194 |
195 | -- AJGPARAM
196 | -- 'PERMX' 'PORO' /
197 |
198 | ------------------- WELL SPECIFICATION DATA --------------------------
199 | WELSPECS
200 | 'INJ-1' 'G' 1 1 2357 WATER 1* 'STD' 3* /
201 | 'INJ-2' 'G' 100 1 2357 WATER 1* 'STD' 3* /
202 | 'PRO-1' 'G' 100 100 2357 OIL 1* 'STD' 3* /
203 | /
204 | COMPDAT
205 | -- RADIUS SKIN
206 | 'INJ-1' 1 1 1 1 'OPEN' 2* 0.15 1* 5.0 /
207 | 'INJ-2' 100 1 1 1 'OPEN' 2* 0.15 1* 5.0 /
208 | 'PRO-1' 100 100 1 1 'OPEN' 2* 0.15 1* 5.0 /
209 | /
210 |
211 | WCONINJE
212 | --'INJ-1' WATER 'OPEN' BHP 2* 300 /
213 | --'INJ-1' WATER 'OPEN' BHP 2* 250 /
214 | 'INJ-1' WATER 'OPEN' BHP 2* ${injbhp[0]} /
215 | 'INJ-2' WATER 'OPEN' BHP 2* ${injbhp[1]} /
216 | /
217 |
218 | WCONPROD
219 | --'PRO-1' 'OPEN' BHP 5* 100 /
220 | 'PRO-1' 'OPEN' BHP 5* ${prodbhp[0]} /
221 | /
222 |
223 |
224 | --------------------- PRODUCTION SCHEDULE ----------------------------
225 |
226 |
227 |
228 | DATES
229 | 1 JAN 1995 /
230 | /
231 |
232 | DATES -- Generated : Petrel
233 | 1 JAN 1996 /
234 | /
235 |
236 | DATES -- Generated : Petrel
237 | 1 JAN 1997 /
238 | /
239 |
240 | DATES -- Generated : Petrel
241 | 1 JAN 1998 /
242 | /
243 |
244 | DATES -- Generated : Petrel
245 | 1 JAN 1999 /
246 | /
247 |
248 |
249 |
250 |
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/README.md:
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1 | # Subsurface
2 | Repository containing some standard simulation wrappers. For a detailed description of how to build the wrappers,
3 | see the documentation for PET.
4 |
5 | ## Installation
6 | Clone the repository and install it in editable mode by running
7 | ```bash
8 | python3 -m pip install -e .
9 | ```
10 |
11 | ## Examples
12 | The example demonstrates usage of [OPM-flow](https://opm-project.org/). To reproduce, ensure that OPM-flow is installed and in the path. The full noteboox is [here](https://github.com/Python-Ensemble-Toolbox/SimulatorWrap/tree/main/Example), we employ the [3Spot example](https://github.com/Python-Ensemble-Toolbox/Examples/tree/main/3Spot) as a template for this example. All files are Example folder.
13 |
14 |
15 | ```python
16 | # import the flow class
17 | from subsurface.multphaseflow.opm import flow
18 | # import datatime
19 | import datetime as dt
20 | # import numpy
21 | import numpy as np
22 | ```
23 |
24 | To initialllize the wrapper such that we get the needed outputs we must specify multiple inputs. This will typically be extracted from a config .toml file.
25 |
26 |
27 | ```python
28 | # a dictionary containing relevant information
29 | input_dict = {'parallel':2,
30 | 'simoptions': [['sim_flag', '--tolerance-mb=1e-5 --parsing-strictness=low']],
31 | 'sim_limit': 4,
32 | 'reportpoint': [dt.datetime(1994,2,9,00,00,00),
33 | dt.datetime(1995,1,1,00,00,00),
34 | dt.datetime(1996,1,1,00,00,00),
35 | dt.datetime(1997,1,1,00,00,00),
36 | dt.datetime(1998,1,1,00,00,00),
37 | dt.datetime(1999,1,1,00,00,00)],
38 | 'reporttype': "dates",
39 | 'datatype': [
40 | "fopt",
41 | "fgpt",
42 | "fwpt",
43 | "fwit"],
44 | 'runfile':'3well'}
45 |
46 | # name of the runfile
47 | filename = '3WELL'
48 | ```
49 |
50 |
51 | ```python
52 | # Generate an instance of the simulator class
53 | sim = flow(input_dict=input_dict,filename=filename)
54 | ```
55 |
56 |
57 | ```python
58 | # Setup simulator
59 | sim.setup_fwd_run(redund_sim=None)
60 | ```
61 |
62 | The point of the simulator wrapper in PET is to generate the simulation response for an ensemble of parameters. The mako template file needs to render a DATA file for each uncertain parameter. Hence, the syntax of the mako file need to match the test one wants to run. It is up to the user to specify this file. In the 3Spot case, the uncertain parameter consists of the bhp controll for the wells. In the wrapper this is a dictionary with keys matching the variablename in the mako file.
63 |
64 |
65 | ```python
66 | state = {'injbhp':np.array([280,245]),
67 | 'prodbhp':np.array([110])}
68 | ```
69 |
70 |
71 | ```python
72 | # we can now run the flow simulator
73 | pred = sim.run_fwd_sim(state,member_i=0,del_folder=True)
74 | ```
75 |
76 |
77 | ```python
78 | pred
79 | ```
80 |
81 |
82 |
83 |
84 | [{'fopt': array([[0.]]),
85 | 'fgpt': array([[0.]]),
86 | 'fwpt': array([[0.]]),
87 | 'fwit': array([[0.]])},
88 | {'fopt': array([131.0504], dtype=float32),
89 | 'fgpt': array([0.], dtype=float32),
90 | 'fwpt': array([0.48596448], dtype=float32),
91 | 'fwit': array([242.00461], dtype=float32)},
92 | {'fopt': array([276.51306], dtype=float32),
93 | 'fgpt': array([0.], dtype=float32),
94 | 'fwpt': array([0.857482], dtype=float32),
95 | 'fwit': array([463.29108], dtype=float32)},
96 | {'fopt': array([420.74808], dtype=float32),
97 | 'fgpt': array([0.], dtype=float32),
98 | 'fwpt': array([1.1765413], dtype=float32),
99 | 'fwit': array([675.35266], dtype=float32)},
100 | {'fopt': array([564.2478], dtype=float32),
101 | 'fgpt': array([0.], dtype=float32),
102 | 'fwpt': array([1.4610703], dtype=float32),
103 | 'fwit': array([891.02484], dtype=float32)},
104 | {'fopt': array([707.78033], dtype=float32),
105 | 'fgpt': array([0.], dtype=float32),
106 | 'fwpt': array([1.720426], dtype=float32),
107 | 'fwit': array([1110.3655], dtype=float32)}]
108 |
109 |
110 |
111 |
112 | ```python
113 | # we can make simple plot using matplotlib
114 | import matplotlib.pyplot as plt
115 | # Display plots inline in Jupyter
116 | %matplotlib inline
117 | ```
118 |
119 |
120 | ```python
121 | plt.figure(figsize=(10, 6));
122 | plt.plot(input_dict['reportpoint'],np.concatenate(np.array([el['fopt'].flatten() for el in pred])));
123 | plt.title('Field Oil Production Total');
124 | plt.xlabel('Report dates');
125 | plt.ylabel('STB');
126 | ```
127 |
128 |
129 | 
130 |
131 |
132 |
133 | ```python
134 | plt.figure(figsize=(10, 6));
135 | plt.plot(input_dict['reportpoint'],np.concatenate(np.array([el['fgpt'].flatten() for el in pred])));
136 | plt.title('Field Gas Production Total');
137 | plt.xlabel('Report dates');
138 | plt.ylabel('STB');
139 | ```
140 |
141 |
142 |
143 | 
144 |
145 |
146 |
147 |
148 | ```python
149 | plt.figure(figsize=(10, 6));
150 | plt.plot(input_dict['reportpoint'],np.concatenate(np.array([el['fwpt'].flatten() for el in pred])));
151 | plt.title('Field Water Production Total');
152 | plt.xlabel('Report dates');
153 | plt.ylabel('STB');
154 | ```
155 |
156 |
157 |
158 | 
159 |
160 |
161 |
162 |
163 | ```python
164 | plt.figure(figsize=(10, 6));
165 | plt.plot(input_dict['reportpoint'],np.concatenate(np.array([el['fwit'].flatten() for el in pred])));
166 | plt.title('Field Water Injection Total');
167 | plt.xlabel('Report dates');
168 | plt.ylabel('STB');
169 | ```
170 |
171 |
172 |
173 | 
174 |
175 |
176 |
--------------------------------------------------------------------------------
/src/subsurface/multphaseflow/misc/grid/sector.py:
--------------------------------------------------------------------------------
1 | """\
2 | Extract a sector from an existing cornerpoint grid.
3 | """
4 | import argparse
5 | import collections
6 | import logging
7 | import numpy
8 | import re
9 | import sys
10 |
11 | import simulator.multphaseflow.misc.grid as pyr
12 | import simulator.multphaseflow.misc.grdecl as grdecl
13 |
14 |
15 | # add a valid log in case we are not run through the main program which
16 | # sets up one for us
17 | log = logging.getLogger(__name__) # pylint: disable=invalid-name
18 | log.addHandler(logging.NullHandler())
19 |
20 | # three consecutive integers, separated by comma, and perhaps some spaces
21 | # thrown in for readability, optionally enclosed in parenthesis
22 | tuple_format = re.compile(r'\(?([0-9]+)\ *\,\ *([0-9]+)\ *\,\ *([0-9]+)\)?')
23 |
24 |
25 | def parse_tuple(corner):
26 | """\
27 | Parse a parenthesized tuple into three constituent coordinates.
28 |
29 | :param corner: Coordinate specification on the format "(i1,j1,k1)"
30 | :type corner: str
31 | :returns: The parsed tuple, converted into zero-based coordinates
32 | and in Python-matrix order: (k, j, i)
33 | :rtype : (int, int, int)
34 | """
35 | # let the regular expression engine parse the string
36 | match = re.match(tuple_format, corner.strip())
37 |
38 | # if the string matched, then we know that each of the sub-groups can be
39 | # parsed into strings successfully. group 0 is the entire string, so we
40 | # get natural numbering into the parenthesized expressions. subtract one
41 | # to get zero-based coordinates
42 | if match:
43 | i = int(match.group(1)) - 1
44 | j = int(match.group(2)) - 1
45 | k = int(match.group(3)) - 1
46 | return (k, j, i)
47 | # if we didn't got any valid string, then return a bottom value
48 | else:
49 | return None
50 |
51 |
52 | def sort_tuples(corner, opposite):
53 | """\
54 | :param corner: Coordinates of one corner
55 | :type corner: (int, int, int)
56 | :param opposite: Coordinates of the opposite corner
57 | :type opposite: (int, int, int)
58 | :returns: The two tuples, but with coordinates interchanged so that
59 | one corner is always in the lower, left, back and the
60 | other is in the upper, right, front
61 | :rtype: ((int, int, int), (int, int, int))
62 | """
63 | # pick out the most extreme variant in either direction, into each its own
64 | # variable; this may be the same as the input or not, but at least we know
65 | # for sure when we return from this method
66 | least = (min(corner[0], opposite[0]),
67 | min(corner[1], opposite[1]),
68 | min(corner[2], opposite[2]))
69 | most = (max(corner[0], opposite[0]),
70 | max(corner[1], opposite[1]),
71 | max(corner[2], opposite[2]))
72 | return (least, most)
73 |
74 |
75 | def extract_dimens(least, most):
76 | """\
77 | Build a new dimension tuple for a submodel
78 |
79 | :param least: Lower, left-most, back corner of submodel, (k1, j1, i1)
80 | :type least: (int, int, int)
81 | :param most: Upper, right-most, front corner of submodel, (k2, j2, i2)
82 | :type most: (int, int, int)
83 | :returns: Dimensions of the submodel
84 | :rtype: numpy.ndarray((3,))
85 | """
86 | # split the corners into constituents
87 | k1, j1, i1 = least
88 | k2, j2, i2 = most
89 |
90 | # make an array out of the cartesian distance of the two corners
91 | sector_dimens = numpy.array([i2-i1+1, j2-j1+1, k2-k1+1], dtype=numpy.int32)
92 | return sector_dimens
93 |
94 |
95 | def extract_coord(coord, least, most):
96 | """\
97 | Extract the coordinate pillars for a submodel
98 |
99 | :param coord: Coordinate pillars for the entire grid
100 | :type coord: numpy.ndarray((nj+1, ni+1, 2, 3))
101 | :param least: Lower, left-most, back corner of submodel, (k1, j1, i1)
102 | :type least: (int, int, int)
103 | :param most: Upper, right-most, front corner of submodel, (k2, j2, i2)
104 | :type most: (int, int, int)
105 | :returns: Coordinate pilars for the submodel
106 | :rtype: numpy.ndarray((j2-j1+2, i2-i1+2, 2, 3))
107 | """
108 | # split the corners into constituents
109 | k1, j1, i1 = least
110 | k2, j2, i2 = most
111 |
112 | # add one to get the pillar on the other side of the element, so that
113 | # we include the last element, add one more since Python indexing is
114 | # end-exclusive
115 | sector_coord = coord[j1:(j2+2), i1:(i2+2), :, :]
116 | return sector_coord
117 |
118 |
119 | def extract_zcorn(zcorn, least, most):
120 | """\
121 | Extract the hinge depth values for a submodel
122 |
123 | :param zcorn: Hinge depth values for the entire grid
124 | :type zcorn: numpy.ndarray((nk, 2, nj, 2, ni, 2))
125 | :param least: Lower, left-most, back corner of submodel, (k1, j1, i1)
126 | :type least: (int, int, int)
127 | :param most: Upper, right-most, front corner of submodel, (k2, j2, i2)
128 | :type most: (int, int, int)
129 | :returns: Hinge depth values for the submodel
130 | :rtype: numpy.ndarray((k2-k1+1, 2, j2-j1+1, 2, i2-i1+1))
131 | """
132 | # split the corners into constituents
133 | k1, j1, i1 = least
134 | k2, j2, i2 = most
135 |
136 | # add one since Python-indexing is end-exclusive, and we want to include
137 | # the element in the opposite corner. all eight hinges are returned for
138 | # each element (we only select in every other dimension)
139 | sector_zcorn = zcorn[k1:(k2+1), :, j1:(j2+1), :, i1:(i2+1), :]
140 | return sector_zcorn
141 |
142 |
143 | def extract_cell_prop(prop, least, most):
144 | """\
145 | Extract the property values for a submodel
146 |
147 | :param prop: Property values for each cell in the the entire grid
148 | :type prop: numpy.ndarray((nk, nj, ni))
149 | :param least: Lower, left-most, back corner of submodel, (k1, j1, i1)
150 | :type least: (int, int, int)
151 | :param most: Upper, right-most, front corner of submodel, (k2, j2, i2)
152 | :type most: (int, int, int)
153 | :returns: Property values for each cell in the submodel
154 | :rtype: numpy.ndarray((k2-k1+1, j2-j1+1, i2-i1+1))
155 | """
156 | # split the corners into constituents
157 | k1, j1, i1 = least
158 | k2, j2, i2 = most
159 |
160 | # add one since Python-indexing is end-exclusive, and we want to include
161 | # the element in the opposite corner.
162 | sector_prop = prop[k1:(k2+1), j1:(j2+1), i1:(i2+1)]
163 | return sector_prop
164 |
165 |
166 | def extract_grid(grid, least, most):
167 | """\
168 | Extract a submodel from a full grid
169 |
170 | :param grid: Attributes of the full grid, like COORD, ZCORN, ACTNUM
171 | :type grid: dict
172 | :param least: Lower, left-most, back corner of submodel, (k1, j1, i1)
173 | :type least: (int, int, int)
174 | :param most: Upper, right-most, front corner of submodel, (k2, j2, i2)
175 | :type most: (int, int, int)
176 | :returns: Attributes of the sector model
177 | :rtype: dict
178 | """
179 | # create a new grid and fill extract standard properties
180 | sector = collections.OrderedDict()
181 | sector['DIMENS'] = extract_dimens(least, most)
182 | sector['COORD'] = extract_coord(grid['COORD'], least, most)
183 | sector['ZCORN'] = extract_zcorn(grid['ZCORN'], least, most)
184 | sector['ACTNUM'] = extract_cell_prop(grid['ACTNUM'], least, most)
185 |
186 | # then extract all extra cell properties, such as PORO, PERMX that
187 | # may have been added
188 | for prop_name in grid:
189 | # ignore the standard properties; they have already been converted
190 | # by specialized methods above
191 | prop_upper = prop_name.upper()
192 | std_prop = ((prop_upper == 'DIMENS') or (prop_upper == 'COORD') or
193 | (prop_upper == 'ZCORN') or (prop_upper == 'ACTNUM'))
194 | # use the generic method to convert this property
195 | if not std_prop:
196 | sector[prop_name] = extract_cell_prop(grid[prop_name], least, most)
197 |
198 | return sector
199 |
200 |
201 | def main(*args):
202 | """Read a data file to see if it parses OK."""
203 | # setup simple logging where we prefix each line with a letter code
204 | logging.basicConfig(level=logging.INFO,
205 | format="%(levelname).1s: %(message).76s")
206 |
207 | # parse command-line arguments
208 | parser = argparse.ArgumentParser()
209 | parser.add_argument("infile", metavar="infile.grdecl", help="Input model")
210 | parser.add_argument("outfile", metavar="outfile",
211 | help="Output sector model")
212 | parser.add_argument("first", metavar="i1,j1,k1", type=parse_tuple,
213 | help="A corner of the sector model (one-based)")
214 | parser.add_argument("last", metavar="i2,j2,k2", type=parse_tuple,
215 | help="The opposite corner of the sector (one-based)")
216 | parser.add_argument("--dialect", choices=['ecl', 'cmg'], default='ecl')
217 | parser.add_argument("--verbose", action='store_true')
218 | parser.add_argument("--quiet", action='store_true')
219 | cmd_args = parser.parse_args(*args)
220 |
221 | # adjust the verbosity of the program
222 | if cmd_args.verbose:
223 | logging.getLogger(__name__).setLevel(logging.DEBUG)
224 | if cmd_args.quiet:
225 | logging.getLogger(__name__).setLevel(logging.NOTSET)
226 |
227 | # read the input file
228 | log.info('Reading full grid')
229 | grid = pyr.read_grid(cmd_args.infile)
230 |
231 | # get the two opposite corners that defines the submodel
232 | log.info('Determining scope of sector model')
233 | least, most = sort_tuples(cmd_args.first, cmd_args.last)
234 | log.info('Sector model is (%d, %d, %d)-(%d, %d, %d)',
235 | least[2]+1, least[1]+1, least[0]+1,
236 | most[2]+1, most[1]+1, most[0]+1)
237 |
238 | # extract the data for the submodel into a new grid
239 | log.info('Extracting sector model from full grid')
240 | submodel = extract_grid(grid, least, most)
241 |
242 | # write this grid to output
243 | log.info('Writing sector model to disk')
244 | grdecl.write(cmd_args.outfile, submodel, cmd_args.dialect,
245 | multi_file=True)
246 |
247 |
248 | # if this module is called as a standalone program, then pass all the
249 | # arguments, except the program name
250 | if __name__ == "__main__":
251 | main(sys.argv[1:])
252 |
--------------------------------------------------------------------------------
/src/subsurface/multphaseflow/opm.py:
--------------------------------------------------------------------------------
1 | """Wrap OPM-flow"""
2 | # External imports
3 | from subprocess import call, DEVNULL, run
4 | import os,sys
5 | import shutil
6 | import re
7 | import time
8 | from datetime import timedelta
9 |
10 | # Internal imports
11 | from subsurface.multphaseflow.eclipse import eclipse
12 | from misc.system_tools.environ_var import OPMRunEnvironment
13 |
14 |
15 | class flow(eclipse):
16 | """
17 | Class for running OPM flow with Eclipse input files. Inherits eclipse parent class for setting up and running
18 | simulations, and reading the results.
19 | """
20 |
21 | def __init__(self,input_file=None,initialize_parent=True):
22 | if initialize_parent:
23 | super().__init__(input_file)
24 | else:
25 | self.file = input_file['filename']
26 | self.options = input_file
27 |
28 | def call_sim(self, folder=None, wait_for_proc=False):
29 | """
30 | Call OPM flow simulator via shell.
31 |
32 | Parameters
33 | ----------
34 | folder : str
35 | Folder with runfiles.
36 |
37 | wait_for_proc : bool
38 | Boolean determining if we wait for the process to be done or not.
39 |
40 | Changelog
41 | ---------
42 | - ST 18/10-18
43 | """
44 | # Filename
45 | if folder is not None:
46 | filename = folder + self.file
47 | else:
48 | filename = self.file
49 |
50 | success = True
51 | #print(filename)
52 | try:
53 | with OPMRunEnvironment(filename, 'PRT', ['End of simulation', 'NOSIM']):
54 | com = []
55 | if self.options['mpi']:
56 | com.extend(self.options['mpi'].split())
57 | com.append(self.options['sim_path'] + 'flow')
58 | if self.options['parsing-strictness']:
59 | com.extend(['--parsing-strictness=' + self.options['parsing-strictness']])
60 | com.extend(['--output-dir=' + folder, *
61 | self.options['sim_flag'].split(), filename + '.DATA'])
62 | if 'sim_limit' in self.options:
63 | call(com, stdout=DEVNULL, timeout=self.options['sim_limit'])
64 | else:
65 | call(com, stdout=DEVNULL)
66 | raise ValueError # catch errors in run_sim
67 | except Exception as e:
68 | print('\nError in the OPM run.') # add rerun?
69 | if not os.path.exists('Crashdump'):
70 | shutil.copytree(folder, 'Crashdump')
71 | success = False
72 |
73 | return success
74 |
75 | def check_sim_end(self, finished_member=None):
76 | """
77 | Check in RPT file for "End of simulation" to see if OPM flow is done.
78 |
79 | Changelog
80 | ---------
81 | - ST 19/10-18
82 | """
83 | # Initialize output
84 | # member = None
85 | #
86 | # # Search for output.dat file
87 | # for file in os.listdir('En_' + str(finished_member)): # Search within a specific En_folder
88 | # if file.endswith('PRT'): # look in PRT file
89 | # with open('En_' + str(finished_member) + os.sep + file, 'r') as fid:
90 | # for line in fid:
91 | # if re.search('End of simulation', line):
92 | # # TODO: not do time.sleep()
93 | # # time.sleep(0.1)
94 | # member = finished_member
95 |
96 | return finished_member
97 |
98 | @staticmethod
99 | def SLURM_HPC_run(n_e, venv,filename, **kwargs):
100 | """
101 | HPC run manager for SLURM.
102 |
103 | This function will start num_runs of sim.call_sim() using job arrays in SLURM.
104 | """
105 | # Extract the filename from the kwargs
106 | filename_str = f'"{filename.upper()}"' if filename is not None else ""
107 |
108 | # Extract mpi flag from kwargs
109 | mpi = kwargs.get("mpi", None)
110 | mpi_str = f'"{mpi}"' if mpi is not None else '"mpirun --bind-to none -np 1"'
111 |
112 | # set number of tasks to the number following -np in mpi_str (default is 1)
113 | n_tasks = re.search(r"-np (\d+)", mpi_str).group(1)
114 |
115 | # extract the sim_limit from kwargs. Default is 1 hour
116 | sim_limit = kwargs.get("sim_limit", None)
117 | sim_limit_str = f'--time={str(timedelta(seconds=sim_limit))}' if sim_limit is not None else "--time=01:00:00"
118 |
119 | # extract estimated memory requirement (Gigabyte) for a job
120 | mem = str(kwargs.get("mem", "4G"))
121 |
122 | # extract opm simulator version
123 | opm_ver = kwargs.get("opm_ver", "") # e.g., "/2025.04-foss-2024a" (remember the leading /)
124 |
125 | # extract Python version
126 | python_ver = kwargs.get("python_ver", "") # e.g., "/3.12.3-GCCcore-13.3.0" (remember the leading /)
127 |
128 | diff_ne = n_e[-1] - n_e[0]
129 |
130 | slurm_script = f"""#!/bin/bash
131 | #SBATCH --partition=comp
132 | #SBATCH --job-name=EnDA
133 | #SBATCH --array=0-{diff_ne}
134 | #SBATCH {sim_limit_str}
135 | #SBATCH --mem={mem}
136 | #SBATCH --ntasks={n_tasks}
137 | #SBATCH --cpus-per-task=2
138 | #SBATCH --export=ALL
139 | #SBATCH --output=/dev/null
140 |
141 | # OPTIONAL: load modules here
142 | module load Python{python_ver}
143 | export LMOD_DISABLE_SAME_NAME_AUTOSWAP=no
144 | module load opm-simulators{opm_ver}
145 |
146 | source {venv}
147 |
148 | # Set folder based on SLURM_ARRAY_TASK_ID
149 | folder="En_$(( {n_e[0]} + SLURM_ARRAY_TASK_ID ))/"
150 |
151 | python -m subsurface.multphaseflow.opm "$folder" {filename_str} {mpi_str}
152 | """
153 | script_name = "submit_test_parallel_mpi.sh"
154 | with open(script_name, "w") as f:
155 | f.write(slurm_script)
156 |
157 | # Make it executable (optional):
158 | os.chmod(script_name, 0o755)
159 |
160 | # print(f"Created SLURM script: {script_name}")
161 | # print(f"Submitting array job with {num_runs} tasks...")
162 |
163 | # Submit the script to SLURM
164 | cmd = ["sbatch", script_name]
165 | result = run(cmd, capture_output=True, text=True)
166 |
167 | # remove script file
168 | os.remove(script_name)
169 |
170 | # Extract the job ID from the output
171 | match = re.search(r"Submitted batch job (\d+)", result.stdout)
172 | if match:
173 | return match.group(1) # Return the main job ID
174 | else:
175 | print("Failed to extract Job ID from sbatch output.")
176 | return None
177 |
178 | @staticmethod
179 | def SLURM_ARRAY_HPC_run(n_e, venv, filename, **kwargs):
180 | """
181 | HPC run manager for Slurm array jobs.
182 | Each ensemble member runs independently in its own task.
183 |
184 | Parameters
185 | ----------
186 | n_e : list[int]
187 | Indices of ensemble members to simulate.
188 | venv : str
189 | Path to Python virtual environment activate script.
190 | filename : str
191 | Simulation input file.
192 | kwargs : dict
193 | Extra simulation options. Recognized:
194 | - sim_limit (float seconds or str HH:MM:SS)
195 | - mem (default "4G")
196 | - cpus_per_task (default 2)
197 | """
198 |
199 | # Start and end indices for the array
200 | start_idx = n_e[0]
201 | end_idx = n_e[-1]
202 | num_tasks = end_idx - start_idx
203 |
204 | # Extract options
205 | sim_limit = kwargs.get("sim_limit", None)
206 | if sim_limit is not None:
207 | if isinstance(sim_limit, (int, float)):
208 | from datetime import timedelta
209 | sim_limit_str = f'--time={str(timedelta(seconds=sim_limit))}'
210 | else:
211 | sim_limit_str = f'--time={sim_limit}'
212 | else:
213 | sim_limit_str = "--time=02:00:00"
214 |
215 | mem = kwargs.get("mem", "4G")
216 | cpus_per_task = kwargs.get("cpus_per_task", 1)
217 |
218 | slurm_script = f"""#!/bin/bash
219 | #SBATCH --job-name=EnDA_array
220 | #SBATCH --partition=comp
221 | #SBATCH --array=0-{num_tasks}
222 | #SBATCH --cpus-per-task={cpus_per_task}
223 | #SBATCH --mem={mem}
224 | #SBATCH {sim_limit_str}
225 | #SBATCH --output=logs/job_%A_%a.out
226 | #SBATCH --error=logs/job_%A_%a.err
227 |
228 | module load Python
229 | export LMOD_DISABLE_SAME_NAME_AUTOSWAP=no
230 | module load opm-simulators
231 | source {venv}
232 |
233 | IDX=$(( {start_idx} + SLURM_ARRAY_TASK_ID ))
234 | FOLDER="En_$IDX/"
235 |
236 | python -m subsurface.multphaseflow.opm "$FOLDER" {filename} ""
237 | """
238 |
239 | script_name = "submit_array.sh"
240 | with open(script_name, "w") as f:
241 | f.write(slurm_script)
242 |
243 | os.chmod(script_name, 0o755)
244 |
245 | result = run(["sbatch", script_name], capture_output=True, text=True)
246 |
247 | os.remove(script_name)
248 |
249 | match = re.search(r"Submitted batch job (\d+)", result.stdout)
250 | if match:
251 | return match.group(1)
252 | else:
253 | print("Job submission failed:", result.stderr)
254 | return None
255 |
256 |
257 | def are_jobs_done(self, job_id):
258 | """Check if all job array tasks are completed using sacct."""
259 | check_cmd = ["sacct", "-j", f"{job_id}", "--format=JobID,State", "--noheader"]
260 |
261 | # print(check_cmd)
262 |
263 | check_result = run(check_cmd, capture_output=True, text=True)
264 |
265 | while not len(check_result.stdout): # if spinning up
266 | time.sleep(1)
267 | check_result = run(check_cmd, capture_output=True, text=True)
268 |
269 | # print(check_result.stdout)
270 |
271 | return_states = []
272 |
273 | job_states = check_result.stdout.strip().split("\n")
274 | for job in job_states:
275 | parts = job.split()
276 | if len(parts) >= 2:
277 | state = parts[1]
278 | if state not in ["COMPLETED", "FAILED", "CANCELLED"]:
279 | return False # A job is still running or pendin
280 | else:
281 | if state == "FAILED" or state == "CANCELLED":
282 | return_states.append(False)
283 | else:
284 | return_states.append(True)
285 |
286 | return return_states
287 |
288 | def wait_for_jobs(self,job_id,wait_time=10):
289 | """Wait until all job array tasks are completed."""
290 | #print(f"Waiting for job array {job_id} to complete...")
291 |
292 | val = self.are_jobs_done(job_id)
293 | while not val:
294 | time.sleep(wait_time) # Wait for 10 seconds before checking again
295 | val = self.are_jobs_done(job_id)
296 |
297 | return val
298 |
299 | #print(f"All jobs in array {job_id} are completed.")
300 |
301 |
302 |
303 | class ebos(eclipse):
304 | """
305 | Class for running OPM ebos with Eclipse input files. Inherits eclipse parent class for setting up and running
306 | simulations, and reading the results.
307 | """
308 |
309 | def call_sim(self, folder=None, wait_for_proc=False):
310 | """
311 | Call OPM flow simulator via shell.
312 |
313 | Parameters
314 | ----------
315 | folder : str
316 | Folder with runfiles.
317 |
318 | wait_for_proc : bool
319 | Determines whether to wait for the process to be done or not.
320 |
321 | Changelog
322 | ---------
323 | - RJL 27/08-19
324 | """
325 | # Filename
326 | if folder is not None:
327 | filename = folder + self.file
328 | else:
329 | filename = self.file
330 |
331 | # Run simulator
332 | if 'sim_path' not in self.options.keys():
333 | self.options['sim_path'] = ''
334 |
335 | with OPMRunEnvironment(filename, 'OUT', 'Timing receipt'):
336 | with open(filename+'.OUT', 'w') as f:
337 | call([self.options['sim_path'] + 'ebos', '--output-dir=' + folder,
338 | *self.options['sim_flag'].split(), filename + '.DATA'], stdout=f)
339 |
340 | def check_sim_end(self, finished_member=None):
341 | """
342 | Check in RPT file for "End of simulation" to see if OPM ebos is done.
343 |
344 | Changelog
345 | ---------
346 | - RJL 27/08-19
347 | """
348 | # Initialize output
349 | # member = None
350 | #
351 | # # Search for output.dat file
352 | # for file in os.listdir('En_' + str(finished_member)): # Search within a specific En_folder
353 | # if file.endswith('OUT'): # look in OUT file
354 | # with open('En_' + str(finished_member) + os.sep + file, 'r') as fid:
355 | # for line in fid:
356 | # if re.search('Timing receipt', line):
357 | # # TODO: not do time.sleep()
358 | # # time.sleep(0.1)
359 | # member = finished_member
360 |
361 | return finished_member
362 |
363 |
364 | if __name__ == "__main__":
365 | import sys
366 | if len(sys.argv) != 4:
367 | print("Usage: python -m subsurface.multphaseflow.opm ")
368 | sys.exit(1)
369 |
370 | folder = sys.argv[1]
371 | filename = sys.argv[2]
372 | mpi = sys.argv[3]
373 | options = {}
374 | options['sim_path'] = ''
375 | options['sim_flag'] = ''
376 | options['mpi'] = mpi
377 | options['parsing-strictness'] = ''
378 | options['filename'] = filename
379 |
380 | sim = flow(input_file=options,initialize_parent=False)
381 | success = sim.call_sim(folder=folder)
382 | if success:
383 | sys.exit(0)
384 | else:
385 | sys.exit(1) # ensure that slurm catch the error
386 | #print("Success!" if success else "Failed.")
387 |
--------------------------------------------------------------------------------
/src/subsurface/multphaseflow/misc/system_tools/environ_var.py:
--------------------------------------------------------------------------------
1 | """Descriptive description."""
2 |
3 | import os
4 | import re
5 | import sys
6 | import multiprocessing.context as ctx
7 | import platform
8 |
9 |
10 | class OpenBlasSingleThread:
11 | """
12 | A context manager class to set OpenBLAS multi threading environment variable to 1 (i.e., single threaded). The
13 | class is used in a 'with'-statement to ensure that everything inside the statement is run single threaded,
14 | and outside the statement is run using whatever the environment variable was set before the 'with'-statement.
15 | The environment variable setting threading in OpenBLAS is OMP_NUM_THREADS.
16 |
17 | Example
18 | -------
19 |
20 | >>> from system_tools.environ_var import OpenBlasSingleThread
21 | ... import ctypes
22 | ... import multiprocessing as mp
23 | ...
24 | ... def justdoit():
25 | ... # Load OpenBLAS library and print number of threads
26 | ... openblas_lib = ctypes.cdll.LoadLibrary('/scratch/openblas/lib/libopenblas.so')
27 | ... print(openblas_lib.openblas_get_num_threads())
28 | ...
29 | ... if __name__ == "__main__":
30 | ... # Load OpenBLAS library and print number of threads before the with-statement
31 | ... openblas_lib = ctypes.cdll.LoadLibrary('/scratch/openblas/lib/libopenblas.so')
32 | ... print(openblas_lib.openblas_get_num_threads())
33 | ...
34 | ... # Run a Process inside the with-statement with the OpenBlasSingleThread class.
35 | ... with OpenBlasSingleThread ():
36 | ... p = mp.Process (target=justdoit)
37 | ... p.start ()
38 | ... p.join ()
39 | ...
40 | ... # Load OpenBLAS library and print number of threads before the with-statement
41 | ... openblas_lib = ctypes.cdll.LoadLibrary('/scratch/openblas/lib/libopenblas.so')
42 | ... print(openblas_lib.openblas_get_num_threads())
43 | """
44 |
45 | def __init__(self):
46 | """
47 | Init. the class with no inputs. Use this to initialize internal variables for storing number of threads an
48 | the Process context manager before the change to single thread.
49 |
50 | Parameters
51 | ----------
52 | num_threads:
53 | String with number of OpenBLAS threads before change to single
54 | threaded (it is the content of OMP_NUM_THREADS)
55 | ctx:
56 | The context variable from Process (default is 'fork' context, but
57 | we want to use 'spawn')
58 |
59 | Changelog
60 | ---------
61 | - ST 31/10-17
62 | """
63 | self.num_threads = ''
64 | self.ctx = None
65 |
66 | def __enter__(self):
67 | """
68 | Method that is run when class is initiated by a 'with'-statement
69 |
70 | Changelog
71 | ---------
72 | - ST 31/10-17
73 | """
74 | # Save OMP_NUM_THREADS environment variable to restore later
75 | if 'OMP_NUM_THREADS' in os.environ:
76 | self.num_threads = os.environ['OMP_NUM_THREADS']
77 | else:
78 | self.num_threads = ''
79 |
80 | # Set OMP_NUM_THREADS to 1 to ensure single threaded OpenBLAS
81 | os.environ['OMP_NUM_THREADS'] = '1'
82 |
83 | # Save Process context variable to restore later
84 | self.ctx = ctx._default_context
85 |
86 | # Change context to 'spawn' to ensure that any use of Process inside the 'with'-statement will initialize
87 | # with the newly set OMP_NUM_THREADS=1 environment variable. (The default, 'fork', context only copy its
88 | # parent environment variables without taking into account changes made after a Python program is
89 | # initialized)
90 | ctx._default_context = (ctx.DefaultContext(ctx._concrete_contexts['spawn']))
91 |
92 | # Return self
93 | return self
94 |
95 | def __exit__(self, exc_typ, exc_val, exc_trb):
96 | """
97 | Method that is run when 'with'-statement closes. Here, we reset OMP_NUM_THREADS and Process context to what
98 | is was set to before the 'with'-statement. Input here in this method are required to work in 'with'-statement.
99 |
100 | Changelog
101 | ---------
102 | - ST 31/10-17
103 | """
104 | # Check if there was any OMP_NUM_THREADS at all before the with-statement, and reset it thereafter.
105 | if len(self.num_threads):
106 | os.environ['OMP_NUM_THREADS'] = self.num_threads
107 | else:
108 | os.environ.unsetenv('OMP_NUM_THREADS')
109 |
110 | # Reset Process context
111 | ctx._default_context = self.ctx
112 |
113 | # Return False (exit 0?)
114 | return False
115 |
116 |
117 | class CmgRunEnvironment:
118 | """
119 | A context manager class to run CMG simulators with correct environmental variables.
120 | """
121 |
122 | def __init__(self, root, simulator, version, license):
123 | """
124 | We initialize the context manager by setting up correct paths and environment variable names that we set in
125 | __enter__.
126 |
127 | Parameters
128 | ----------
129 | root : str
130 | Root folder where CMG simulator(s) are installed.
131 |
132 | simulator : str
133 | Simulator name.
134 |
135 | version : str
136 | Version of the simulator.
137 |
138 | license : str
139 | License server name.
140 |
141 | Changelog
142 | ---------
143 | - ST 25/10-18
144 |
145 | Notes
146 | -----
147 | 'version' is the release version of CMG, e.g., 2017.101.G.
148 | """
149 | # In
150 | self.root = root
151 | self.sim = simulator
152 | self.ver = version
153 | self.lic = license
154 |
155 | # Internal
156 | self.ctx = None
157 | self.path = ''
158 | self.ld_path = ''
159 |
160 | # Check system platform.
161 | # TODO: Figure out paths in other systems (read Windows...) and remove assertion.
162 | assert (platform.system() == 'Linux'), \
163 | 'Sorry, we have only set up paths for Linux systems... But hey, maybe you can implemented it for your ' \
164 | 'system? :)'
165 |
166 | # Base path to simulator folders
167 | self.path_base = self.root + self.ver + os.sep + self.sim + os.sep + self.ver[:-3] + os.sep + \
168 | 'linux_x64' + os.sep
169 |
170 | # Path to exe file
171 | self.path_exe = self.path_base + 'exe'
172 |
173 | # Path to libraries
174 | self.path_lib = self.path_base + 'lib'
175 |
176 | def __enter__(self):
177 | """
178 | Method that is run when class is initiated by a 'with'-statement
179 |
180 | Changelog
181 | ---------
182 | - ST 25/10-18
183 | """
184 | # Append if environment variable already exist, or generate it if not.
185 | # We also save all environment variables that we intend to alter, so we can restore them when closing the
186 | # context manager class
187 | # PATH
188 | if 'PATH' in os.environ:
189 | self.path = os.environ['PATH']
190 | os.environ['PATH'] = self.path_exe + os.pathsep + os.environ['PATH']
191 | else:
192 | self.path = ''
193 | os.environ['PATH'] = self.path_exe
194 |
195 | # LD_LIBRARY_PATH
196 | if 'LD_LIBRARY_PATH' in os.environ:
197 | self.ld_path = os.environ['LD_LIBRARY_PATH']
198 | os.environ['LD_LIBRARY_PATH'] = self.path_lib + \
199 | os.pathsep + os.environ['LD_LIBRARY_PATH']
200 | else:
201 | self.ld_path = ''
202 | os.environ['LD_LIBRARY_PATH'] = self.path_lib
203 |
204 | # Create environment variable for CMG license server
205 | os.environ['CMG_LIC_HOST'] = self.lic
206 |
207 | # Save Process context variable to restore later
208 | self.ctx = ctx._default_context
209 |
210 | # Change context to 'spawn' to ensure that any use of Process inside the 'with'-statement will initialize
211 | # with the newly set environment variables. (The default, 'fork', context only copy its
212 | # parent environment variables without taking into account changes made after a Python program is
213 | # initialized)
214 | ctx._default_context = (ctx.DefaultContext(ctx._concrete_contexts['spawn']))
215 |
216 | # Return self
217 | return self
218 |
219 | def __exit__(self, exc_typ, exc_val, exc_trb):
220 | """
221 | Method that is run when 'with'-statement closes. Here, we reset environment variables and Process context to
222 | what is was set to before the 'with'-statement. Input here in this method are required to work in
223 | 'with'-statement.
224 |
225 | Changelog
226 | ---------
227 | - ST 25/10-18
228 | """
229 | # Reset PATH and LD_LIBRARY_PATH to what they were before our intervention. If they were not set we delete
230 | # them from the environment variables
231 | if len(self.path):
232 | os.environ['PATH'] = self.path
233 | else:
234 | os.environ.unsetenv('PATH')
235 |
236 | if len(self.ld_path):
237 | os.environ['LD_LIBRARY_PATH'] = self.ld_path
238 | else:
239 | os.environ.unsetenv('LD_LIBRARY_PATH')
240 |
241 | # We unset the CMG license server path
242 | os.environ.unsetenv('CMG_LIC_HOST')
243 |
244 | # Reset Process context
245 | ctx._default_context = self.ctx
246 |
247 | # Return False (exit 0?)
248 | return False
249 |
250 |
251 | class OPMRunEnvironment:
252 | """
253 | A context manager class to run OPM simulators with correct environmental variables.
254 | """
255 |
256 | def __init__(self, filename, suffix, matchstring):
257 | """
258 |
259 | - filename: OPM run file, needed to check for errors (string)
260 | - suffix: What file to search for complete sign
261 | - matchstring: what is the complete sign
262 |
263 | Changelog
264 | ---------
265 | - KF 30/10-19
266 | """
267 | self.filename = filename
268 | self.suffix = suffix
269 | if type(matchstring) != list:
270 | self.mstring = list(matchstring)
271 | else:
272 | self.mstring = matchstring
273 |
274 | def __enter__(self):
275 | """
276 | Method that is run when class is initiated by a 'with'-statement
277 |
278 | Changelog
279 | ---------
280 | - KF 30/10-19
281 | """
282 | # Append if environment variable already exist, or generate it if not.
283 | # We also save all environment variables that we intend to alter, so we can restore them when closing the
284 | # context manager class
285 |
286 | # Save Process context variable to restore later
287 | self.ctx = ctx._default_context
288 |
289 | # Change context to 'spawn' to ensure that any use of Process inside the 'with'-statement will initialize
290 | # with the newly set environment variables. (The default, 'fork', context only copy its
291 | # parent environment variables without taking into account changes made after a Python program is
292 | # initialized)
293 | ctx._default_context = (ctx.DefaultContext(ctx._concrete_contexts['spawn']))
294 |
295 | # Return self
296 | return self
297 |
298 | def __exit__(self, exc_typ, exc_val, exc_trb):
299 | """
300 | Method that is run when 'with'-statement closes. Here, we reset environment variables and Process context to
301 | what it was set to before the 'with'-statement. Input here in this method are required to work in
302 | 'with'-statement.
303 |
304 | Changelog
305 | ---------
306 | - ST 25/10-18
307 | """
308 | # Reset PATH and LD_LIBRARY_PATH to what they were before our intervention. If they were not set we delete
309 | # them from the environment variables
310 |
311 | # Reset Process context
312 | ctx._default_context = self.ctx
313 |
314 | member = False
315 |
316 | with open(self.filename + '.' + self.suffix, 'r') as fid:
317 | for line in fid:
318 | if any([re.search(elem, line) for elem in self.mstring]):
319 | # TODO: not do time.sleep()
320 | # time.sleep(0.1)
321 | member = True
322 | if member == False:
323 | return False
324 | return True
325 |
326 |
327 | class FlowRockRunEnvironment:
328 | """
329 | A context manager class to run flowRock simulators with correct environmental variables.
330 | """
331 |
332 | def __init__(self, filename):
333 | """
334 |
335 | - filename: dummy run file
336 |
337 | Changelog
338 | ---------
339 | - KF 30/10-19
340 | """
341 | self.filename = filename
342 |
343 | def __enter__(self):
344 | """
345 | Method that is run when class is initiated by a 'with'-statement
346 |
347 | Changelog
348 | ---------
349 | - KF 30/10-19
350 | """
351 | # Append if environment variable already exist, or generate it if not.
352 | # We also save all environment variables that we intend to alter, so we can restore them when closing the
353 | # context manager class
354 |
355 | # Save Process context variable to restore later
356 | self.ctx = ctx._default_context
357 |
358 | # Change context to 'spawn' to ensure that any use of Process inside the 'with'-statement will initialize
359 | # with the newly set environment variables. (The default, 'fork', context only copy its
360 | # parent environment variables without taking into account changes made after a Python program is
361 | # initialized)
362 | ctx._default_context = (ctx.DefaultContext(ctx._concrete_contexts['spawn']))
363 |
364 | # Return self
365 | return self
366 |
367 | def __exit__(self, exc_typ, exc_val, exc_trb):
368 | """
369 | Method that is run when 'with'-statement closes. Here, we reset environment variables and Process context to
370 | what is was set to before the 'with'-statement. Input here in this method are required to work in
371 | 'with'-statement.
372 |
373 | Changelog
374 | ---------
375 | - ST 25/10-18
376 | """
377 | # Reset PATH and LD_LIBRARY_PATH to what they were before our intervention. If they were not set we delete
378 | # them from the environment variables
379 |
380 | # Reset Process context
381 | ctx._default_context = self.ctx
382 |
383 | member = False
384 |
385 | if len(self.filename.split(os.sep)) == 1:
386 | if self.filename in os.listdir():
387 | member = True
388 | else:
389 | if self.filename.split(os.sep)[1] in os.listdir(self.filename.split(os.sep)[0]):
390 | member = True
391 |
392 | if member == False:
393 | sys.exit(1)
394 |
395 | return False
396 |
397 |
398 | class EclipseRunEnvironment:
399 | """
400 | A context manager class to run eclipse simulators with correct environmental variables.
401 | """
402 |
403 | def __init__(self, filename):
404 | """
405 | input
406 | filename: eclipse run file, needed to check for errors (string)
407 |
408 | Changelog
409 | ---------
410 | - KF 30/10-19
411 | """
412 | self.filename = filename
413 |
414 | def __enter__(self):
415 | """
416 | Method that is run when class is initiated by a 'with'-statement
417 |
418 | Changelog
419 | ---------
420 | - KF 30/10-19
421 | """
422 | # Append if environment variable already exist, or generate it if not.
423 | # We also save all environment variables that we intend to alter, so we can restore them when closing the
424 | # context manager class
425 |
426 | # Save Process context variable to restore later
427 | self.ctx = ctx._default_context
428 |
429 | # Change context to 'spawn' to ensure that any use of Process inside the 'with'-statement will initialize
430 | # with the newly set environment variables. (The default, 'fork', context only copy its
431 | # parent environment variables without taking into account changes made after a Python program is
432 | # initialized)
433 | ctx._default_context = (ctx.DefaultContext(ctx._concrete_contexts['spawn']))
434 |
435 | # Return self
436 | return self
437 |
438 | def __exit__(self, exc_typ, exc_val, exc_trb):
439 | """
440 | Method that is run when 'with'-statement closes. Here, we reset environment variables and Process context to
441 | what is was set to before the 'with'-statement. Input here in this method are required to work in
442 | 'with'-statement.
443 |
444 | Changelog
445 | ---------
446 | - ST 25/10-18
447 | """
448 | # Reset PATH and LD_LIBRARY_PATH to what they were before our intervention. If they were not set we delete
449 | # them from the environment variables
450 |
451 | # Reset Process context
452 | ctx._default_context = self.ctx
453 |
454 | error_dict = {}
455 |
456 | with open(self.filename + '.ECLEND', 'r') as f:
457 | txt = [value.strip() for value in (f.read()).split('\n')]
458 |
459 | # Search for the text Error Summary which starts the error summary section
460 | for j in range(0, len(txt)):
461 | if txt[j] == 'Error summary':
462 | for k in range(1, 6):
463 | tmp_line = txt[j + k].split(' ')
464 | # store the error statistics as elements in a dictionary
465 | error_dict[tmp_line[0]] = float(tmp_line[-1])
466 | # If there are no errors the run was a success. If 'Error summary' cannot be found the run has
467 | # not finished.
468 | if len(error_dict) > 0:
469 | if error_dict['Errors'] > 0:
470 | print('\n\033[1;31mERROR: RUN has failed with {} errors!\033[1;m'.format(
471 | error_dict['Errors']))
472 | sys.exit(1)
473 |
474 | # Return False (exit 0?)
475 | return False
476 |
--------------------------------------------------------------------------------
/src/subsurface/multphaseflow/misc/grid/cornerpoint.py:
--------------------------------------------------------------------------------
1 | """Common functionality for visualization of corner-point grids.
2 |
3 | import pyresito.grid.cornerpoint as cp
4 | """
5 | import itertools as it
6 | import logging
7 | import numpy as np
8 | import numpy.ma as ma
9 |
10 |
11 | # add a valid log in case we are not run through the main program which
12 | # sets up one for us
13 | log = logging.getLogger(__name__) # pylint: disable=invalid-name
14 | log.addHandler(logging.NullHandler())
15 |
16 |
17 | def scatter(cell_field):
18 | """\
19 | Duplicate all items in every dimension.
20 |
21 | Use this method to duplicate values associated with each cell to
22 | each of the corners in the cell.
23 |
24 | :param cell_field: Property per cell in the grid
25 | :type cell_field: :class:`numpy.ndarray`, shape = (nk, nj, ni)
26 | :return: Property per corner in the cube
27 | :rtype: :class:`numpy.ndarray`, shape = (nk, 2, nj, 2, ni, 2)
28 |
29 | >>> scatter(np.array([[[1, 2],
30 | [3, 4]],
31 | [[5, 6],
32 | [7, 8]]]))
33 |
34 | array([[[[[[1, 1], [2, 2]],
35 | [[1, 1], [2, 2]]],
36 | [[[3, 3], [4, 4]],
37 | [[3, 3], [4, 4]]]],
38 |
39 | [[[[1, 1], [2, 2]],
40 | [[1, 1], [2, 2]]],
41 | [[[3, 3], [4, 4]],
42 | [[3, 3], [4, 4]]]]],
43 |
44 | [[[[[5, 5], [6, 6]],
45 | [[5, 5], [6, 6]]],
46 | [[[7, 7], [8, 8]],
47 | [[7, 7], [8, 8]]]],
48 |
49 | [[[[5, 5], [6, 6]],
50 | [[5, 5], [6, 6]]],
51 | [[[7, 7], [8, 8]],
52 | [[7, 7], [8, 8]]]]]])
53 | """
54 | # get the dimensions of the cube in easily understood aliases
55 | nk, nj, ni = cell_field.shape # pylint: disable=invalid-name
56 |
57 | # create an extra dimension so that we can duplicate individual values
58 | flat = np.reshape(cell_field, (nk, nj, ni, 1))
59 |
60 | # duplicate along each of the axis
61 | dup_i = np.tile(flat, (1, 1, 1, 2))
62 | dup_j = np.tile(dup_i, (1, 1, 2, 1))
63 | dup_k = np.tile(dup_j, (1, 2, 1, 1))
64 |
65 | # reformat to a cube with the appropriate dimensions
66 | corn_field = np.reshape(dup_k, (nk, 2, nj, 2, ni, 2))
67 | return corn_field
68 |
69 |
70 | def inner_dup(pillar_field):
71 | """Duplicate all inner items in both dimensions.
72 |
73 | Use this method to duplicate values associated with each pillar to
74 | the corners on each side(s) of the pillar; four corners for all
75 | interior pillars, two corners for all pillars on the rim and only
76 | one (element) corner for those pillars that are on the grid corners.
77 |
78 | :param pillar_field: Property per pillar in the grid
79 | :type pillar_field: :class:`numpy.ndarray`, shape=(m+1, n+1)
80 | :returns: Property per corner in a grid plane
81 | :rtype: :class:`numpy.ndarray`, shape=(2*m, 2*n))
82 |
83 | >>> inner_dup(np.array ([[1, 2, 3],
84 | [4, 5, 6],
85 | [7, 8, 9]]))
86 | array([[1, 2, 2, 3],
87 | [4, 5, 5, 6],
88 | [4, 5, 5, 6],
89 | [7, 8, 8, 9]])
90 | """
91 | # extract the inner horizontal part of the plane
92 | horz_part = pillar_field[:, 1:-1]
93 |
94 | # tile it to a separate plane
95 | horz_dupd = np.tile(horz_part, (2, 1, 1))
96 |
97 | # shift the tile to the end so it can be rolled
98 | # into the second dimension
99 | horz_shft = np.transpose(horz_dupd, (1, 2, 0))
100 |
101 | # roll this into the second dimension
102 | horz_roll = np.reshape(horz_shft,
103 | (horz_shft.shape[0],
104 | horz_shft.shape[1] * 2))
105 |
106 | # add back the first and last column
107 | horz = np.column_stack([pillar_field[:, 0],
108 | horz_roll,
109 | pillar_field[:, -1]])
110 |
111 | # extract the inner vertical part of the plane
112 | vert_part = horz[1:-1, :]
113 |
114 | # tile it to a separate plane
115 | vert_dupd = np.tile(vert_part, (1, 1, 2))
116 |
117 | # roll this into the first dimension
118 | vert_roll = np.reshape(vert_dupd,
119 | (vert_dupd.shape[1] * 2,
120 | vert_dupd.shape[2] // 2))
121 |
122 | # add back the first and last row
123 | result = np.vstack([horz[0, :],
124 | vert_roll,
125 | horz[-1, :]])
126 | return result
127 |
128 |
129 | def elem_vtcs_ndcs(nk, nj, ni): # pylint: disable=invalid-name
130 | """List zcorn indices used by every element in an nk*nj*ni grid
131 |
132 | :param nk: Number of layers in Z direction
133 | :type nk: int
134 | :param nj: Number of elements in the Y direction
135 | :type nj: int
136 | :param ni: Number of elements in the X direction
137 | :type ni: int
138 | :returns: Zero-based indices for the hexahedral element corners
139 | :rtype: :class:`numpy.ndarray`, shape=(nk*nj*ni, 8), dtype=int
140 | """
141 | # hex_perm is the order a hexahedron should be specified to the
142 | # gridding engine (it is the same for VTK and Ensight Gold formats)
143 | # relative to the order they are in the Eclipse format. the latter
144 | # four is listed first because we turn the z order around with a
145 | # transform.
146 | # local indices: 0, 1, 2, 3, 4, 5, 6, 7
147 | hex_perm = np.array([4, 5, 7, 6, 0, 1, 3, 2], dtype=int)
148 |
149 | # kji is the global (k, j, i) index for every element; we tile
150 | # this into 8 corners per element, with 3 indices per corner;
151 | # this this matrix contains repeats of 8 identical permutations
152 | # of the values 0..(ni-1), 0..(nj-1) and 0..(nk-1)
153 | kji = np.array(list(it.product(range(nk),
154 | range(nj),
155 | range(ni))))
156 | kji = np.reshape(np.tile(kji, [1, hex_perm.shape[0]]), [-1, 3])
157 |
158 | # bfr is the local (bottom, front, right) index for every corner;
159 | # this is a block of 8 local corners which are picked out of the
160 | # zcorn matrix to then correspond with the gridding engines order.
161 | # we tile this block for every element
162 | bfr = np.array(list(it.product([0, 1], repeat=3)))[hex_perm, :]
163 | bfr = np.tile(bfr, [nk*nj*ni, 1])
164 |
165 | # calculate running number for every corner, combining the element
166 | # indices kji with the local corner indices bfr. the zcorn hypercube
167 | # has dimensions nk * 2 * nj * 2 * ni * 2; the indexing is simply a
168 | # flattened view of this hypercube.
169 | ndx = (((2*kji[:, 0] + bfr[:, 0]) * 2*nj +
170 | (2*kji[:, 1] + bfr[:, 1])) * 2*ni +
171 | 2*kji[:, 2] + bfr[:, 2])
172 |
173 | # we then collect the indices so that we get 8 of them (all those that
174 | # belongs to the same element) on a row
175 | ndx = np.reshape(ndx, [-1, hex_perm.shape[0]])
176 | return ndx
177 |
178 |
179 | # pylint: disable=invalid-name, multiple-statements, too-many-locals
180 | def corner_coordinates(coord, zcorn):
181 | """Generate (x, y, z) coordinates for each corner-point.
182 |
183 | :param coord: Pillar geometrical information
184 | :type coord: :class:`numpy.ndarray`, shape=(nj+1, ni+1, 2, 3)
185 | :param zcorn: Depth values along each pillar
186 | :type zcorn: :class:`numpy.ndarray`, shape=(nk, 2, nj, 2, ni, 2)
187 | :returns: Coordinate values for each corner
188 | :rtype: :class:`numpy.ndarray`, shape=(3, nk*2*nj*2*ni*2)
189 | """
190 | # indices to treat the pillar matrix as a record
191 | X = 0
192 | Y = 1
193 | Z = 2
194 | START = 0
195 | END = 1
196 |
197 | # calculate depth derivatives for the pillar slope
198 | dx = coord[:, :, END, X] - coord[:, :, START, X]
199 | dy = coord[:, :, END, Y] - coord[:, :, START, Y]
200 | dz = coord[:, :, END, Z] - coord[:, :, START, Z]
201 |
202 | # make the pillar information compatible with a plane of corners,
203 | # having a singleton dimension at the front (instead tiling 2*nk)
204 | x0 = inner_dup(coord[:, :, START, X])[None, :, :]
205 | y0 = inner_dup(coord[:, :, START, Y])[None, :, :]
206 | z0 = inner_dup(coord[:, :, START, Z])[None, :, :]
207 | dxdz = inner_dup(dx / dz)[None, :, :]
208 | dydz = inner_dup(dy / dz)[None, :, :]
209 |
210 | # infer the grid size from the dimensions of coord
211 | nj = coord.shape[0] - 1
212 | ni = coord.shape[1] - 1
213 |
214 | # make the formal dimensions of the depths compatible with the plane
215 | # of vectors created from the pillars; notice that the first dimension
216 | # is not singular
217 | z = np.reshape(zcorn, (-1, nj*2, ni*2))
218 |
219 | # calculate the point in the plane where the horizon intersect with the
220 | # pillar; we get the (x, y)-coordinates for each corner. notice that the
221 | # difference z - z0 is for each point, whereas dz is for the pillar!
222 | x = (z - z0) * dxdz + x0
223 | y = (z - z0) * dydz + y0
224 |
225 | # reformat the coordinates into the final coordinates
226 | xyz = np.vstack([np.reshape(x, (1, -1)),
227 | np.reshape(y, (1, -1)),
228 | np.reshape(z, (1, -1))])
229 | return xyz
230 |
231 |
232 | # Enumeration of the dimensions in a point tuple
233 | Dim = type('Dim', (), {
234 | 'X': 0,
235 | 'Y': 1,
236 | 'Z': 2,
237 | })
238 |
239 |
240 | # Enumeration of the faces of a hexahedron. The contents are the local
241 | # indices in each row of 8 corners that are set up for the elements by
242 | # the elem_vtcs_ndcs function. (The indices here are the numbers that
243 | # are in the comment "local indices" above the hex_perm selector)
244 | Face = type('Face', (), {
245 | 'DOWN': np.array([0, 1, 2, 3]),
246 | 'UP': np.array([4, 5, 6, 7]),
247 | 'FRONT': np.array([4, 7, 3, 0]),
248 | 'BACK': np.array([5, 6, 2, 1]),
249 | 'LEFT': np.array([7, 6, 2, 3]),
250 | 'RIGHT': np.array([4, 5, 1, 0]),
251 | 'ALL': np.array([0, 1, 2, 3, 4, 5, 6, 7]),
252 | })
253 |
254 |
255 | def cp_cells(grid, face):
256 | """
257 | Make a cell array from a cornerpoint grid. The cells will be in the
258 | same order as the Cartesian enumeration of the grid.
259 |
260 | :param grid: Pillar coordinates and corner depths
261 | :type grid: dict, with 'coord' and 'zcorn' properties
262 | :param face: Which face that should be extracted, e.g. Face.UP
263 | :type face: Face enum
264 | :returns: Set of geometrical objects that can be sent to rendering
265 | :rtype: dict with 'points', shape (nverts, 3), and 'cells', shape
266 | (nelems, ncorns), where ncorns is either 8 (hexahedron
267 | volume or 4 (quadrilateral face), depending on the face
268 | parameter.
269 | """
270 | src = {}
271 |
272 | log.debug("Generating points for corner depths")
273 | # notice that VTK wants shape (nverts, 3), where as the code sets up
274 | # for Ensight format which is (3, nverts).
275 | src['points'] = corner_coordinates(grid['COORD'],
276 | grid['ZCORN']).T.copy()
277 |
278 | # order of the dimensions are different from the structure to the call
279 | ni, nj, nk = grid['DIMENS']
280 |
281 | # extract only the columns of the face we want to show. the shape was
282 | # originally (nelem, 8). copy is necessary to get a contiguous array
283 | # for VTK
284 | log.debug("Generating cells")
285 | src['cells'] = elem_vtcs_ndcs(nk, nj, ni)[:, face].copy()
286 | return src
287 |
288 |
289 | def cell_filter(grid, func):
290 | """Create a filter for a specific grid.
291 |
292 | :param grid: Grid structure that should be filtered
293 | :type grid: dict
294 | :param func: Lambda function that takes i, j, k indices (one-based)
295 | and returns boolean for whether the cells should be
296 | included or not. The function should be vectorized.
297 | :type func: Callable[(int, int, int), bool]
298 |
299 | >>> layr = cell_filter (grid, lamba i, j, k: np.greater_equal (k, 56))
300 | """
301 | # extract the dimensions; notice that the i-dimensions is first
302 | # in this list, since it is directly from the grid
303 | ni, nj, nk = grid['DIMENS'] # pylint: disable=invalid-name
304 |
305 | # setup a grid of the i, j and k address for each of the cells;
306 | # notice that now the order of the dimensions are swapped so that
307 | # they fit with the memory layout of a loaded Numpy array
308 | kji = np.mgrid[1:(nk+1), 1:(nj+1), 1:(ni+1)]
309 |
310 | # call the filter function on all these addresses, and simply
311 | # return the boolean array of those
312 | filter_flags = func(kji[2], kji[1], kji[0])
313 | masked = filter_flags.astype(np.bool)
314 |
315 | # get the mask of active cells, and combine this with the masked
316 | # cells from the filter, giving us a flag for all visible nodes
317 | active = grid['ACTNUM']
318 | visible = np.logical_and(active, masked)
319 |
320 | return visible
321 |
322 |
323 | def face_coords(grid):
324 | """Get (x, y, z) coordinates for each corner-point.
325 |
326 | :param grid: Cornerpoint-grid
327 | :type grid: dict
328 | :returns: Coordinate values for each corner. Use the Face enum to index
329 | the first dimension, k, j, i coordinates to index the next
330 | three, and Dim enum to index the last dimension.
331 | Note that the first point in a face is not necessarily the
332 | point that is closest to the origin of the grid.
333 | :rtype: :class:`numpy.ndarray`, shape = (8, nk, nj, ni, 3)
334 |
335 | >>> import numpy as np
336 | >>> import pyresito.io.ecl as ecl
337 | >>> import pyresito.grid.cornerpoint as cp
338 | >>> case = ecl.EclipseCase ("FOO")
339 | >>> coord_fijkd = cp.face_coords (case.grid ())
340 | >>> # get the midpoint of the upper face in each cell
341 | >>> up_mid = np.average (coord_fijkd [cp.Face.UP, :, :, :, :], axis = 0)
342 | """
343 | # get coordinates in native corner-point format
344 | xyz = corner_coordinates(grid['COORD'], grid['ZCORN'])
345 |
346 | # get extent of grid
347 | ni, nj, nk = grid['DIMENS']
348 |
349 | # break up the latter dimension into a many-dimensional hypercube; this
350 | # is an inexpensive operation since it won't have to reshuffle the memory
351 | xyz = np.reshape(xyz, (3, nk, 2, nj, 2, ni, 2))
352 |
353 | # move all the dimensions local within an element to the front
354 | xyz = np.transpose(xyz, (2, 4, 6, 1, 3, 5, 0))
355 |
356 | # coalesce the local dimensions so that they end up in one dimension
357 | # which can be indexed by the Face enum to extract a certain field
358 | xyz = np.reshape(xyz, (8, nk, nj, ni, 3))
359 |
360 | return xyz
361 |
362 |
363 | def horizon(grid, layer=0, top=True):
364 | """Extract the points that are in a certain horizon and average them so
365 | that the result is per cell and not per pillar.
366 |
367 | :param grid: Grid structure
368 | :type grid: dict
369 | :param layer: The K index of the horizon. Default is the layer at the top.
370 | :type layer: int
371 | :param top: Whether the top face should be exported. If this is False,
372 | then the bottom face is exported instead.
373 | :type top: bool
374 | :returns: Depth at the specified horizon for each cell center
375 | :rtype: :class:`numpy.ma.array`, shape = (nk, nj, ni),
376 | dtype = numpy.float64
377 | """
378 | # get the dimensions of the grid. notice that this array is always given
379 | # in Fortran order (since Eclipse works that way) and not in native order
380 | num_i, num_j, _ = grid['DIMENS']
381 |
382 | # zcorn is nk * (up,down) * nj * (front,back) * ni * (left,right). we first
383 | # project the particular layer and face that we want to work with, ending
384 | # up with four corners for each cell.
385 | vertical = 0 if top else 1
386 | corners = grid['ZCORN'][layer, vertical, :, :, :, :]
387 |
388 | # move the second and fourth dimension (front/back and left/right) to the
389 | # back and collapse them into one dimension, meaning that we get
390 | # (nj, ni, 4). then take the average across this last dimension, ending up
391 | # with an (nj, ni) grid, which is what we return
392 | heights = np.average(np.reshape(np.transpose(
393 | corners, axes=(0, 2, 1, 3)), (num_j, num_i, 2*2)), axis=2)
394 |
395 | # if there are any inactive elements, then mask out the elevation at that
396 | # spot (it is not really a part of the grid)
397 | actnum = grid['ACTNUM'][layer, :, :]
398 | return ma.array(data=heights, mask=np.logical_not(actnum))
399 |
400 |
401 | def _reduce_corners(plane, red_op):
402 | """
403 | :param plane: Z-coordinates for a specific horizon in the grid
404 | :type plane: :class:`numpy.ndarray`, shape = (nj, 2, ni, 2)
405 | :param red_op: How coordinates are merged (reduction operator): either
406 | numpy.minimum or np.maximum, depending on top or bottom
407 | :type red_op: :class:`numpy.ufunc`
408 | :returns: Extremal value of each point around the corners.
409 | :rtype: :class:`numpy.ndarray`, shape = (nj+1, ni+1)
410 |
411 | >> plane = np.reshape (np.arange (36) + 1, (3, 2, 3, 2))
412 | >> _reduce_corners (plane, np.minimum)
413 | """
414 | # constants
415 | NORTH = 1
416 | SOUTH = 0
417 | EAST = 1
418 | WEST = 0
419 |
420 | # get dimensions of the domain
421 | nj, _, ni, _ = plane.shape
422 |
423 | # allocate output memory for all pillars
424 | out = np.empty((nj + 1, ni + 1), dtype=np.float64)
425 |
426 | # views into the original plane, getting a specific corner in every cell.
427 | # these views then have dimensions (nj, ni)
428 | nw = plane[:, NORTH, :, WEST]
429 | ne = plane[:, NORTH, :, EAST]
430 | sw = plane[:, SOUTH, :, WEST]
431 | se = plane[:, SOUTH, :, EAST]
432 |
433 | # four corners of the output grid only have a single value. the views have
434 | # indices 0..n-1, the output array have indices 0..n
435 | out[0, 0] = sw[0, 0]
436 | out[nj, 0] = nw[nj-1, 0]
437 | out[0, ni] = se[0, ni-1]
438 | out[nj, ni] = ne[nj-1, ni-1]
439 |
440 | # four edges contains values from two windows; first two horizontal edges,
441 | # (varying along i), then two vertical edges (varying along j). recall that
442 | # *ranges* in Python have inclusive start, exclusive end.
443 | out[0, 1:ni] = red_op(sw[0, 1:ni], se[0, 0:ni-1])
444 | out[nj, 1:ni] = red_op(nw[nj-1, 1:ni], ne[nj-1, 0:ni-1])
445 | out[1:nj, 0] = red_op(nw[0:nj-1, 0], sw[1:nj, 0])
446 | out[1:nj, ni] = red_op(ne[0:nj-1, ni-1], se[1:nj, ni-1])
447 |
448 | # interior have two nested reduction operations
449 | out[1:nj, 1:ni] = red_op(
450 | red_op(nw[0:nj-1, 1:ni], sw[1:nj, 1:ni]),
451 | red_op(ne[0:nj-1, 0:ni-1], se[1:nj, 0:ni-1]))
452 |
453 | return out
454 |
455 |
456 | def horizon_pillars(grid, layer=0, top=True):
457 | """Extract heights where a horizon crosses the pillars.
458 |
459 | :param grid: Grid structure, containing both COORD and ZCORN properties.
460 | :type grid: dict
461 | :param layer: The K index of the horizon. Default is the layer at the top.
462 | :type layer: int
463 | :param top: Whether the top face should be exported. If this false is
464 | False, then the bottom face is exported instead.
465 | :type top: bool
466 | :returns: Heights of the horizon at each pillar, in the same format as
467 | the COORD matrix.
468 | :rtype: :class:`numpy.ndarray`, shape = (nj+1, ni+1, 2, 3)
469 | """
470 | # NumPy's average operations finds the average within arrays, but we want
471 | # an operation that can take the average across two arrays
472 | def avg_op(a, b):
473 | return 0.5 * (a + b)
474 |
475 | # zcorn is nk * (up,down) * nj * (front,back) * ni * (left,right). we first
476 | # project the particular layer and face that we want to work with, ending
477 | # up with four corners for each cell. take the average of the heights that
478 | # are hinged up on each pillar to get a "smooth" surface. (this will not be
479 | # the same surface that the cornerpoint grid was created from).
480 | vertical = 0 if top else 1
481 | points = _reduce_corners(grid['ZCORN'][layer, vertical, :, :, :, :],
482 | avg_op)
483 | return points
484 |
485 |
486 | def snugfit(grid):
487 | """Create coordinate pillars that matches exactly the top and bottom
488 | horizon of the grid cells.
489 |
490 | This version assumes that the pillars in the grid are all strictly
491 | vertical, i.e. the x- and y-coordinates will not be changed.
492 |
493 | :param grid: Grid structure, containing both COORD and ZCORN properties.
494 | :type grid: dict
495 | :returns: Pillar coordinates, in the same format as the COORD matrix.
496 | Note that a new matrix is returned, the original grid is not
497 | altered/updated.
498 | :rtype: :class:`numpy.ndarray`, shape = (nj+1, ni+1, 2, 3)
499 | """
500 | # placement in the plane of each pillar is unchanged
501 | x = grid['COORD'][:, :, 0, 0]
502 | y = grid['COORD'][:, :, 0, 1]
503 |
504 | # get implicit dimension of grid
505 | njp1, nip1 = x.shape
506 |
507 | # get new top and bottom from the z-coordinates; smaller z is shallower
508 | top = _reduce_corners(grid['ZCORN'][0, 0, :, :, :, :], np.minimum)
509 | btm = _reduce_corners(grid['ZCORN'][-1, 1, :, :, :, :], np.maximum)
510 |
511 | # combine coordinates to a pillar grid with new z-coordinates
512 | coord = np.reshape(np.dstack((
513 | x.ravel(), y.ravel(), top.ravel(),
514 | x.ravel(), y.ravel(), btm.ravel())), (njp1, nip1, 2, 3))
515 |
516 | return coord
517 |
518 |
519 | def bounding_box(corn, filtr):
520 | """\
521 | Bounding box of the grid. This function will always assume that the grid
522 | is aligned with the geographical axes.
523 |
524 | :param corn: Coordinate values for each corner. This matrix can be
525 | constructed with the `corner_coordinates` function.
526 | :type corn: :class:`numpy.ndarray`, shape=(3, nk*2*nj*2*ni*2)
527 | :param filtr: Active corners; use scatter of ACTNUM if no filtering
528 | :type filtr: :class:`numpy.ndarray`, shape = (nk, 2, nj, 2, ni, 2),
529 | dtype = numpy.bool
530 | :return: Bottom front right corner and top back left corner. Since
531 | the matrix is returned with C ordering, it is specified the
532 | opposite way of what is natural for mathematical matrices.
533 | :rtype: :class:`numpy.ndarray`, shape = (2, 3), dtype = np.float64
534 |
535 | >>> corn = corner_coordinates(grid['COORD'], grid['ZCORN'])
536 | >>> bbox = bounding_box(corn, scatter(grid['ACTNUM']))
537 | >>> p, q = bbox[0, :], bbox[1, :]
538 | >>> diag = np.sqrt(np.dot(q - p, q - p))
539 | """
540 | # scatter the filter mask from each cell to its corners
541 | mask = np.logical_not(filtr).ravel()
542 |
543 | # build arrays of each separate coordinate based on its inclusion
544 | x_vals = ma.array(data=corn[0, :], mask=mask)
545 | y_vals = ma.array(data=corn[1, :], mask=mask)
546 | z_vals = ma.array(data=corn[2, :], mask=mask)
547 |
548 | # construct bounding box that includes all coordinates in visible grid
549 | bbox = np.array([[np.min(x_vals), np.min(y_vals), np.min(z_vals)],
550 | [np.max(x_vals), np.max(y_vals), np.max(z_vals)]],
551 | dtype=corn.dtype)
552 | return bbox
553 |
554 |
555 | def mass_center(corn, filtr):
556 | """\
557 | Mass center of the grid. This function will always assume that the density
558 | is equal throughout the field.
559 |
560 | :param corn: Coordinate values for each corner. This matrix can be
561 | constructed with the `corner_coordinates` function.
562 | :type corn: :class:`numpy.ndarray`, shape=(3, nk*2*nj*2*ni*2)
563 | :param filtr: Active corners; use scatter of ACTNUM if no filtering
564 | :type filtr: :class:`numpy.ndarray`, shape = (nk, 2, nj, 2, ni, 2),
565 | dtype = numpy.bool
566 | :return: Center of mass. This should be the focal point of the grid.
567 | :rtype: :class:`numpy.ndarray`, shape = (3,), dtype = np.float64
568 |
569 | >>> corn = cp.corner_coordinates(grid['COORD'], grid['ZCORN'])
570 | >>> focal_point = cp.mass_center(corn, cp.scatter(grid['ACTNUM']))
571 | """
572 | # scatter the filter mask from each cell to its corners
573 | mask = np.logical_not(filtr).ravel()
574 |
575 | # build arrays of each separate coordinate based on its inclusion
576 | x_vals = ma.array(data=corn[0, :], mask=mask)
577 | y_vals = ma.array(data=corn[1, :], mask=mask)
578 | z_vals = ma.array(data=corn[2, :], mask=mask)
579 |
580 | # use this as a coarse approximation to find the element center
581 | center = np.array([np.average(x_vals),
582 | np.average(y_vals),
583 | np.average(z_vals)], dtype=corn.dtype)
584 | return center
585 |
--------------------------------------------------------------------------------
/src/subsurface/rockphysics/standardrp.py:
--------------------------------------------------------------------------------
1 | """Descriptive description."""
2 |
3 | __author__ = 'TM'
4 |
5 | # standardrp.py
6 | import numpy as np
7 | import sys
8 | import multiprocessing as mp
9 | # internal load
10 | from misc.system_tools.environ_var import OpenBlasSingleThread # Single threaded OpenBLAS runs
11 |
12 |
13 | class elasticproperties:
14 | """
15 | Calculate elastic properties from standard
16 | rock-physics models, specifically following Batzle
17 | and Wang, Geophysics, 1992, for fluid properties, and
18 | Report 1 in Abul Fahimuddin's thesis at Universty of
19 | Bergen (2010) for other properties.
20 |
21 | Examples
22 | --------
23 | >>> porosity = 0.2
24 | ... pressure = 5
25 | ... phases = ["Oil","Water"]
26 | ... saturations = [0.3, 0.5]
27 | ...
28 | ... satrock = Elasticproperties()
29 | ... satrock.calc_props(phases, saturations, pressure, porosity)
30 | """
31 |
32 | def __init__(self, input_dict):
33 | self.dens = None
34 | self.bulkmod = None
35 | self.shearmod = None
36 | self.bulkvel = None
37 | self.shearvel = None
38 | self.bulkimp = None
39 | self.shearimp = None
40 | # The overburden for each grid cell must be
41 | # specified as values on an .npz-file whose
42 | # name is given in input_dict.
43 | self.input_dict = input_dict
44 | self._extInfoInputDict()
45 |
46 | def _extInfoInputDict(self):
47 | # The key word for the file name in the
48 | # dictionary must read "overburden"
49 | if 'overburden' in self.input_dict:
50 | obfile = self.input_dict['overburden']
51 | npzfile = np.load(obfile)
52 | # The values of overburden must have been
53 | # stored on file using:
54 | # np.savez(,
55 | # obvalues=)
56 | self.overburden = npzfile['obvalues']
57 | npzfile.close()
58 | if 'baseline' in self.input_dict:
59 | self.baseline = self.input_dict['baseline'] # 4D baseline
60 | if 'parallel' in self.input_dict:
61 | self.parallel = self.input_dict['parallel']
62 |
63 | def _filter(self):
64 | bulkmod = self.bulkimp
65 | self.bulkimp = bulkmod.flatten()
66 |
67 | def setup_fwd_run(self, state):
68 | """
69 | Setup the input parameters to be used in the PEM simulator. Parameters can be a an ensemble or a single array.
70 | State is set as an attribute of the simulator, and the correct value is determined in self.pem.calc_props()
71 |
72 | Parameters
73 | ----------
74 | state : dict
75 | Dictionary of input parameters or states.
76 |
77 | Changelog
78 | ---------
79 | - KF 11/12-2018
80 | """
81 | # self.inv_state = {}
82 | # list_pem_param =[el for el in [foo for foo in self.pem['garn'].keys()] + [foo for foo in self.filter.keys()] +
83 | # [foo for foo in self.__dict__.keys()]]
84 |
85 | # list_tot_param = state.keys()
86 | # for param in list_tot_param:
87 | # if param in list_pem_param or (param.split('_')[-1] in ['garn', 'rest']):
88 | # self.inv_state[param] = state[param]
89 |
90 | pass
91 |
92 | def calc_props(self, phases, saturations, pressure,
93 | porosity, dens = None, wait_for_proc=None, ntg=None, Rs=None, press_init=None, ensembleMember=None):
94 | ###
95 | # This doesn't initialize for models with no uncertainty
96 | ###
97 | # # if some PEM properties have uncertainty, set the correct value
98 | # if ensembleMember is not None:
99 | # for pem_state in self.__dict__.keys(): # loop over all possible pem vaules
100 | # if pem_state is not 'inv_state': # do not alter the ensemble
101 | # if type(eval('self.{}'.format(pem_state))) is dict:
102 | # for el in eval('self.{}'.format(pem_state)).keys():
103 | # if type(eval('self.{}'.format(pem_state))[el]) is dict:
104 | # for param in eval('self.{}'.format(pem_state))[el].keys():
105 | # if param in self.inv_state:
106 | # eval('self.{}'.format(pem_state))[el][param]=\
107 | # self.inv_state[param][:, ensembleMember]
108 | # elif param + '_' + el in self.inv_state:
109 | # eval('self.{}'.format(pem_state))[el][param] = \
110 | # self.inv_state[param+'_' + el][:, ensembleMember]
111 | # else:
112 | # if el in self.inv_state:
113 | # eval('self.{}'.format(pem_state))[el] = self.inv_state[el][:,ensembleMember]
114 | # else:
115 | # if pem_state in self.inv_state:
116 | # setattr(self,pem_state, self.inv_state[pem_state][:,ensembleMember])
117 |
118 | # Check if the inputs are given as a list (more
119 | # than one phase) or a single input (single
120 | # phase). If single phase input, make the input a
121 | # list with a single entry (s.t. it can be used
122 | # directly with the methods below)
123 | #
124 | if not isinstance(phases, list):
125 | phases = [phases]
126 | if not isinstance(saturations, list):
127 | saturations = [saturations]
128 | if not isinstance(pressure, list) and \
129 | type(pressure).__module__ != 'numpy':
130 | pressure = [pressure]
131 | if not isinstance(porosity, list) and \
132 | type(porosity).__module__ != 'numpy':
133 | porosity = [porosity]
134 | #
135 | # Load "overburden" into local variable to
136 | # comply with remaining code parts
137 | overburden = self.overburden
138 |
139 | if press_init is None:
140 | p_init = self.p_init
141 | else:
142 | p_init = press_init
143 | #
144 | poverburden = self.overburden
145 |
146 | # debug
147 | self.pressure = pressure
148 | self.peff = poverburden - pressure
149 | self.porosity = porosity
150 |
151 | # Check that no. of phases is equal to no. of
152 | # entries in saturations list
153 | #
154 | assert (len(saturations) == len(phases))
155 | #
156 | # Make saturation a Numpy array (so that we
157 | # can easily access the values for each
158 | # phase at one grid cell)
159 | #
160 | # Transpose makes it a no. grid cells x phases
161 | # array
162 | saturations = np.array(saturations).T
163 | #
164 | # Check if we actually inputted saturation values
165 | # for a single grid cell. If yes, we redefine
166 | # saturations to get it on the correct form (no.
167 | # grid cells x phases array).
168 | #
169 | if saturations.ndim == 1:
170 | saturations = \
171 | np.array([[x] for x in saturations]).T
172 | #
173 | # Loop over all grid cells and calculate the
174 | # various saturated properties
175 | #
176 | self.phases = phases
177 |
178 | self.dens = np.zeros(len(saturations[:, 0]))
179 | self.bulkmod = np.zeros(len(saturations[:, 0]))
180 | self.shearmod = np.zeros(len(saturations[:, 0]))
181 | self.bulkvel = np.zeros(len(saturations[:, 0]))
182 | self.shearvel = np.zeros(len(saturations[:, 0]))
183 | self.bulkimp = np.zeros(len(saturations[:, 0]))
184 | self.shearimp = np.zeros(len(saturations[:, 0]))
185 |
186 | if ntg is None:
187 | ntg = [None for _ in range(len(saturations[:, 0]))]
188 | if Rs is None:
189 | Rs = [None for _ in range(len(saturations[:, 0]))]
190 | if p_init is None:
191 | p_init = [None for _ in range(len(saturations[:, 0]))]
192 |
193 | for i in range(len(saturations[:, 0])):
194 | #
195 | # Calculate fluid properties
196 | #
197 | # set Rs if needed
198 | densf, bulkf = \
199 | self._fluidprops(self.phases,
200 | saturations[i, :], pressure[i], Rs[i])
201 | #
202 | denss, bulks, shears = \
203 | self._solidprops(porosity[i], ntg[i], i)
204 | #
205 | # Calculate dry rock moduli
206 | #
207 |
208 | bulkd, sheard = \
209 | self._dryrockmoduli(porosity[i],
210 | overburden[i],
211 | pressure[i], bulks,
212 | shears, i, ntg[i], p_init[i], denss, Rs[i], self.phases)
213 | # -------------------------------
214 | # Calculate saturated properties
215 | # -------------------------------
216 | #
217 | # Density
218 | #
219 | self.dens[i] = (porosity[i]*densf + (1-porosity[i])*denss)
220 | #
221 | # Moduli
222 | #
223 | self.bulkmod[i] = \
224 | bulkd + (1 - bulkd/bulks)**2 / \
225 | (porosity[i]/bulkf +
226 | (1-porosity[i])/bulks -
227 | bulkd/(bulks**2))
228 | self.shearmod[i] = sheard
229 |
230 | # Velocities (due to bulk/shear modulus being
231 | # in MPa, we multiply by 1000 to get m/s
232 | # instead of km/s)
233 | #
234 | self.bulkvel[i] = \
235 | 1000*np.sqrt((abs(self.bulkmod[i]) +
236 | 4*self.shearmod[i]/3)/(self.dens[i]))
237 | self.shearvel[i] = \
238 | 1000*np.sqrt(self.shearmod[i] /
239 | (self.dens[i]))
240 | #
241 | # Impedances (m/s)*(Kg/m3)
242 | #
243 | self.bulkimp[i] = self.dens[i] * \
244 | self.bulkvel[i]
245 | self.shearimp[i] = self.dens[i] * \
246 | self.shearvel[i]
247 |
248 | def getMatchProp(self, petElProp):
249 | if petElProp.lower() == 'density':
250 | self.match_prop = self.getDens()
251 | elif petElProp.lower() == 'bulk_modulus':
252 | self.match_prop = self.getBulkMod()
253 | elif petElProp.lower() == 'shear_modulus':
254 | self.match_prop = self.getShearMod()
255 | elif petElProp.lower() == 'bulk_velocity':
256 | self.match_prop = self.getBulkVel()
257 | elif petElProp.lower() == 'shear_velocity':
258 | self.match_prop = self.getShearVel()
259 | elif petElProp.lower() == "bulk_impedance":
260 | self.match_prop = self.getBulkImp()
261 | elif petElProp.lower() == 'shear_impedance':
262 | self.match_prop = self.getShearImp()
263 | else:
264 | print("\nError in getMatchProp method")
265 | print("No model output type selected for "
266 | "data match.")
267 | print("Legal model output types are "
268 | "(case insensitive):")
269 | print("Density, bulk modulus, shear "
270 | "modulus, bulk velocity,")
271 | print("shear velocity, bulk impedance, "
272 | "shear impedance")
273 | sys.exit(1)
274 | return self.match_prop
275 |
276 | def getDens(self):
277 | return self.dens
278 |
279 | def getBulkMod(self):
280 | return self.bulkmod
281 |
282 | def getShearMod(self):
283 | return self.shearmod
284 |
285 | def getBulkVel(self):
286 | return self.bulkvel
287 |
288 | def getShearVel(self):
289 | return self.shearvel
290 |
291 | def getBulkImp(self):
292 | return self.bulkimp
293 |
294 | def getShearImp(self):
295 | return self.shearimp
296 |
297 | def getOverburdenP(self):
298 | return self.overburden
299 |
300 | def getPressure(self):
301 | return self.pressure
302 |
303 | def getPeff(self):
304 | return self.peff
305 |
306 | def getPorosity(self):
307 | return self.porosity
308 | #
309 | # ===================================================
310 | # Fluid properties start
311 | # ===================================================
312 | #
313 | def _fluidprops(self, fphases, fsats, fpress, Rs=None):
314 | #
315 | # Calculate fluid density and bulk modulus
316 | #
317 | #
318 | # Input
319 | # fphases - fluid phases present; Oil
320 | # and/or Water and/or Gas
321 | # fsats - fluid saturation values for
322 | # fluid phases in "fphases"
323 | # fpress - fluid pressure value (MPa)
324 | # Rs - Gas oil ratio. Default value None
325 |
326 | #
327 | # Output
328 | # fdens - density of fluid mixture for
329 | # pressure value "fpress" inherited
330 | # from phaseprops)
331 | # fbulk - bulk modulus of fluid mixture for
332 | # pressure value "fpress" (unit
333 | # inherited from phaseprops)
334 | #
335 | # -----------------------------------------------
336 | #
337 | fdens = 0.0
338 | fbinv = 0.0
339 |
340 | for i in range(len(fphases)):
341 | #
342 | # Calculate mixture properties by summing
343 | # over individual phase properties
344 | #
345 | pdens, pbulk = self._phaseprops(fphases[i],
346 | fpress, Rs)
347 | fdens = fdens + fsats[i]*abs(pdens)
348 | fbinv = fbinv + fsats[i]/abs(pbulk)
349 | fbulk = 1.0/fbinv
350 | #
351 | return fdens, fbulk
352 | #
353 | # ---------------------------------------------------
354 | #
355 |
356 | def _phaseprops(self, fphase, press, Rs=None):
357 | #
358 | # Calculate properties for a single fluid phase
359 | #
360 | #
361 | # Input
362 | # fphase - fluid phase; Oil, Water or Gas
363 | # press - fluid pressure value (MPa)
364 | #
365 | # Output
366 | # pdens - phase density of fluid phase
367 | # "fphase" for pressure value
368 | # "press" (kg/m³)
369 | # pbulk - bulk modulus of fluid phase
370 | # "fphase" for pressure value
371 | # "press" (MPa)
372 | #
373 | # -----------------------------------------------
374 | #
375 | if fphase.lower() == "oil":
376 | coeffsrho = np.array([0.8, 829.9])
377 | coeffsbulk = np.array([10.42, 995.79])
378 | elif fphase.lower() == "wat":
379 | coeffsrho = np.array([0.3, 1067.3])
380 | coeffsbulk = np.array([9.0, 2807.6])
381 | elif fphase.lower() == "gas":
382 | coeffsrho = np.array([4.7, 13.4])
383 | coeffsbulk = np.array([2.75, 0.0])
384 | else:
385 | print("\nError in phaseprops method")
386 | print("Illegal fluid phase name.")
387 | print("Legal fluid phase names are (case "
388 | "insensitive): Oil, Wat, and Gas.")
389 | sys.exit(1)
390 | #
391 | # Assume simple linear pressure dependencies.
392 | # Coefficients are inferred from
393 | # plots in Batzle and Wang, Geophysics, 1992,
394 | # (where I set the temperature to be 100 degrees
395 | # Celsius, Note also that they give densities in
396 | # g/cc). The resulting straight lines do not fit
397 | # the data extremely well, but they should
398 | # be sufficiently accurate for the purpose of
399 | # this project.
400 | #
401 | pdens = coeffsrho[0]*press + coeffsrho[1]
402 | pbulk = coeffsbulk[0]*press + coeffsbulk[1]
403 | #
404 | return pdens, pbulk
405 |
406 | #
407 | # =======================
408 | # Fluid properties end
409 | # =======================
410 | #
411 |
412 | #
413 | # =========================
414 | # Solid properties start
415 | # =========================
416 | #
417 | def _solidprops(self, poro, ntg=None, ind=None):
418 | #
419 | # Calculate bulk and shear solid rock (mineral)
420 | # moduli by averaging Hashin-Shtrikman bounds
421 | #
422 | #
423 | # Input
424 | # poro -porosity
425 | #
426 | # Output
427 | # denss - solid rock density (kg/m³)
428 | # bulks - solid rock bulk modulus (unit
429 | # inherited from hashinshtr)
430 | # shears - solid rock shear modulus (unit
431 | # inherited from hashinshtr)
432 | #
433 | # -----------------------------------------------
434 | #
435 | # From PetroWiki (kg/m³)
436 | #
437 | densc = 2540
438 | densq = 2650
439 | #
440 | # From "Step 1" of "recipe" in Report 1 in Abul
441 | # Fahimuddin's thesis.
442 | #
443 | vclay = 0.7 - 1.58*poro
444 | #
445 | # Calculate solid rock (mineral) density. (Note
446 | # that this is often termed \rho_dry, and not
447 | # \rho_s)
448 | #
449 | denss = densq + vclay*(densc - densq)
450 | #
451 | # Calculate lower and upper bulk and shear
452 | # Hashin-Shtrikman bounds
453 | #
454 | bulkl, bulku, shearl, shearu = \
455 | self._hashinshtr(vclay)
456 | #
457 | # Calculate bulk and shear solid rock (mineral)
458 | # moduli as arithmetic means of the respective
459 | # bounds
460 | #
461 | bulkb = np.array([bulkl, bulku])
462 | shearb = np.array([shearl, shearu])
463 | bulks = np.mean(bulkb)
464 | shears = np.mean(shearb)
465 | #
466 | return denss, bulks, shears
467 | #
468 | # ---------------------------------------------------
469 | #
470 |
471 | def _hashinshtr(self, vclay):
472 | #
473 | # Calculate lower and upper, bulk and shear,
474 | # Hashin-Shtrikman bounds, utilizing that they
475 | # all have the common mathematical form,
476 | #
477 | # f = a + b/((1/c) + d*(1/e)).
478 | #
479 | #
480 | # Input
481 | # vclay - "volume of clay"
482 | #
483 | # Output
484 | # bulkl - lower bulk Hashin-Shtrikman
485 | # bound (MPa)
486 | # bulku - upper bulk Hashin-Shtrikman
487 | # bound (MPa)
488 | # shearl - lower shear Hashin-Shtrikman
489 | # bound (MPa)
490 | # shearu - upper shear Hashin-Shtrikman
491 | # bound (MPa)
492 | #
493 | # -----------------------------------------------
494 | #
495 | # From table 1 in Report 1 in Abul Fahimuddin's
496 | # thesis (he used GPa, I use MPa), ("c" for clay
497 | # and "q" for quartz.):
498 | #
499 | bulkc = 14900
500 | bulkq = 37000
501 | shearc = 1950
502 | shearq = 44000
503 | #
504 | # Calculate quantities common for both bulk and
505 | # shear formulas
506 | #
507 | lb = 1 - vclay
508 | ub = vclay
509 | le = bulkc + 4*shearc/3
510 | ue = bulkq + 4*shearq/3
511 | #
512 | # Calculate quantities common only for bulk
513 | # formulas
514 | #
515 | bld = vclay
516 | bud = 1 - vclay
517 | blc = bulkq - bulkc
518 | buc = bulkc - bulkq
519 | #
520 | # Calculate quantities common only for shear
521 | # formulas
522 | #
523 | sld = 2*vclay*(bulkc + 2*shearc)/(5*shearc)
524 | sud = 2*(1 - vclay)*(bulkq + 2*shearq)/(5*shearq)
525 | slc = shearq - shearc
526 | suc = shearc - shearq
527 | #
528 | # Calculate bounds utilizing generic formula;
529 | # f = a + b/((1/c) + d*(1/e)).
530 | #
531 | # Lower bulk
532 | #
533 | bulkl = self._genhashinshtr(bulkc, lb, blc, bld,
534 | le)
535 | #
536 | # Upper bulk
537 | #
538 | bulku = self._genhashinshtr(bulkq, ub, buc, bud,
539 | ue)
540 | #
541 | # Lower shear
542 | #
543 | shearl = self._genhashinshtr(shearc, lb, slc,
544 | sld, le)
545 | #
546 | # Upper shear
547 | #
548 | shearu = self._genhashinshtr(shearq, ub, suc,
549 | sud, ue)
550 | #
551 | return bulkl, bulku, shearl, shearu
552 |
553 | #
554 | # ---------------------------------------------------
555 | #
556 | def _genhashinshtr(self, a, b, c, d, e):
557 | #
558 | # Calculate arbitrary Hashin-Shtrikman bound,
559 | # which has the generic form
560 | #
561 | # f = a + b/((1/c) + d*(1/e))
562 | #
563 | # both for lower and upper bulk and shear bounds
564 | #
565 | #
566 | # Input
567 | # a - see above formula
568 | # b - see above formula
569 | # c - see above formula
570 | # d - see above formula
571 | # e - see above formula
572 | #
573 | # Output
574 | # f - Bulk or shear Hashin-Shtrikman bound
575 | # value
576 | #
577 | # -----------------------------------------------
578 | #
579 | cinv = 1/c
580 | einv = 1/e
581 | f = a + b/(cinv + d*einv)
582 | #
583 | return f
584 | #
585 | # =======================
586 | # Solid properties end
587 | # =======================
588 | #
589 |
590 | #
591 | # ============================
592 | # Dry rock properties start
593 | # ============================
594 | #
595 | def _dryrockmoduli(self, poro, poverb, pfluid, bulks, shears, ind=None, ntg=None, p_init=None, denss=None, Rs=None, phases=None):
596 | #
597 | #
598 | # Calculate bulk and shear dry rock moduli,
599 | # utilizing that they have the common
600 | # mathematical form,
601 | #
602 | # -- -- ^(-1)
603 | # |(poro/poroc) 1 - (poro/poroc)|
604 | # f = |------------ + ----------------| - z.
605 | # | a + z b + z |
606 | # --. --
607 | #
608 | #
609 | # Input
610 | # poro - porosity
611 | # poverb - overburden pressure (MPa)
612 | # pfluid - fluid pressure (MPa)
613 | # bulks - bulk solid (mineral) rock bulk
614 | # modulus (MPa)
615 | # shears - solid rock (mineral) shear
616 | # modulus (MPa)
617 | #
618 | # Output
619 | # bulkd - dry rock bulk modulus (unit
620 | # inherited from hertzmindlin and
621 | # variable; bulks)
622 | # sheard - dry rock shear modulus (unit
623 | # inherited from hertzmindlin and
624 | # variable; shears)
625 | #
626 | # -----------------------------------------------
627 | #
628 | # Calculate Hertz-Mindlin moduli
629 | #
630 | bulkhm, shearhm = self._hertzmindlin(poverb,
631 | pfluid)
632 | #
633 | # From table 1 in Report 1 in Abul Fahimuddin's
634 | # thesis (I assume \phi_max in that
635 | # table corresponds to \phi_c in his formulas):
636 | #
637 | poroc = 0.4
638 | #
639 | # Calculate input common to both bulk and
640 | # shear formulas
641 | #
642 | poratio = poro/poroc
643 | #
644 | # Calculate input to bulk formula
645 | #
646 | ba = bulkhm
647 | bb = bulks
648 | bz = 4*shearhm/3
649 | #
650 | # Calculate input to shear formula
651 | #
652 | sa = shearhm
653 | sb = shears
654 | sz = (shearhm/6)*((9*bulkhm + 8*shearhm) /
655 | (bulkhm + 2*shearhm))
656 | #
657 | # Calculate moduli
658 | #
659 | bulkd = self._gendryrock(poratio, ba, bb, bz)
660 | sheard = self._gendryrock(poratio, sa, sb, sz)
661 | #
662 | return bulkd, sheard
663 | #
664 | # ---------------------------------------------------
665 | #
666 |
667 | def _hertzmindlin(self, poverb, pfluid):
668 | #
669 | # Calculate bulk and shear Hertz-Mindlin moduli
670 | # utilizing that they have the common
671 | # mathematical form,
672 | #
673 | # f = max*(peff/pref)^kappa.
674 | #
675 | #
676 | # Input
677 | # poverb - overburden pressure
678 | # pfluid - fluid pressure
679 | #
680 | # Output
681 | # bulkhm - Hertz-Mindlin bulk modulus
682 | # (MPa)
683 | # shearhm - Hertz-Mindlin shear modulus
684 | # (MPa)
685 | #
686 | # -----------------------------------------------
687 | #
688 | # From table 1 in Report 1 in Abul Fahimuddin's
689 | # thesis (he used GPa for the moduli, I use MPa
690 | # also for them):
691 | #
692 | bulkmax = 3310
693 | shearmax = 2840
694 | pref = 8.8
695 | kappa = 0.233
696 | #
697 | # Calculate moduli
698 | #
699 | peff = poverb - pfluid
700 | if peff < 0:
701 | print("\nError in _hertzmindlin method")
702 | print("Negative effective pressure (" + str(peff) +
703 | "). Setting effective pressure to 0.01")
704 | peff = 0.01
705 | # sys.exit(1)
706 | common = (peff/pref)**kappa
707 | bulkhm = bulkmax*common
708 | shearhm = shearmax*common
709 | #
710 | return bulkhm, shearhm
711 | #
712 | # ---------------------------------------------------
713 | #
714 |
715 | def _gendryrock(self, q, a, b, z):
716 | #
717 | # Calculate arbitrary dry rock moduli, which has
718 | # the generic form
719 | #
720 | # -- -- ^(-1)
721 | # | q 1 - q |
722 | # f = |------------ + ----------------| - z,
723 | # | a + z b + z |
724 | # --. --
725 | #
726 | # both for bulk and shear moduli
727 | #
728 | #
729 | # Input
730 | # q - see above formula
731 | # a - see above formula
732 | # b - see above formula
733 | # z - see above formula
734 | #
735 | # Output
736 | # f - Bulk or shear dry rock modulus value
737 | #
738 | # -----------------------------------------------
739 | #
740 | afrac = q/(a + z)
741 | bfrac = (1 - q)/(b + z)
742 | f = 1/(afrac + bfrac) - z
743 | #
744 | return f
745 | # ===========================
746 | # Dry rock properties end
747 | # ===========================
748 |
749 |
750 | if __name__ == '__main__':
751 | #
752 | # Example input with two phases and three grid cells
753 | #
754 | porosity = [0.34999999, 0.34999999, 0.34999999]
755 | # pressure = [ 29.29150963, 29.14003944, 28.88845444]
756 | pressure = [29.3558, 29.2625, 29.3558]
757 | # pressure = [ 25.0, 25.0, 25.0]
758 | phases = ["Oil", "Wat"]
759 | # saturations = [[0.72783828, 0.66568458, 0.58033288],
760 | # [0.27216172, 0.33431542, 0.41966712]]
761 | saturations = [[0.6358, 0.5755, 0.6358],
762 | [0.3641, 0.4245, 0.3641]]
763 | # saturations = [[0.4, 0.5, 0.6],
764 | # [0.6, 0.5, 0.4]]
765 | petElProp = "bulk velocity"
766 | input_dict = {}
767 | input_dict['overburden'] = 'overb.npz'
768 |
769 | print("\nInput:")
770 | print("porosity, pressure:", porosity, pressure)
771 | print("phases, saturations:", phases, saturations)
772 | print("petElProp:", petElProp)
773 | print("input_dict:", input_dict)
774 |
775 | satrock = elasticproperties(input_dict)
776 |
777 | print("overburden:", satrock.overburden)
778 |
779 | satrock.calc_props(phases, saturations, pressure,
780 | porosity)
781 |
782 | print("\nOutput from calc_props:")
783 | print("Density:", satrock.getDens())
784 | print("Bulk modulus:", satrock.getBulkMod())
785 | print("Shear modulus:", satrock.getShearMod())
786 | print("Bulk velocity:", satrock.getBulkVel())
787 | print("Shear velocity:", satrock.getShearVel())
788 | print("Bulk impedance:", satrock.getBulkImp())
789 | print("Shear impedance:", satrock.getShearImp())
790 |
791 | satrock.getMatchProp(petElProp)
792 |
793 | print("\nOutput from getMatchProp:")
794 | print("Model output selected for data match:",
795 | satrock.match_prop)
796 |
--------------------------------------------------------------------------------
/src/subsurface/rockphysics/softsandrp.py:
--------------------------------------------------------------------------------
1 | """Descriptive description."""
2 |
3 | __author__ = {'TM', 'TB', 'ML'}
4 |
5 | # standardrp.py
6 | import numpy as np
7 | import sys
8 | import multiprocessing as mp
9 | from CoolProp.CoolProp import PropsSI # http://coolprop.org/#high-level-interface-example
10 | import CoolProp.CoolProp as CP
11 | # Density of carbon dioxide at 100 bar and 25C # Smeaheia 37 degrees C
12 | #rho_co2 = PropsSI('D', 'T', 298.15, 'P', 100e5, 'CO2')
13 | from numpy.random import poisson
14 |
15 | # internal load
16 | from misc.system_tools.environ_var import OpenBlasSingleThread # Single threaded OpenBLAS runs
17 |
18 |
19 | class elasticproperties:
20 | """
21 | Calculate elastic properties from standard
22 | rock-physics models, specifically following Batzle
23 | and Wang, Geophysics, 1992, for fluid properties, and
24 | Report 1 in Abul Fahimuddin's thesis at Universty of
25 | Bergen (2010) for other properties.
26 |
27 | Example
28 | -------
29 | >>> porosity = 0.2
30 | ... pressure = 5
31 | ... phases = ["Oil","Water"]
32 | ... saturations = [0.3, 0.5]
33 | ...
34 | ... satrock = Elasticproperties()
35 | ... satrock.calc_props(phases, saturations, pressure, porosity)
36 | """
37 |
38 | def __init__(self, input_dict):
39 | self.dens = None
40 | self.bulkmod = None
41 | self.shearmod = None
42 | self.bulkvel = None
43 | self.shearvel = None
44 | self.bulkimp = None
45 | self.shearimp = None
46 | # The overburden for each grid cell must be
47 | # specified as values on an .npz-file whose
48 | # name is given in input_dict.
49 | self.input_dict = input_dict
50 | self._extInfoInputDict()
51 |
52 | def _extInfoInputDict(self):
53 | # The key word for the file name in the
54 | # dictionary must read "overburden"
55 | if 'overburden' in self.input_dict:
56 | obfile = self.input_dict['overburden']
57 | npzfile = np.load(obfile)
58 | # The values of overburden must have been
59 | # stored on file using:
60 | # np.savez(,
61 | # obvalues=)
62 | self.overburden = npzfile['obvalues']
63 | npzfile.close()
64 | #else:
65 | # # Norne litho pressure equation in Bar
66 | # P_litho = -49.6 + 0.2027 * Z + 6.127e-6 * Z ** 2 # Using e-6 for scientific notation
67 | # # Convert reservoir pore pressure from Bar to MPa
68 | # P_litho *= 0.1
69 | # self.overburden = P_litho
70 |
71 | if 'baseline' in self.input_dict:
72 | self.baseline = self.input_dict['baseline'] # 4D baseline
73 | if 'parallel' in self.input_dict:
74 | self.parallel = self.input_dict['parallel']
75 |
76 | def _filter(self):
77 | bulkmod = self.bulkimp
78 | self.bulkimp = bulkmod.flatten()
79 |
80 | def setup_fwd_run(self, state):
81 | """
82 | Setup the input parameters to be used in the PEM simulator. Parameters can be an ensemble or a single array.
83 | State is set as an attribute of the simulator, and the correct value is determined in self.pem.calc_props()
84 |
85 | Parameters
86 | ----------
87 | state : dict
88 | Dictionary of input parameters or states.
89 |
90 | Changelog
91 | ---------
92 | - KF 11/12-2018
93 | """
94 | # self.inv_state = {}
95 | # list_pem_param =[el for el in [foo for foo in self.pem['garn'].keys()] + [foo for foo in self.filter.keys()] +
96 | # [foo for foo in self.__dict__.keys()]]
97 |
98 | # list_tot_param = state.keys()
99 | # for param in list_tot_param:
100 | # if param in list_pem_param or (param.split('_')[-1] in ['garn', 'rest']):
101 | # self.inv_state[param] = state[param]
102 |
103 | pass
104 |
105 | def calc_props(self, phases, saturations, pressure,
106 | porosity, dens = None, wait_for_proc=None, ntg=None, Rs=None, press_init=None, ensembleMember=None):
107 | ###
108 |
109 | #
110 | if not isinstance(phases, list):
111 | phases = [phases]
112 | if not isinstance(saturations, list):
113 | saturations = [saturations]
114 | if not isinstance(pressure, list) and \
115 | type(pressure).__module__ != 'numpy':
116 | pressure = [pressure]
117 | if not isinstance(porosity, list) and \
118 | type(porosity).__module__ != 'numpy':
119 | porosity = [porosity]
120 | #
121 | # Load "overburden" pressures into local variable to
122 | # comply with remaining code parts
123 | poverburden = self.overburden
124 |
125 | # debug
126 | self.pressure = pressure
127 | self.peff = poverburden - pressure
128 | self.porosity = porosity
129 |
130 | if press_init is None:
131 | p_init = self.p_init
132 | else:
133 | p_init = press_init
134 |
135 | # Average number of contacts that each grain has with surrounding grains
136 | coordnumber = self._coordination_number()
137 |
138 | # porosity value separating the porous media's mechanical and acoustic behaviour
139 | phicritical = self._critical_porosity()
140 |
141 |
142 | # Check that no. of phases is equal to no. of
143 | # entries in saturations list
144 | #
145 | assert (len(saturations) == len(phases))
146 | #
147 | # Make saturation a Numpy array (so that we
148 | # can easily access the values for each
149 | # phase at one grid cell)
150 | #
151 | # Transpose makes it a no. grid cells x phases
152 | # array
153 | saturations = np.array(saturations).T
154 | #
155 | # Check if we actually inputted saturation values
156 | # for a single grid cell. If yes, we redefine
157 | # saturations to get it on the correct form (no.
158 | # grid cells x phases array).
159 | #
160 | if saturations.ndim == 1:
161 | saturations = \
162 | np.array([[x] for x in saturations]).T
163 | #
164 | # Loop over all grid cells and calculate the
165 | # various saturated properties
166 | #
167 | self.phases = phases
168 |
169 | self.dens = np.zeros(len(saturations[:, 0]))
170 | self.bulkmod = np.zeros(len(saturations[:, 0]))
171 | self.shearmod = np.zeros(len(saturations[:, 0]))
172 | self.bulkvel = np.zeros(len(saturations[:, 0]))
173 | self.shearvel = np.zeros(len(saturations[:, 0]))
174 | self.bulkimp = np.zeros(len(saturations[:, 0]))
175 | self.shearimp = np.zeros(len(saturations[:, 0]))
176 |
177 | if ntg is None:
178 | ntg = [None for _ in range(len(saturations[:, 0]))]
179 | if Rs is None:
180 | Rs = [None for _ in range(len(saturations[:, 0]))]
181 | if p_init is None:
182 | p_init = [None for _ in range(len(saturations[:, 0]))]
183 |
184 |
185 | if dens is not None:
186 | assert (len(dens) == len(phases))
187 | # Transpose makes it a no. grid cells x phases array
188 | dens = np.array(dens).T
189 |
190 | #
191 | denss, bulks, shears = self._solidprops_Johansen()
192 |
193 | for i in range(len(saturations[:, 0])):
194 | #
195 | # Calculate fluid properties
196 | #
197 | if dens is None:
198 | densf_SI = self._fluid_densSIprop(self.phases,
199 | saturations[i, :], pressure[i])
200 | bulkf_Brie = self._fluidprops_Brie(self.phases, saturations[i, :], pressure[i], densf_SI)
201 | densf, bulkf = \
202 | self._fluidprops_Wood(self.phases,
203 | saturations[i, :], pressure[i], Rs[i])
204 | else:
205 | densf = self._fluid_dens(saturations[i, :], dens[i, :])
206 |
207 | bulkf = self._fluidprops_Brie(self.phases, saturations[i, :], pressure[i], densf)
208 | #
209 | #denss, bulks, shears = \
210 | # self._solidprops(porosity[i], ntg[i], i)
211 |
212 | #
213 | # Calculate dry rock moduli
214 | #
215 |
216 | #bulkd, sheard = \
217 | # self._dryrockmoduli(porosity[i],
218 | # overburden[i],
219 | # pressure[i], bulks,
220 | # shears, i, ntg[i], p_init[i], denss, Rs[i], self.phases)
221 | #
222 | peff = self._effective_pressure(poverburden[i], pressure[i])
223 |
224 |
225 | bulkd, sheard = \
226 | self._dryrockmoduli_Smeaheia(coordnumber, phicritical, porosity[i], peff, bulks, shears)
227 |
228 | # -------------------------------
229 | # Calculate saturated properties
230 | # -------------------------------
231 | #
232 | # Density (kg/m3)
233 | #
234 | self.dens[i] = (porosity[i]*densf +
235 | (1-porosity[i])*denss)
236 | #
237 | # Moduli (MPa)
238 | #
239 | self.bulkmod[i] = \
240 | bulkd + (1 - bulkd/bulks)**2 / \
241 | (porosity[i]/bulkf +
242 | (1-porosity[i])/bulks -
243 | bulkd/(bulks**2))
244 | self.shearmod[i] = sheard
245 | #
246 | # Velocities (km/s)
247 | #
248 | self.bulkvel[i] = \
249 | np.sqrt((abs(self.bulkmod[i]) +
250 | 4*self.shearmod[i]/3)/(self.dens[i]))
251 | self.shearvel[i] = \
252 | np.sqrt(self.shearmod[i] /
253 | (self.dens[i]))
254 | #
255 | # convert from (km/s) to (m/s)
256 | #
257 | self.bulkvel[i] *= 1000
258 | self.shearvel[i] *= 1000
259 | #
260 | # Impedance (m/s)*(kg/m3)
261 | #
262 | self.bulkimp[i] = self.dens[i] * \
263 | self.bulkvel[i]
264 | self.shearimp[i] = self.dens[i] * \
265 | self.shearvel[i]
266 |
267 |
268 |
269 | def getMatchProp(self, petElProp):
270 | if petElProp.lower() == 'density':
271 | self.match_prop = self.getDens()
272 | elif petElProp.lower() == 'bulk_modulus':
273 | self.match_prop = self.getBulkMod()
274 | elif petElProp.lower() == 'shear_modulus':
275 | self.match_prop = self.getShearMod()
276 | elif petElProp.lower() == 'bulk_velocity':
277 | self.match_prop = self.getBulkVel()
278 | elif petElProp.lower() == 'shear_velocity':
279 | self.match_prop = self.getShearVel()
280 | elif petElProp.lower() == "bulk_impedance":
281 | self.match_prop = self.getBulkImp()
282 | elif petElProp.lower() == 'shear_impedance':
283 | self.match_prop = self.getShearImp()
284 | else:
285 | print("\nError in getMatchProp method")
286 | print("No model output type selected for "
287 | "data match.")
288 | print("Legal model output types are "
289 | "(case insensitive):")
290 | print("Density, bulk modulus, shear "
291 | "modulus, bulk velocity,")
292 | print("shear velocity, bulk impedance, "
293 | "shear impedance")
294 | sys.exit(1)
295 | return self.match_prop
296 |
297 | def getDens(self):
298 | return self.dens
299 |
300 | def getBulkMod(self):
301 | return self.bulkmod
302 |
303 | def getShearMod(self):
304 | return self.shearmod
305 |
306 | def getBulkVel(self):
307 | return self.bulkvel
308 |
309 | def getShearVel(self):
310 | return self.shearvel
311 |
312 | def getBulkImp(self):
313 | return self.bulkimp
314 |
315 | def getShearImp(self):
316 | return self.shearimp
317 |
318 | def getOverburdenP(self):
319 | return self.overburden
320 |
321 | def getPressure(self):
322 | return self.pressure
323 |
324 | def getPeff(self):
325 | return self.peff
326 |
327 | def getPorosity(self):
328 | return self.porosity
329 | #
330 | # ===================================================
331 | # Fluid properties start
332 | # ===================================================
333 | #
334 | def _fluid_densSIprop(self, phases, fsats, press, t= 37, CO2 = None):
335 |
336 | conv2Pa = 1e6 # MPa to Pa
337 | ta = t + 273.15 # absolute temp in K
338 | # fluid densities
339 | fdens = 0.0
340 |
341 | for i in range(len(phases)):
342 | #
343 | # Calculate mixture properties by summing
344 | # over individual phase properties
345 | #
346 |
347 | var = phases[i]
348 | if var == 'GAS' and CO2 is None:
349 | pdens = PropsSI('D', 'T', ta, 'P', press * conv2Pa, 'Methane')
350 | elif var == 'GAS' and CO2 is True:
351 | pdens = PropsSI('D', 'T', ta, 'P', press * conv2Pa, 'CO2')
352 | elif var == 'OIL':
353 | CP.get_global_param_string('predefined_mixtures').split(',')[0:6]
354 | #pdens = CP.PropsSI('D', 'T', ta, 'P', press * conv2Pa, 'Ekofisk.mix')
355 | pdens = CP.PropsSI('D', 'T', ta, 'P', press * conv2Pa, 'butane')
356 | elif var == 'WAT':
357 | pdens = PropsSI('D', 'T|liquid', ta, 'P', press * conv2Pa, 'Water')
358 |
359 | fdens = fdens + fsats[i] * abs(pdens)
360 |
361 | return fdens
362 |
363 | def _fluidprops_Wood(self, fphases, fsats, fpress, Rs=None):
364 | #
365 | # Calculate fluid density and bulk modulus
366 | #
367 | #
368 | # Input
369 | # fphases - fluid phases present; Oil
370 | # and/or Water and/or Gas
371 | # fsats - fluid saturation values for
372 | # fluid phases in "fphases"
373 | # fpress - fluid pressure value (MPa)
374 | # Rs - Gas oil ratio. Default value None
375 |
376 | #
377 | # Output
378 | # fdens - density of fluid mixture for
379 | # pressure value "fpress" inherited
380 | # from phaseprops)
381 | # fbulk - bulk modulus of fluid mixture for
382 | # pressure value "fpress" (unit
383 | # inherited from phaseprops)
384 | #
385 | # -----------------------------------------------
386 | #
387 | fdens = 0.0
388 | fbinv = 0.0
389 |
390 | for i in range(len(fphases)):
391 | #
392 | # Calculate mixture properties by summing
393 | # over individual phase properties
394 | #
395 | pdens, pbulk = self._phaseprops(fphases[i],
396 | fpress, Rs)
397 | fdens = fdens + fsats[i]*abs(pdens)
398 | fbinv = fbinv + fsats[i]/abs(pbulk)
399 | fbulk = 1.0/fbinv
400 | #
401 | return fdens, fbulk
402 | #
403 | # ---------------------------------------------------
404 | #
405 |
406 | def _fluid_dens(self, fsatsp, fdensp):
407 | fdens = sum(fsatsp * fdensp)
408 | return fdens
409 |
410 | def _fluidprops_Brie(self, fphases, fsats, fpress, fdens, Rs=None, e = 5):
411 | #
412 | # Calculate fluid density and bulk modulus BRIE et al. 1995
413 | # Assumes two phases liquid and gas
414 | #
415 | # Input
416 | # fphases - fluid phases present; Oil
417 | # and/or Water and/or Gas
418 | # fsats - fluid saturation values for
419 | # fluid phases in "fphases"
420 | # fdens - fluid density for given pressure and temperature
421 | # fpress - fluid pressure value (MPa)
422 | # Rs - Gas oil ratio. Default value None
423 | # e - Brie's exponent (e= 5 Utsira sand filled with brine and CO2
424 | # Figure 7 in Carcione et al. 2006 "Physics and Seismic Modeling
425 | # for Monitoring CO 2 Storage"
426 |
427 | #
428 | # Output
429 | # fbulk - bulk modulus of fluid mixture for
430 | # pressure value "fpress" (unit
431 | # inherited from phaseprops)
432 | #
433 | # -----------------------------------------------
434 | #
435 |
436 |
437 | for i in range(len(fphases)):
438 | #
439 | if fphases[i].lower() in ["oil", "wat"]:
440 | fsatsl = fsats[i]
441 | pbulkl = self._phaseprops_Smeaheia(fphases[i], fpress, fdens, Rs)
442 | elif fphases[i].lower() in ["gas"]:
443 | pbulkg = self._phaseprops_Smeaheia(fphases[i], fpress, fdens, Rs)
444 |
445 |
446 | fbulk = (pbulkl - pbulkg) * (fsatsl)**e + pbulkg
447 |
448 | #
449 | return fbulk
450 | #
451 | # ---------------------------------------------------
452 | #
453 | @staticmethod
454 | def pseudo_p_t(pres, t, gs):
455 | """Calculate the pseudoreduced temperature and pressure according to Thomas et al. 1970.
456 |
457 | Parameters
458 | ----------
459 | pres : float or array-like
460 | Pressure in MPa
461 | t : float or array-like
462 | Temperature in °C
463 | gs : float
464 | Gas gravity
465 |
466 | Returns
467 | -------
468 | float or array-like
469 | Ta: absolute temperature
470 | Ppr:pseudoreduced pressure
471 | Tpr:pseudoreduced temperature
472 | """
473 |
474 | # convert the temperature to absolute temperature
475 | ta = t + 273.15
476 | p_pr = pres / (4.892 - 0.4048 * gs)
477 | t_pr = ta / (94.72 + 170.75 * gs)
478 | return ta, p_pr, t_pr
479 | #
480 | # ---------------------------------------------------
481 | #
482 | @staticmethod
483 | def dz_dp(p_pr, t_pr):
484 | """Values for dZ/dPpr obtained from equation 10b in Batzle and Wang (1992).
485 | """
486 | # analytic
487 | dz_dp = (0.03 + 0.00527 * (3.5 - t_pr) ** 3) + 0.109 * (3.85 - t_pr) ** 2 * 1.2 * p_pr ** 0.2 * -(
488 | 0.45 + 8 * (0.56 - 1 / t_pr) ** 2) / t_pr * np.exp(
489 | -(0.45 + 8 * (0.56 - 1 / t_pr) ** 2) * p_pr ** 1.2 / t_pr)
490 |
491 | # numerical approximation
492 | # dzdp= 1.938783*P_pr**0.2*(1 - 0.25974025974026*T_pr)**2*(-8*(0.56 - 1/T_pr)**2 - 0.45)*
493 | # np.exp(P_pr**1.2*(-8*(0.56 - 1/T_pr)**2 - 0.45)/T_pr)/T_pr + 0.22595125*(1 - 0.285714285714286*T_pr)**3
494 | # + 0.03
495 | return dz_dp
496 | #
497 | #-----------------------------------------------------------
498 | #
499 | def _phaseprops_Smeaheia(self, fphase, press, fdens, Rs=None, t = 37, CO2 = True):
500 | #
501 | # Calculate properties for a single fluid phase
502 | #
503 | #
504 | # Input
505 | # fphase - fluid phase; Oil, Water or Gas
506 | # press - fluid pressure value (MPa)
507 | # fdens - fluid density (kg/m3)
508 | # t - temperature in degrees C
509 | #
510 | # Output
511 | # pbulk - bulk modulus of fluid phase
512 | # "fphase" for pressure value
513 | # "press" (MPa)
514 | #
515 | # -----------------------------------------------
516 | # References
517 | # ----------
518 | # Xu, H. (2006). Calculation of CO2 acoustic properties using Batzle-Wang equations. Geophysics, 71(2), F21-F23.
519 | # """
520 |
521 | if fphase.lower() == "wat": # refers to pure water or brine
522 | #Compute the bulk modulus of pure water as a function of temperature and pressure
523 | #using Batzle and Wang (1992).
524 | if np.any(press > 100):
525 | print('pressures above about 100 MPa-> inaccurate estimations of water velocity')
526 | w = np.array([[1.40285e+03, 1.52400e+00, 3.43700e-03, -1.19700e-05],
527 | [4.87100e+00, -1.11000e-02, 1.73900e-04, -1.62800e-06],
528 | [-4.78300e-02, 2.74700e-04, -2.13500e-06, 1.23700e-08],
529 | [1.48700e-04, -6.50300e-07, -1.45500e-08, 1.32700e-10],
530 | [-2.19700e-07, 7.98700e-10, 5.23000e-11, -4.61400e-13]])
531 | v_w = sum(w[i, j] * t ** i * press ** j for i in range(5) for j in range(4)) # m/s
532 | K_w = fdens * v_w ** 2 * 1e-6
533 | if CO2 is True: # refers to brine
534 | salinity = 35000 / 1000000
535 | s1 = 1170 - 9.6 * t + 0.055 * t ** 2 - 8.5e-5 * t ** 3 + 2.6 * press - 0.0029 * t * press - 0.0476 * press ** 2
536 | s15 = 780 - 10 * press + 0.16 * press ** 2
537 | s2 = -820
538 | v_b = v_w + s1 * salinity + s15 * salinity ** 1.5 + s2 * salinity ** 2
539 | x = 300 * press - 2400 * press * salinity + t * (80 + 3 * t - 3300 * salinity - 13 * press + 47 * press * salinity)
540 | rho_b = fdens + salinity * (0.668 + 0.44 * salinity + 1e-6 * x)
541 | pbulk = rho_b * v_b ** 2 * 1e-6
542 | else:
543 | pbulk = K_w
544 |
545 | elif fphase.lower() == "gas" and CO2 is True: # refers to CO2
546 | R = 8.3145 # J.mol-1K-1 gas constant for CO2
547 | gs = 1.5189 # Specific gravity #https://www.engineeringtoolbox.com/specific-gravities-gases-d_334.html
548 | ta, p_pr, t_pr = self.pseudo_p_t(press, t, gs)
549 |
550 | E = 0.109 * (3.85 - t_pr) ** 2 * np.exp(-(0.45 + 8 * (0.56 - 1 / t_pr) ** 2) * p_pr ** 1.2 / t_pr)
551 | Z = (0.03 + 0.00527 * (3.5 - t_pr) ** 3) * p_pr + (0.642 * t_pr - 0.007 * t_pr ** 4 - 0.52) + E
552 | rho = 28.8 * gs * press / (Z * R * ta) # g/cm3
553 |
554 | r_0 = 0.85 + 5.6 / (p_pr + 2) + 27.1 / (p_pr + 3.5) ** 2 - 8.7 * np.exp(-0.65 * (p_pr + 1))
555 | dz_dp = self.dz_dp(p_pr, t_pr)
556 | pbulk = press / (1 - p_pr * dz_dp / Z) * r_0
557 |
558 | #pbulk_test = self.test_new_implementation(press)
559 | #print(np.max(pbulk-pbulk_test))
560 |
561 | elif fphase.lower() == "gas": # refers to Methane
562 | gs = 0.5537 #https://www.engineeringtoolbox.com/specific-gravities-gases-d_334.html
563 | R = 8.3145 # J.mol-1K-1 gas constant
564 | ta, p_pr, t_pr = self.pseudo_p_t(press, t, gs)
565 | E = 0.109 * (3.85 - t_pr) ** 2 * np.exp(-(0.45 + 8 * (0.56 - 1 / t_pr) ** 2) * p_pr ** 1.2 / t_pr)
566 | Z = (0.03 + 0.00527 * (3.5 - t_pr) ** 3) * p_pr + (0.642 * t_pr - 0.007 * t_pr ** 4 - 0.52) + E
567 | rho = 28.8 * gs * press / (Z * R * ta) # g/cm3
568 |
569 | r_0 = 0.85 + 5.6 / (p_pr + 2) + 27.1 / (p_pr + 3.5) ** 2 - 8.7 * np.exp(-0.65 * (p_pr + 1))
570 | dz_dp = self.dz_dp(p_pr, t_pr)
571 | pbulk = press / (1 - p_pr * dz_dp / Z) * r_0
572 |
573 | elif fphase.lower() == "oil": #pure oil
574 | # Estimate the oil bulk modulus at specific temperature and pressure.
575 | v = 2096 * (fdens / (2600 - fdens)) ** 0.5 - 3.7 * t + 4.64 * press + 0.0115 * (
576 | 4.12 * (1080 / fdens - 1) ** 0.5 - 1) * t * press
577 | pbulk = fdens * v ** 2
578 |
579 |
580 | #
581 | return pbulk
582 |
583 | #
584 | def test_new_implementation(self, press):
585 | # Values from .DATA file for Smeaheia (converted to MPa)
586 | press_range = np.array(
587 | [0.101, 0.885, 1.669, 2.453, 3.238, 4.022, 4.806, 5.590, 6.2098, 7.0899, 7.6765, 8.2630, 8.8495, 9.4359,
588 | 10.0222, 10.6084, 11.1945, 14.7087, 17.6334, 20.856, 23.4695, 27.5419]) # Example pressures in MPa
589 | Bo_values = np.array(
590 | [1.07365, 0.11758, 0.05962, 0.03863, 0.02773, 0.02100, 0.01639, 0.01298, 0.010286, 0.007578, 0.005521,
591 | 0.003314, 0.003034, 0.002919, 0.002851, 0.002802, 0.002766, 0.002648, 0.002599, 0.002566, 0.002546,
592 | 0.002525]) # Example formation volume factors in m^3/kg
593 |
594 | # Calculate numerical derivative of Bo with respect to Pressure
595 | dBo_dP = - np.gradient(Bo_values, press_range)
596 | # Calculate isothermal compressibility (van der Waals)
597 | compressibility = (1 / Bo_values) * dBo_dP # Resulting array of compressibility values
598 | bulk_mod = 1 / compressibility
599 |
600 | # Find the index of the closest pressure value in b
601 | closest_index = (np.abs(press_range - press)).argmin()
602 |
603 | # Extract the corresponding value from a
604 | pbulk_test = bulk_mod[closest_index]
605 | return pbulk_test
606 |
607 | def _phaseprops(self, fphase, press, Rs=None):
608 | #
609 | # Calculate properties for a single fluid phase
610 | #
611 | #
612 | # Input
613 | # fphase - fluid phase; Oil, Water or Gas
614 | # press - fluid pressure value (MPa)
615 | #
616 | # Output
617 | # pdens - phase density of fluid phase
618 | # "fphase" for pressure value
619 | # "press" (kg/m³)
620 | # pbulk - bulk modulus of fluid phase
621 | # "fphase" for pressure value
622 | # "press" (MPa)
623 | #
624 | # -----------------------------------------------
625 | #
626 | if fphase.lower() == "oil":
627 | coeffsrho = np.array([0.8, 829.9])
628 | coeffsbulk = np.array([10.42, 995.79])
629 | elif fphase.lower() == "wat":
630 | coeffsrho = np.array([0.3, 1067.3])
631 | coeffsbulk = np.array([9.0, 2807.6])
632 | elif fphase.lower() == "gas":
633 | coeffsrho = np.array([4.7, 13.4])
634 | coeffsbulk = np.array([2.75, 0.0])
635 | else:
636 | print("\nError in phaseprops method")
637 | print("Illegal fluid phase name.")
638 | print("Legal fluid phase names are (case "
639 | "insensitive): Oil, Wat, and Gas.")
640 | sys.exit(1)
641 | #
642 | # Assume simple linear pressure dependencies.
643 | # Coefficients are inferred from
644 | # plots in Batzle and Wang, Geophysics, 1992,
645 | # (where I set the temperature to be 100 degrees
646 | # Celsius, Note also that they give densities in
647 | # g/cc). The resulting straight lines do not fit
648 | # the data extremely well, but they should
649 | # be sufficiently accurate for the purpose of
650 | # this project.
651 | #
652 | pdens = coeffsrho[0]*press + coeffsrho[1]
653 | pbulk = coeffsbulk[0]*press + coeffsbulk[1]
654 | #
655 | return pdens, pbulk
656 |
657 | #
658 | # =======================
659 | # Fluid properties end
660 | # =======================
661 | #
662 |
663 | #
664 | # =========================
665 | # Solid properties start
666 | # =========================
667 | #
668 | def _solidprops_Johansen(self):
669 | #
670 | # Calculate bulk and shear solid rock (mineral)
671 | # moduli by averaging Hashin-Shtrikman bounds
672 | #
673 | #
674 | # Input
675 | # poro -porosity
676 | #
677 | # Output
678 | # denss - solid rock density (kg/m³)
679 | # bulks - solid rock bulk modulus (unit MPa)
680 | # shears - solid rock shear modulus (unit MPa)
681 | #
682 | # -----------------------------------------------
683 | #
684 | #
685 | # Solid rock (mineral) density. (Note
686 | # that this is often termed \rho_dry, and not
687 | # \rho_s)
688 |
689 | denss = 2650 # Density of mineral/solid rock kg/m3
690 |
691 | #
692 | bulks = 37 # (GPa)
693 | shears = 44 # (GPa)
694 | bulks *= 1000 # Convert from GPa to MPa
695 | shears *= 1000
696 | #
697 | return denss, bulks, shears
698 | #
699 | #
700 | # =======================
701 | # Solid properties end
702 | # =======================
703 | #
704 | def _coordination_number(self):
705 | # Applies for granular media
706 | # Average number of contacts that each grain has with surrounding grains
707 | # Coordnumber = 6; simple cubic packing
708 | # Coordnumber = 12; hexagonal close packing
709 | # Needed for Hertz-Mindlin model
710 | # Smeaheia number (Tuhin)
711 | coordnumber = 9
712 |
713 | return coordnumber
714 | #
715 | def _critical_porosity(self):
716 | # For most porous media there exists a critical porosity
717 | # phi_critical, that seperates their mechanical and acoustic behaviour into two domains.
718 | # For porosities below phi_critical the mineral grains are oad bearing, for values above the grains are
719 | # suspended in the fluids which are load-bearing
720 | # Needed for Hertz-Mindlin model
721 | # Smeaheia number (Tuhin)
722 | phicritical = 0.36
723 |
724 | return phicritical
725 | #
726 | def _effective_pressure(self, poverb, pfluid):
727 |
728 | # Input
729 | # poverb - overburden pressure (MPa)
730 | # pfluid - fluid pressure (MPa)
731 |
732 | peff = poverb - pfluid
733 |
734 | if peff < 0:
735 | print("\nError in _hertzmindlin method")
736 | print("Negative effective pressure (" + str(peff) +
737 | "). Setting effective pressure to 0.01")
738 | peff = 0.01
739 |
740 |
741 |
742 | return peff
743 |
744 | # ============================
745 | # Dry rock properties start
746 | # ============================
747 | #
748 | def _dryrockmoduli_Smeaheia(self, coordnumber, phicritical, poro, peff, bulks, shears):
749 | #
750 | #
751 | # Calculate bulk and shear dry rock moduli,
752 |
753 | #
754 | # Input
755 | # poro - porosity
756 | # peff - effective pressure overburden - fluid pressure (MPa)
757 | # bulks - bulk solid (mineral) rock bulk
758 | # modulus (MPa)
759 | # shears - solid rock (mineral) shear
760 | # modulus (MPa)
761 | #
762 | # Output
763 | # bulkd - dry rock bulk modulus (unit
764 | # inherited from hertzmindlin and
765 | # variable; bulks)
766 | # sheard - dry rock shear modulus (unit
767 | # inherited from hertzmindlin and
768 | # variable; shears)
769 | #
770 | # -----------------------------------------------
771 | #
772 | # Calculate Hertz-Mindlin moduli
773 | #
774 | bulkhm, shearhm = self._hertzmindlin_Mavko(peff, bulks, shears, coordnumber, phicritical)
775 | #
776 | bulkd = 1 / ((poro / phicritical) / (bulkhm + 4 / 3 * shearhm) +
777 | (1 - poro / phicritical) / (bulks + 4 / 3 * shearhm)) - 4 / 3 * shearhm
778 |
779 | psi = (9 * bulkhm + 8 * shearhm) / (bulkhm + 2 * shearhm)
780 |
781 | sheard = 1 / ((poro / phicritical) / (shearhm + 1 / 6 * psi * shearhm) +
782 | (1 - poro / phicritical) / (shears + 1 / 6 * psi * shearhm)) - 1 / 6 * psi * shearhm
783 |
784 | #return K_dry, G_dry
785 | return bulkd, sheard
786 |
787 |
788 | #
789 | # ---------------------------------------------------
790 | #
791 |
792 | def _hertzmindlin_Mavko(self, peff, bulks, shears, coordnumber, phicritical):
793 | #
794 | # Calculate bulk and shear Hertz-Mindlin moduli
795 | # adapted from Tuhins kode and "The rock physics handbook", pp247
796 | #
797 | #
798 | # Input
799 | # p_eff - effective pressure
800 | # bulks - bulk solid (mineral) rock bulk
801 | # modulus (MPa)
802 | # shears - solid rock (mineral) shear
803 | # modulus (MPa)
804 | # coordnumber - average number of contacts that each grain has with surrounding grains
805 | # phicritical - critical porosity
806 | #
807 | # Output
808 | # bulkhm - Hertz-Mindlin bulk modulus
809 | # (MPa)
810 | # shearhm - Hertz-Mindlin shear modulus
811 | # (MPa)
812 | #
813 | # -----------------------------------------------
814 | #
815 |
816 |
817 | poisson = (3 * bulks - 2 * shears) / (6 * bulks + 2 * shears)
818 |
819 | bulkhm = ((coordnumber ** 2 * (1 - phicritical) ** 2 * shears ** 2 * peff) /
820 | (18 * np.pi ** 2 * (1 - poisson) ** 2)) ** (1 / 3)
821 | shearhm = (5 - 4 * poisson) / (10 - 5 * poisson) * \
822 | ((3 * coordnumber ** 2 * (1 - phicritical) ** 2 * shears ** 2 * peff) /
823 | (2 * np.pi ** 2 * (1 - poisson) ** 2)) ** (1 / 3)
824 |
825 |
826 |
827 | #
828 | return bulkhm, shearhm
829 |
830 |
831 | # ===========================
832 | # Dry rock properties end
833 | # ===========================
834 |
835 |
836 | if __name__ == '__main__':
837 | #
838 | # Example input with two phases and three grid cells
839 | #
840 | porosity = [0.34999999, 0.34999999, 0.34999999]
841 | # pressure = [ 29.29150963, 29.14003944, 28.88845444]
842 | pressure = [29.3558, 29.2625, 29.3558]
843 | # pressure = [ 25.0, 25.0, 25.0]
844 | phases = ["Oil", "Wat"]
845 | # saturations = [[0.72783828, 0.66568458, 0.58033288],
846 | # [0.27216172, 0.33431542, 0.41966712]]
847 | saturations = [[0.6358, 0.5755, 0.6358],
848 | [0.3641, 0.4245, 0.3641]]
849 | # saturations = [[0.4, 0.5, 0.6],
850 | # [0.6, 0.5, 0.4]]
851 | petElProp = "bulk velocity"
852 | input_dict = {}
853 | input_dict['overburden'] = 'overb.npz'
854 |
855 | print("\nInput:")
856 | print("porosity, pressure:", porosity, pressure)
857 | print("phases, saturations:", phases, saturations)
858 | print("petElProp:", petElProp)
859 | print("input_dict:", input_dict)
860 |
861 | satrock = elasticproperties(input_dict)
862 |
863 | print("overburden:", satrock.overburden)
864 |
865 | satrock.calc_props(phases, saturations, pressure,
866 | porosity)
867 |
868 | print("\nOutput from calc_props:")
869 | print("Density:", satrock.getDens())
870 | print("Bulk modulus:", satrock.getBulkMod())
871 | print("Shear modulus:", satrock.getShearMod())
872 | print("Bulk velocity:", satrock.getBulkVel())
873 | print("Shear velocity:", satrock.getShearVel())
874 | print("Bulk impedance:", satrock.getBulkImp())
875 | print("Shear impedance:", satrock.getShearImp())
876 |
877 | satrock.getMatchProp(petElProp)
878 |
879 | print("\nOutput from getMatchProp:")
880 | print("Model output selected for data match:",
881 | satrock.match_prop)
882 |
--------------------------------------------------------------------------------
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281 | may be on a different server (operated by you or a third party)
282 | that supports equivalent copying facilities, provided you maintain
283 | clear directions next to the object code saying where to find the
284 | Corresponding Source. Regardless of what server hosts the
285 | Corresponding Source, you remain obligated to ensure that it is
286 | available for as long as needed to satisfy these requirements.
287 |
288 | e) Convey the object code using peer-to-peer transmission, provided
289 | you inform other peers where the object code and Corresponding
290 | Source of the work are being offered to the general public at no
291 | charge under subsection 6d.
292 |
293 | A separable portion of the object code, whose source code is excluded
294 | from the Corresponding Source as a System Library, need not be
295 | included in conveying the object code work.
296 |
297 | A "User Product" is either (1) a "consumer product", which means any
298 | tangible personal property which is normally used for personal, family,
299 | or household purposes, or (2) anything designed or sold for incorporation
300 | into a dwelling. In determining whether a product is a consumer product,
301 | doubtful cases shall be resolved in favor of coverage. For a particular
302 | product received by a particular user, "normally used" refers to a
303 | typical or common use of that class of product, regardless of the status
304 | of the particular user or of the way in which the particular user
305 | actually uses, or expects or is expected to use, the product. A product
306 | is a consumer product regardless of whether the product has substantial
307 | commercial, industrial or non-consumer uses, unless such uses represent
308 | the only significant mode of use of the product.
309 |
310 | "Installation Information" for a User Product means any methods,
311 | procedures, authorization keys, or other information required to install
312 | and execute modified versions of a covered work in that User Product from
313 | a modified version of its Corresponding Source. The information must
314 | suffice to ensure that the continued functioning of the modified object
315 | code is in no case prevented or interfered with solely because
316 | modification has been made.
317 |
318 | If you convey an object code work under this section in, or with, or
319 | specifically for use in, a User Product, and the conveying occurs as
320 | part of a transaction in which the right of possession and use of the
321 | User Product is transferred to the recipient in perpetuity or for a
322 | fixed term (regardless of how the transaction is characterized), the
323 | Corresponding Source conveyed under this section must be accompanied
324 | by the Installation Information. But this requirement does not apply
325 | if neither you nor any third party retains the ability to install
326 | modified object code on the User Product (for example, the work has
327 | been installed in ROM).
328 |
329 | The requirement to provide Installation Information does not include a
330 | requirement to continue to provide support service, warranty, or updates
331 | for a work that has been modified or installed by the recipient, or for
332 | the User Product in which it has been modified or installed. Access to a
333 | network may be denied when the modification itself materially and
334 | adversely affects the operation of the network or violates the rules and
335 | protocols for communication across the network.
336 |
337 | Corresponding Source conveyed, and Installation Information provided,
338 | in accord with this section must be in a format that is publicly
339 | documented (and with an implementation available to the public in
340 | source code form), and must require no special password or key for
341 | unpacking, reading or copying.
342 |
343 | 7. Additional Terms.
344 |
345 | "Additional permissions" are terms that supplement the terms of this
346 | License by making exceptions from one or more of its conditions.
347 | Additional permissions that are applicable to the entire Program shall
348 | be treated as though they were included in this License, to the extent
349 | that they are valid under applicable law. If additional permissions
350 | apply only to part of the Program, that part may be used separately
351 | under those permissions, but the entire Program remains governed by
352 | this License without regard to the additional permissions.
353 |
354 | When you convey a copy of a covered work, you may at your option
355 | remove any additional permissions from that copy, or from any part of
356 | it. (Additional permissions may be written to require their own
357 | removal in certain cases when you modify the work.) You may place
358 | additional permissions on material, added by you to a covered work,
359 | for which you have or can give appropriate copyright permission.
360 |
361 | Notwithstanding any other provision of this License, for material you
362 | add to a covered work, you may (if authorized by the copyright holders of
363 | that material) supplement the terms of this License with terms:
364 |
365 | a) Disclaiming warranty or limiting liability differently from the
366 | terms of sections 15 and 16 of this License; or
367 |
368 | b) Requiring preservation of specified reasonable legal notices or
369 | author attributions in that material or in the Appropriate Legal
370 | Notices displayed by works containing it; or
371 |
372 | c) Prohibiting misrepresentation of the origin of that material, or
373 | requiring that modified versions of such material be marked in
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375 |
376 | d) Limiting the use for publicity purposes of names of licensors or
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378 |
379 | e) Declining to grant rights under trademark law for use of some
380 | trade names, trademarks, or service marks; or
381 |
382 | f) Requiring indemnification of licensors and authors of that
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384 | it) with contractual assumptions of liability to the recipient, for
385 | any liability that these contractual assumptions directly impose on
386 | those licensors and authors.
387 |
388 | All other non-permissive additional terms are considered "further
389 | restrictions" within the meaning of section 10. If the Program as you
390 | received it, or any part of it, contains a notice stating that it is
391 | governed by this License along with a term that is a further
392 | restriction, you may remove that term. If a license document contains
393 | a further restriction but permits relicensing or conveying under this
394 | License, you may add to a covered work material governed by the terms
395 | of that license document, provided that the further restriction does
396 | not survive such relicensing or conveying.
397 |
398 | If you add terms to a covered work in accord with this section, you
399 | must place, in the relevant source files, a statement of the
400 | additional terms that apply to those files, or a notice indicating
401 | where to find the applicable terms.
402 |
403 | Additional terms, permissive or non-permissive, may be stated in the
404 | form of a separately written license, or stated as exceptions;
405 | the above requirements apply either way.
406 |
407 | 8. Termination.
408 |
409 | You may not propagate or modify a covered work except as expressly
410 | provided under this License. Any attempt otherwise to propagate or
411 | modify it is void, and will automatically terminate your rights under
412 | this License (including any patent licenses granted under the third
413 | paragraph of section 11).
414 |
415 | However, if you cease all violation of this License, then your
416 | license from a particular copyright holder is reinstated (a)
417 | provisionally, unless and until the copyright holder explicitly and
418 | finally terminates your license, and (b) permanently, if the copyright
419 | holder fails to notify you of the violation by some reasonable means
420 | prior to 60 days after the cessation.
421 |
422 | Moreover, your license from a particular copyright holder is
423 | reinstated permanently if the copyright holder notifies you of the
424 | violation by some reasonable means, this is the first time you have
425 | received notice of violation of this License (for any work) from that
426 | copyright holder, and you cure the violation prior to 30 days after
427 | your receipt of the notice.
428 |
429 | Termination of your rights under this section does not terminate the
430 | licenses of parties who have received copies or rights from you under
431 | this License. If your rights have been terminated and not permanently
432 | reinstated, you do not qualify to receive new licenses for the same
433 | material under section 10.
434 |
435 | 9. Acceptance Not Required for Having Copies.
436 |
437 | You are not required to accept this License in order to receive or
438 | run a copy of the Program. Ancillary propagation of a covered work
439 | occurring solely as a consequence of using peer-to-peer transmission
440 | to receive a copy likewise does not require acceptance. However,
441 | nothing other than this License grants you permission to propagate or
442 | modify any covered work. These actions infringe copyright if you do
443 | not accept this License. Therefore, by modifying or propagating a
444 | covered work, you indicate your acceptance of this License to do so.
445 |
446 | 10. Automatic Licensing of Downstream Recipients.
447 |
448 | Each time you convey a covered work, the recipient automatically
449 | receives a license from the original licensors, to run, modify and
450 | propagate that work, subject to this License. You are not responsible
451 | for enforcing compliance by third parties with this License.
452 |
453 | An "entity transaction" is a transaction transferring control of an
454 | organization, or substantially all assets of one, or subdividing an
455 | organization, or merging organizations. If propagation of a covered
456 | work results from an entity transaction, each party to that
457 | transaction who receives a copy of the work also receives whatever
458 | licenses to the work the party's predecessor in interest had or could
459 | give under the previous paragraph, plus a right to possession of the
460 | Corresponding Source of the work from the predecessor in interest, if
461 | the predecessor has it or can get it with reasonable efforts.
462 |
463 | You may not impose any further restrictions on the exercise of the
464 | rights granted or affirmed under this License. For example, you may
465 | not impose a license fee, royalty, or other charge for exercise of
466 | rights granted under this License, and you may not initiate litigation
467 | (including a cross-claim or counterclaim in a lawsuit) alleging that
468 | any patent claim is infringed by making, using, selling, offering for
469 | sale, or importing the Program or any portion of it.
470 |
471 | 11. Patents.
472 |
473 | A "contributor" is a copyright holder who authorizes use under this
474 | License of the Program or a work on which the Program is based. The
475 | work thus licensed is called the contributor's "contributor version".
476 |
477 | A contributor's "essential patent claims" are all patent claims
478 | owned or controlled by the contributor, whether already acquired or
479 | hereafter acquired, that would be infringed by some manner, permitted
480 | by this License, of making, using, or selling its contributor version,
481 | but do not include claims that would be infringed only as a
482 | consequence of further modification of the contributor version. For
483 | purposes of this definition, "control" includes the right to grant
484 | patent sublicenses in a manner consistent with the requirements of
485 | this License.
486 |
487 | Each contributor grants you a non-exclusive, worldwide, royalty-free
488 | patent license under the contributor's essential patent claims, to
489 | make, use, sell, offer for sale, import and otherwise run, modify and
490 | propagate the contents of its contributor version.
491 |
492 | In the following three paragraphs, a "patent license" is any express
493 | agreement or commitment, however denominated, not to enforce a patent
494 | (such as an express permission to practice a patent or covenant not to
495 | sue for patent infringement). To "grant" such a patent license to a
496 | party means to make such an agreement or commitment not to enforce a
497 | patent against the party.
498 |
499 | If you convey a covered work, knowingly relying on a patent license,
500 | and the Corresponding Source of the work is not available for anyone
501 | to copy, free of charge and under the terms of this License, through a
502 | publicly available network server or other readily accessible means,
503 | then you must either (1) cause the Corresponding Source to be so
504 | available, or (2) arrange to deprive yourself of the benefit of the
505 | patent license for this particular work, or (3) arrange, in a manner
506 | consistent with the requirements of this License, to extend the patent
507 | license to downstream recipients. "Knowingly relying" means you have
508 | actual knowledge that, but for the patent license, your conveying the
509 | covered work in a country, or your recipient's use of the covered work
510 | in a country, would infringe one or more identifiable patents in that
511 | country that you have reason to believe are valid.
512 |
513 | If, pursuant to or in connection with a single transaction or
514 | arrangement, you convey, or propagate by procuring conveyance of, a
515 | covered work, and grant a patent license to some of the parties
516 | receiving the covered work authorizing them to use, propagate, modify
517 | or convey a specific copy of the covered work, then the patent license
518 | you grant is automatically extended to all recipients of the covered
519 | work and works based on it.
520 |
521 | A patent license is "discriminatory" if it does not include within
522 | the scope of its coverage, prohibits the exercise of, or is
523 | conditioned on the non-exercise of one or more of the rights that are
524 | specifically granted under this License. You may not convey a covered
525 | work if you are a party to an arrangement with a third party that is
526 | in the business of distributing software, under which you make payment
527 | to the third party based on the extent of your activity of conveying
528 | the work, and under which the third party grants, to any of the
529 | parties who would receive the covered work from you, a discriminatory
530 | patent license (a) in connection with copies of the covered work
531 | conveyed by you (or copies made from those copies), or (b) primarily
532 | for and in connection with specific products or compilations that
533 | contain the covered work, unless you entered into that arrangement,
534 | or that patent license was granted, prior to 28 March 2007.
535 |
536 | Nothing in this License shall be construed as excluding or limiting
537 | any implied license or other defenses to infringement that may
538 | otherwise be available to you under applicable patent law.
539 |
540 | 12. No Surrender of Others' Freedom.
541 |
542 | If conditions are imposed on you (whether by court order, agreement or
543 | otherwise) that contradict the conditions of this License, they do not
544 | excuse you from the conditions of this License. If you cannot convey a
545 | covered work so as to satisfy simultaneously your obligations under this
546 | License and any other pertinent obligations, then as a consequence you may
547 | not convey it at all. For example, if you agree to terms that obligate you
548 | to collect a royalty for further conveying from those to whom you convey
549 | the Program, the only way you could satisfy both those terms and this
550 | License would be to refrain entirely from conveying the Program.
551 |
552 | 13. Use with the GNU Affero General Public License.
553 |
554 | Notwithstanding any other provision of this License, you have
555 | permission to link or combine any covered work with a work licensed
556 | under version 3 of the GNU Affero General Public License into a single
557 | combined work, and to convey the resulting work. The terms of this
558 | License will continue to apply to the part which is the covered work,
559 | but the special requirements of the GNU Affero General Public License,
560 | section 13, concerning interaction through a network will apply to the
561 | combination as such.
562 |
563 | 14. Revised Versions of this License.
564 |
565 | The Free Software Foundation may publish revised and/or new versions of
566 | the GNU General Public License from time to time. Such new versions will
567 | be similar in spirit to the present version, but may differ in detail to
568 | address new problems or concerns.
569 |
570 | Each version is given a distinguishing version number. If the
571 | Program specifies that a certain numbered version of the GNU General
572 | Public License "or any later version" applies to it, you have the
573 | option of following the terms and conditions either of that numbered
574 | version or of any later version published by the Free Software
575 | Foundation. If the Program does not specify a version number of the
576 | GNU General Public License, you may choose any version ever published
577 | by the Free Software Foundation.
578 |
579 | If the Program specifies that a proxy can decide which future
580 | versions of the GNU General Public License can be used, that proxy's
581 | public statement of acceptance of a version permanently authorizes you
582 | to choose that version for the Program.
583 |
584 | Later license versions may give you additional or different
585 | permissions. However, no additional obligations are imposed on any
586 | author or copyright holder as a result of your choosing to follow a
587 | later version.
588 |
589 | 15. Disclaimer of Warranty.
590 |
591 | THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
592 | APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
593 | HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
594 | OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
595 | THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
596 | PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
597 | IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
598 | ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
599 |
600 | 16. Limitation of Liability.
601 |
602 | IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
603 | WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
604 | THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
605 | GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
606 | USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
607 | DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
608 | PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
609 | EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
610 | SUCH DAMAGES.
611 |
612 | 17. Interpretation of Sections 15 and 16.
613 |
614 | If the disclaimer of warranty and limitation of liability provided
615 | above cannot be given local legal effect according to their terms,
616 | reviewing courts shall apply local law that most closely approximates
617 | an absolute waiver of all civil liability in connection with the
618 | Program, unless a warranty or assumption of liability accompanies a
619 | copy of the Program in return for a fee.
620 |
621 | END OF TERMS AND CONDITIONS
622 |
623 | How to Apply These Terms to Your New Programs
624 |
625 | If you develop a new program, and you want it to be of the greatest
626 | possible use to the public, the best way to achieve this is to make it
627 | free software which everyone can redistribute and change under these terms.
628 |
629 | To do so, attach the following notices to the program. It is safest
630 | to attach them to the start of each source file to most effectively
631 | state the exclusion of warranty; and each file should have at least
632 | the "copyright" line and a pointer to where the full notice is found.
633 |
634 |
635 | Copyright (C)
636 |
637 | This program is free software: you can redistribute it and/or modify
638 | it under the terms of the GNU General Public License as published by
639 | the Free Software Foundation, either version 3 of the License, or
640 | (at your option) any later version.
641 |
642 | This program is distributed in the hope that it will be useful,
643 | but WITHOUT ANY WARRANTY; without even the implied warranty of
644 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
645 | GNU General Public License for more details.
646 |
647 | You should have received a copy of the GNU General Public License
648 | along with this program. If not, see .
649 |
650 | Also add information on how to contact you by electronic and paper mail.
651 |
652 | If the program does terminal interaction, make it output a short
653 | notice like this when it starts in an interactive mode:
654 |
655 | Copyright (C)
656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
657 | This is free software, and you are welcome to redistribute it
658 | under certain conditions; type `show c' for details.
659 |
660 | The hypothetical commands `show w' and `show c' should show the appropriate
661 | parts of the General Public License. Of course, your program's commands
662 | might be different; for a GUI interface, you would use an "about box".
663 |
664 | You should also get your employer (if you work as a programmer) or school,
665 | if any, to sign a "copyright disclaimer" for the program, if necessary.
666 | For more information on this, and how to apply and follow the GNU GPL, see
667 | .
668 |
669 | The GNU General Public License does not permit incorporating your program
670 | into proprietary programs. If your program is a subroutine library, you
671 | may consider it more useful to permit linking proprietary applications with
672 | the library. If this is what you want to do, use the GNU Lesser General
673 | Public License instead of this License. But first, please read
674 | .
675 |
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