├── 2018.04.30 ├── simulation.py └── simulation.xlsm ├── LICENSE ├── README.md ├── Tutor 2 ├── gridsection.py ├── tutor2.py └── tutor2.xlsm ├── Tutor 3 ├── dynamicsection.py ├── gridsection.py ├── propertysection.py └── tutor3.xlsm ├── material ├── pythonExcel.png ├── tutor1.2019-02-14.gif └── tutor2.gif ├── tutor1.py └── tutor1.xlsm /2018.04.30/simulation.py: -------------------------------------------------------------------------------- 1 | from __future__ import division 2 | import sys 3 | import os 4 | import h5py 5 | import numpy as np 6 | import pandas as pd 7 | import matplotlib.pyplot as plt 8 | import xlwings as xw 9 | 10 | from mpl_toolkits.mplot3d import Axes3D 11 | from matplotlib import cm 12 | from matplotlib.ticker import LinearLocator, FormatStrFormatter 13 | import datetime 14 | import subprocess 15 | 16 | realPath = os.path.dirname(os.path.realpath(__file__)) 17 | hdf5File = realPath+'\\simModel\\simModel.hdf5' 18 | filename = realPath+'\\simModel\\model.dxx' 19 | sht = xw.Book.caller().sheets[0] 20 | gridVaryOpt={ } 21 | defaultDim = 200 22 | kwMap = {'dx':'DX','dy':'DY','dz':'DZ','por':'POROSITY','permx':'KX','permy':'PERMY', 23 | 'permz':'PERMZ'} 24 | class CWell: 25 | wellCount = 0 26 | 27 | def __init__(self, name, hI,hJ): 28 | self.name = name 29 | self.head_I = hI 30 | self.head_J = hJ 31 | CWell.wellCount += 1 32 | self.id = CWell.wellCount 33 | 34 | 35 | def getKeyWordBeginRow(iRow,strKW): 36 | index = 'A' 37 | while (sht.range(index+str(iRow)).value != strKW): 38 | iRow = iRow+1 39 | 40 | return iRow 41 | 42 | def getKeyWordEndRow(irow): 43 | irow = irow+1 44 | index = 'B' 45 | while (sht.range(index+str(irow)).value != None): 46 | irow = irow+1 47 | 48 | return irow-1 49 | 50 | def draw2YCurve(ax,title,xlabel,leftMaps,rightMaps): 51 | lineColor = ['b+-','ro-','gs-','h--'] 52 | lmaxV = 0 53 | lminV = 10000 54 | rmaxV = 0 55 | rminV = 10000 56 | 57 | for lMap in leftMaps: 58 | x = lMap['x'] 59 | y = lMap['y'] 60 | i = lMap['id'] 61 | ax.plot(x,y,lineColor[i],lw=2,label=lMap['ylabel']) 62 | 63 | maxNum = max(y) 64 | minNum = min(y) 65 | if(maxNum>lmaxV): 66 | lmaxV = maxNum 67 | if(minNumrmaxV): 81 | rmaxV = maxNum 82 | if(minNum0): 91 | ax2.legend(loc='upper right') 92 | ax2.set_ylim(rminV,rmaxV) 93 | 94 | def drawCurve(ax,xlabel,curvelegend,x,yArray): 95 | 96 | lineColor = ['b+-','ro-','gs-','h--'] 97 | 98 | for i,y in enumerate(yArray): 99 | ax.plot(x, y, lineColor[i], lw=2, zorder=30) 100 | 101 | ax.grid() 102 | ax.set_xlabel(xlabel, fontweight='bold', fontsize=15) 103 | ax.set_xticklabels([]) 104 | ax.set_yticklabels([]) 105 | 106 | ax.legend(ax.lines, curvelegend, fancybox=True, shadow=True, prop={'size': 15}) 107 | 108 | def readGeneralInfo(): 109 | nx = sht.range('B3').options(numbers=int).value 110 | ny = sht.range('C3').options(numbers=int).value 111 | nz = sht.range('D3').options(numbers=int).value 112 | 113 | gridVaryOpt['xopt'] = sht.range('B4').value 114 | gridVaryOpt['yopt'] = sht.range('C4').value 115 | gridVaryOpt['zopt'] = sht.range('D4').value 116 | 117 | gridVaryOpt['por'] = sht.range('F3').value 118 | gridVaryOpt['kx'] = sht.range('G3').value 119 | gridVaryOpt['ky'] = sht.range('H3').value 120 | gridVaryOpt['kz'] = sht.range('I3').value 121 | 122 | return nx,ny,nz 123 | 124 | nx,ny,nz = readGeneralInfo() 125 | 126 | def createHDF5(nx,ny,nz): 127 | 128 | ni = nx 129 | nj = ny 130 | nk = nz 131 | 132 | fModel = h5py.File(hdf5File, "w") 133 | 134 | staticEntry = fModel.create_group(u"StaticGroup") 135 | staticEntry.attrs[u'nx'] = nx 136 | staticEntry.attrs[u'ny'] = ny 137 | staticEntry.attrs[u'nz'] = nz 138 | 139 | fModel.create_group(u"DynamicGroup") 140 | fModel.create_group(u"PvtGroup") 141 | fModel.create_group(u"InitGroup") 142 | fModel.create_dataset(u'StaticGroup/dx', (nk,nj,ni), dtype='f') 143 | fModel.create_dataset(u'StaticGroup/dy', (nk,nj,ni), dtype='f') 144 | fModel.create_dataset(u'StaticGroup/dz', (nk,nj,ni), dtype='f') 145 | fModel.create_dataset(u'StaticGroup/por', (nk,nj,ni), dtype='f') 146 | fModel.create_dataset(u'StaticGroup/permx', (nk,nj,ni), dtype='f') 147 | fModel.create_dataset(u'StaticGroup/permy', (nk,nj,ni), dtype='f') 148 | fModel.create_dataset(u'StaticGroup/permz', (nk,nj,ni), dtype='f') 149 | fModel.create_dataset(u'StaticGroup/tops', (nj,ni), dtype='f') 150 | 151 | fModel.close() 152 | 153 | def init(): 154 | 155 | sht.range((9,3),(9,defaultDim+3-1)).color = (255,255,255) 156 | sht.range((10,3),(10,defaultDim+3-1)).color = (255,255,255) 157 | sht.range((11,3),(11,defaultDim+3-1)).color = (255,255,255) 158 | sht.range((17,3),(17,defaultDim+3-1)).color = (255,255,255) 159 | sht.range((18,3),(18,defaultDim+3-1)).color = (255,255,255) 160 | sht.range((19,3),(19,defaultDim+3-1)).color = (255,255,255) 161 | sht.range((20,3),(20,defaultDim+3-1)).color = (255,255,255) 162 | 163 | 164 | def defineGrid(): 165 | init() 166 | 167 | createHDF5(nx,ny,nz) 168 | 169 | #prepare gui 170 | if gridVaryOpt['xopt'] == 'CON': 171 | sht.range('A9').value = 'DX' 172 | sht.range('B9').value = 'CON' 173 | sht.range('C9').color = (102,255,102) 174 | elif gridVaryOpt['xopt'] == 'XVAR': 175 | sht.range('A9').value = 'DX' 176 | sht.range('B9').value = 'XVAR' 177 | sht.range((9,3),(9,nx+3-1)).color = (102,255,102) 178 | 179 | if gridVaryOpt['yopt'] == 'CON': 180 | sht.range('A10').value = 'DY' 181 | sht.range('B10').value = 'CON' 182 | sht.range('C10').color = (102,255,102) 183 | elif gridVaryOpt['yopt'] == 'YVAR': 184 | sht.range('A10').value = 'DY' 185 | sht.range('B10').value = 'YVAR' 186 | sht.range((10,3),(10,ny+3-1)).color = (102,255,102) 187 | 188 | if gridVaryOpt['zopt'] == 'CON': 189 | sht.range('A11').value = 'DZ' 190 | sht.range('B11').value = 'CON' 191 | sht.range('C11').color = (102,255,102) 192 | elif gridVaryOpt['zopt'] == 'ZVAR': 193 | sht.range('A11').value = 'DZ' 194 | sht.range('B11').value = 'ZVAR' 195 | sht.range((11,3),(11,nz+3-1)).color = (102,255,102) 196 | 197 | if gridVaryOpt['por'] == 'CON': 198 | sht.range('A17').value = 'POR' 199 | sht.range('B17').value = 'CON' 200 | sht.range('C17').color = (102,255,102) 201 | elif gridVaryOpt['por'] == 'ZVAR': 202 | sht.range('A17').value = 'POR' 203 | sht.range('B17').value = 'ZVAR' 204 | sht.range((17,3),(17,nz+3-1)).color = (102,255,102) 205 | 206 | if gridVaryOpt['kx'] == 'CON': 207 | sht.range('A18').value = 'PERMX' 208 | sht.range('B18').value = 'CON' 209 | sht.range('C18').color = (102,255,102) 210 | elif gridVaryOpt['kx'] == 'ZVAR': 211 | sht.range('A18').value = 'PERMX' 212 | sht.range('B18').value = 'ZVAR' 213 | sht.range((18,3),(18,nz+3-1)).color = (102,255,102) 214 | 215 | if gridVaryOpt['ky'] == 'CON': 216 | sht.range('A19').value = 'PERMY' 217 | sht.range('B19').value = 'CON' 218 | sht.range('C19').color = (102,255,102) 219 | elif gridVaryOpt['ky'] == 'ZVAR': 220 | sht.range('A19').value = 'PERMY' 221 | sht.range('B19').value = 'ZVAR' 222 | sht.range((19,3),(19,nz+3-1)).color = (102,255,102) 223 | 224 | if gridVaryOpt['kz'] == 'CON': 225 | sht.range('A20').value = 'PERMZ' 226 | sht.range('B20').value = 'CON' 227 | sht.range('C20').color = (102,255,102) 228 | elif gridVaryOpt['kz'] == 'ZVAR': 229 | sht.range('A20').value = 'PERMZ' 230 | sht.range('B20').value = 'ZVAR' 231 | sht.range((20,3),(20,nz+3-1)).color = (102,255,102) 232 | 233 | def readGrid(): 234 | 235 | fModel = h5py.File(hdf5File, "a") 236 | dset_dx = fModel['StaticGroup/dx'] 237 | dset_dy = fModel['StaticGroup/dy'] 238 | dset_dz = fModel['StaticGroup/dz'] 239 | dset_por = fModel['StaticGroup/por'] 240 | dset_kx = fModel['StaticGroup/permx'] 241 | dset_ky = fModel['StaticGroup/permy'] 242 | dset_kz = fModel['StaticGroup/permz'] 243 | dset_tops = fModel['StaticGroup/tops'] 244 | 245 | iDxRow = getKeyWordBeginRow(1,'DX') 246 | iDyRow = getKeyWordBeginRow(1,'DY') 247 | iDzRow = getKeyWordBeginRow(1,'DZ') 248 | if gridVaryOpt['xopt'] == 'XVAR' : 249 | dxVar = sht.range((iDxRow,3),(iDxRow,nx+3-1)).options(np.array).value 250 | idArray = np.arange(nx) 251 | for id in idArray: 252 | dset_dx[:,:,id] = dxVar[id] 253 | elif gridVaryOpt['xopt'] == 'CON' : 254 | dset_dx[:,:,:] = sht.range((iDxRow,3)).options(numbers=float).value 255 | 256 | if gridVaryOpt['yopt'] == 'YVAR' : 257 | dyVar = sht.range((iDyRow,3),(iDyRow,ny+3-1)).options(np.array).value 258 | idArray = np.arange(ny) 259 | for id in idArray: 260 | dset_dy[:,id,:] = dyVar[id] 261 | elif gridVaryOpt['yopt'] == 'CON' : 262 | dset_dy[:,:,:] = sht.range((iDyRow,3)).options(numbers=float).value 263 | 264 | if gridVaryOpt['zopt'] == 'ZVAR' : 265 | dzVar = sht.range((iDzRow,3),(iDzRow,nz+3-1)).options(np.array).value 266 | idArray = np.arange(nz) 267 | for id in idArray: 268 | dset_dz[id,:,:] = dzVar[id] 269 | elif gridVaryOpt['zopt'] == 'CON' : 270 | dset_dz[:,:,:] = sht.range((iDzRow,3)).options(numbers=float).value 271 | 272 | itopRow = getKeyWordBeginRow(1,'TOPS') 273 | dset_tops[:,:] = sht.range((itopRow,3)).options(numbers=float).value 274 | 275 | iporRow = getKeyWordBeginRow(1,'POR') 276 | ikxRow = getKeyWordBeginRow(1,'PERMX') 277 | ikyRow = getKeyWordBeginRow(1,'PERMY') 278 | ikzRow = getKeyWordBeginRow(1,'PERMZ') 279 | if gridVaryOpt['por'] == 'ZVAR' : 280 | porVar = sht.range((iporRow,3),(iporRow,nz+3-1)).options(np.array).value 281 | idArray = np.arange(nz) 282 | for id in idArray: 283 | dset_por[id,:,:] = porVar[id] 284 | elif gridVaryOpt['por'] == 'CON' : 285 | dset_por[:,:,:] = sht.range((iporRow,3)).options(numbers=float).value 286 | 287 | if gridVaryOpt['kx'] == 'ZVAR' : 288 | kxVar = sht.range((ikxRow,3),(ikxRow,nz+3-1)).options(np.array).value 289 | idArray = np.arange(nz) 290 | for id in idArray: 291 | dset_kx[id,:,:] = kxVar[id] 292 | elif gridVaryOpt['kx'] == 'CON' : 293 | dset_kx[:,:,:] = sht.range((ikxRow,3)).options(numbers=float).value 294 | 295 | if gridVaryOpt['ky'] == 'ZVAR' : 296 | kyVar = sht.range((ikyRow,3),(ikyRow,nz+3-1)).options(np.array).value 297 | idArray = np.arange(nz) 298 | for id in idArray: 299 | dset_ky[id,:,:] = kyVar[id] 300 | elif gridVaryOpt['ky'] == 'CON' : 301 | dset_ky[:,:,:] = sht.range((ikyRow,3)).options(numbers=float).value 302 | 303 | if gridVaryOpt['kz'] == 'ZVAR' : 304 | kzVar = sht.range((ikzRow,3),(ikzRow,nz+3-1)).options(np.array).value 305 | idArray = np.arange(nz) 306 | for id in idArray: 307 | dset_kz[id,:,:] = kzVar[id] 308 | elif gridVaryOpt['kz'] == 'CON' : 309 | dset_kz[:,:,:] = sht.range((ikzRow,3)).options(numbers=float).value 310 | 311 | fModel.flush() 312 | fModel.close() 313 | 314 | def drawPvtCurve(): 315 | fig = plt.figure('PVT') 316 | 317 | iRowPvtSec= getKeyWordBeginRow(1,'PVT') 318 | 319 | iRowBegin = getKeyWordBeginRow(iRowPvtSec,'OIL-PVT') 320 | iRowEnd = getKeyWordEndRow(iRowBegin) 321 | 322 | df_PVTo = sht.range((iRowBegin,2),(iRowEnd,5)).options(pd.DataFrame,index=False).value 323 | 324 | o_x = df_PVTo['P'] 325 | o_y0 = df_PVTo['MUO'] 326 | o_y1 = df_PVTo['BO'] 327 | o_y2 = df_PVTo['RSO'] 328 | 329 | ax = fig.add_subplot(2,1,1) 330 | 331 | lMap1 = {'x':o_x,'y':o_y0,'id':0,'ylabel':'MUO'} 332 | lMap2 = {'x':o_x,'y':o_y1,'id':1,'ylabel':'BO'} 333 | rMap = {'x':o_x,'y':o_y2,'id':2,'ylabel':'RSO'} 334 | leftMaps = [lMap1,lMap2] 335 | rightMaps = [rMap] 336 | 337 | draw2YCurve(ax,'Oil PVT','P',leftMaps,rightMaps) 338 | 339 | # pvtg 340 | iRowBegin = getKeyWordBeginRow(iRowPvtSec,'GAS-PVT') 341 | iRowEnd = getKeyWordEndRow(iRowBegin) 342 | df_PVTg = sht.range((iRowBegin,2),(iRowEnd,4)).options(pd.DataFrame,index=False).value 343 | 344 | g_x = df_PVTg['P'] 345 | g_y0 = df_PVTg['MUG'] 346 | g_y1 = df_PVTg['BG'] 347 | 348 | ax = fig.add_subplot(2,1,2) 349 | 350 | lMap1 = {'x':g_x,'y':g_y0,'id':0,'ylabel':'MUG'} 351 | lMap2 = {'x':g_x,'y':g_y1,'id':1,'ylabel':'BG'} 352 | leftMaps = [lMap1,lMap2] 353 | rightMaps = [] 354 | 355 | draw2YCurve(ax,'Gas PVT','P',leftMaps,rightMaps) 356 | 357 | plt.show() 358 | 359 | def readPvt(f): 360 | iRowPvtSec= getKeyWordBeginRow(1,'PVT') 361 | 362 | iRowPbo = getKeyWordBeginRow(iRowPvtSec,'PBO') 363 | fPbo = sht.range((iRowPbo,2),(iRowPbo,2)).value 364 | iRowMuo_s = getKeyWordBeginRow(iRowPvtSec,'Viso_SLOPE') 365 | fMuo_s = sht.range((iRowMuo_s,2),(iRowMuo_s,2)).value 366 | iRowBo_s = getKeyWordBeginRow(iRowPvtSec,'Bo_SLOPE') 367 | fBo_s = sht.range((iRowBo_s,2),(iRowBo_s,2)).value 368 | 369 | iRowBegin = getKeyWordBeginRow(iRowPvtSec,'OIL-PVT') 370 | iRowEnd = getKeyWordEndRow(iRowBegin) 371 | 372 | df_PVTo = sht.range((iRowBegin,2),(iRowEnd,5)).options(pd.DataFrame).value 373 | 374 | # df to hdf5 375 | df_to_nparray = df_PVTo.to_records(index=True) 376 | 377 | #pvto_nparray = np.asarray(df_to_nparray) 378 | # create dataset 379 | f['PvtGroup/PVTO'] = df_to_nparray 380 | 381 | # pb 382 | f['PvtGroup'].attrs[u'PB'] = fPbo 383 | f['PvtGroup'].attrs[u'MUO_SLOPE'] = fMuo_s 384 | f['PvtGroup'].attrs[u'BO_SLOPE'] = fBo_s 385 | # pvtw 386 | iRowBegin = getKeyWordBeginRow(iRowPvtSec,'WATER-PVT') 387 | iRowEnd = getKeyWordEndRow(iRowBegin) 388 | df_PVTw = sht.range((iRowBegin,2),(iRowEnd,4)).options(pd.DataFrame).value 389 | df_to_nparray = df_PVTw.to_records(index=True) 390 | f['PvtGroup/PVTW'] = df_to_nparray 391 | 392 | # pvtg 393 | iRowBegin = getKeyWordBeginRow(iRowPvtSec,'GAS-PVT') 394 | iRowEnd = getKeyWordEndRow(iRowBegin) 395 | df_PVTg = sht.range((iRowBegin,2),(iRowEnd,4)).options(pd.DataFrame).value 396 | df_to_nparray = df_PVTg.to_records(index=True) 397 | f['PvtGroup/PVTG'] = df_to_nparray 398 | 399 | # density 400 | iDenRow = getKeyWordBeginRow(iRowPvtSec,u'DENSITY') 401 | df_density = sht.range((iDenRow,2),(iDenRow+1,4)).options(pd.DataFrame).value 402 | df_to_nparray = df_density.to_records(index=True) 403 | f['PvtGroup/DENSITY'] = df_to_nparray 404 | 405 | # rock 406 | iRockRow = getKeyWordBeginRow(iRowPvtSec,u'CROCK') 407 | fRock = sht.range((iRockRow,3),(iRockRow,3)).value 408 | f['PvtGroup'].attrs[u'ROCK'] = fRock 409 | 410 | def drawRelPermCurve(): 411 | fig = plt.figure('Rel. Perm') 412 | #ax = fig.add_subplot(111) 413 | 414 | iRowPvtSec= getKeyWordBeginRow(1,'PVT') 415 | # water-oil 416 | iRowBegin = getKeyWordBeginRow(iRowPvtSec,'WATER-OIL') 417 | iRowEnd = getKeyWordEndRow(iRowBegin) 418 | 419 | df_SWOF = sht.range((iRowBegin,2),(iRowEnd,5)).options(pd.DataFrame,index=False).value 420 | 421 | wo_x = df_SWOF['SAT'] 422 | wo_y0 = df_SWOF['KRW'] 423 | wo_y1 = df_SWOF['KROW'] 424 | 425 | wo_yArray = [wo_y0,wo_y1] 426 | ax = fig.add_subplot(2,1,1) 427 | 428 | drawCurve(ax,'SAT',['KRW','KROW'],wo_x,wo_yArray) 429 | 430 | # GAS-LIQUID 431 | iRowBegin = getKeyWordBeginRow(iRowPvtSec,'GAS-LIQUID') 432 | iRowEnd = getKeyWordEndRow(iRowBegin) 433 | 434 | df_SGLF = sht.range((iRowBegin,2),(iRowEnd,5)).options(pd.DataFrame,index=False).value 435 | 436 | x = df_SGLF['SLIQ'] 437 | y0 = df_SGLF['KRG'] 438 | y1 = df_SGLF['KROG'] 439 | 440 | yArray = [y0,y1] 441 | ax = fig.add_subplot(2,1,2) 442 | 443 | drawCurve(ax,'SLIQ',['KRG','KROG'],x,yArray) 444 | 445 | plt.show() 446 | 447 | 448 | def readRelativePerm(f): 449 | iRowPvtSec= getKeyWordBeginRow(1,'PVT') 450 | # water-oil 451 | iRowBegin = getKeyWordBeginRow(iRowPvtSec,'WATER-OIL') 452 | iRowEnd = getKeyWordEndRow(iRowBegin) 453 | 454 | df_SWOF = sht.range((iRowBegin,2),(iRowEnd,5)).options(pd.DataFrame,index=False).value 455 | #sht.range('G29:J39').options(pd.DataFrame).value = df_PVTo 456 | # df to hdf5 457 | df_to_nparray = df_SWOF.to_records(index=True) 458 | # create dataset 459 | f['PvtGroup/SWOF'] = df_to_nparray 460 | 461 | # GAS-LIQUID 462 | iRowBegin = getKeyWordBeginRow(iRowPvtSec,'GAS-LIQUID') 463 | iRowEnd = getKeyWordEndRow(iRowBegin) 464 | 465 | df_SGLF = sht.range((iRowBegin,2),(iRowEnd,5)).options(pd.DataFrame,index=False).value 466 | #sht.range('G29:J39').options(pd.DataFrame).value = df_PVTo 467 | # df to hdf5 468 | df_to_nparray = df_SGLF.to_records(index=True) 469 | # create dataset 470 | f['PvtGroup/SGLF'] = df_to_nparray 471 | 472 | def readPropSection(): 473 | f = h5py.File(hdf5File,'a') 474 | readPvt(f) 475 | readRelativePerm(f) 476 | 477 | f.close() 478 | 479 | def readInitSection(): 480 | f = h5py.File(hdf5File,'a') 481 | iRowInitSec= getKeyWordBeginRow(1,'INITIAL SECTION') 482 | iRowEquil = getKeyWordBeginRow(iRowInitSec,'EQUIL') 483 | fRefP = sht.range((iRowEquil+1,2),(iRowEquil+1,2)).value 484 | fRefDepth = sht.range((iRowEquil+1,3),(iRowEquil+1,3)).value 485 | fOWC = sht.range((iRowEquil+1,4),(iRowEquil+1,4)).value 486 | fOGC = sht.range((iRowEquil+1,5),(iRowEquil+1,5)).value 487 | 488 | f[u'InitGroup'].attrs[u'RefPress'] = fRefP 489 | f[u'InitGroup'].attrs[u'RefDepth'] = fRefDepth 490 | f[u'InitGroup'].attrs[u'OWC'] = fOWC 491 | f[u'InitGroup'].attrs[u'OGC'] = fOGC 492 | 493 | f.close() 494 | 495 | def drawWells(): 496 | fig = plt.figure('WELL PRODUCTION') 497 | 498 | iRow = getKeyWordBeginRow(1,'SCHEDULE SECTION') 499 | index = 'A' 500 | wells = {} 501 | while (sht.range(index+str(iRow)).value!='END'): 502 | iRow = iRow+1 503 | kw = sht.range(index+str(iRow)).value 504 | if(kw==u'General Info'): 505 | iwellDefRow = getKeyWordBeginRow(iRow,u'Well Name') 506 | wellName = sht.range('B'+str(iwellDefRow)).value 507 | head_I = sht.range('D'+str(iwellDefRow)).options(numbers=int).value 508 | head_J = sht.range('F'+str(iwellDefRow)).options(numbers=int).value 509 | well = CWell(wellName,head_I,head_J) 510 | wells[wellName] = well 511 | 512 | elif(kw == u'Production'): 513 | wName = sht.range('A'+str(iRow+1)).value 514 | iEndProdRow = getKeyWordEndRow(iRow) 515 | df_prod = sht.range((iRow,2),(iEndProdRow,7)).options(pd.DataFrame,index=False).value 516 | iRow = iEndProdRow 517 | 518 | well = wells.get(wName) 519 | well.df_prod = df_prod 520 | 521 | wellNUm = len(wells) 522 | subRow = int(wellNUm/2) 523 | if(wellNUm%2>0): 524 | subRow += 1 525 | wellId = 1 526 | for well in wells.values(): 527 | wellName = well.name 528 | df_prod = well.df_prod 529 | df_prod['Date'] = df_prod['Date'].astype('int64') 530 | df_prod['Date'] = pd.to_datetime(df_prod['Date'],format="%Y%m") 531 | x = df_prod['Date'] 532 | 533 | y1 = df_prod[u'Monthly Oil Production'] 534 | y2 = df_prod[u'Monthly Water Production'] 535 | 536 | ax = fig.add_subplot(subRow,2,wellId) 537 | 538 | lMap1 = {'x':x,'y':y1,'id':0,'ylabel':'OPR'} 539 | lMap2 = {'x':x,'y':y2,'id':1,'ylabel':'WPR'} 540 | leftMaps = [lMap1,lMap2] 541 | rightMaps = [] 542 | 543 | draw2YCurve(ax,wellName,'Date',leftMaps,rightMaps) 544 | 545 | wellId += 1 546 | 547 | plt.show() 548 | 549 | 550 | def readScheduleSection(): 551 | iRow = getKeyWordBeginRow(1,'SCHEDULE SECTION') 552 | index = 'A' 553 | wells = {} 554 | while (sht.range(index+str(iRow)).value!='END'): 555 | iRow = iRow+1 556 | kw = sht.range(index+str(iRow)).value 557 | if(kw==u'General Info'): 558 | iwellDefRow = getKeyWordBeginRow(iRow,u'Well Name') 559 | wellName = sht.range('B'+str(iwellDefRow)).value 560 | head_I = sht.range('D'+str(iwellDefRow)).options(numbers=int).value 561 | head_J = sht.range('F'+str(iwellDefRow)).options(numbers=int).value 562 | well = CWell(wellName,head_I,head_J) 563 | wells[wellName] = well 564 | 565 | elif(kw == u'Well Completion'): 566 | comp = [] 567 | wName = sht.range('B'+str(iRow)).value 568 | well = wells.get(wName) 569 | iRow = iRow + 3 570 | iEndComp = getKeyWordEndRow(iRow) 571 | for i_layer in range(iRow,iEndComp+1): 572 | nLayer = sht.range('D'+str(i_layer)).options(numbers=int).value 573 | comp.append(nLayer) 574 | 575 | iRow = iEndComp 576 | well.comp = comp 577 | 578 | elif(kw == u'Production'): 579 | wName = sht.range('A'+str(iRow+1)).value 580 | iEndProdRow = getKeyWordEndRow(iRow) 581 | prod_date = sht.range((iRow+1,2),(iEndProdRow,2)).options(numbers=str).value 582 | df_prod = sht.range((iRow,3),(iEndProdRow,7)).options(pd.DataFrame,index=False).value 583 | iRow = iEndProdRow 584 | 585 | 586 | well = wells.get(wName) 587 | well.df_prod = df_prod 588 | 589 | 590 | np_prodDate = np.array(prod_date) 591 | asciiList = [n.encode("ascii", "ignore") for n in np_prodDate] 592 | well.prod_date = asciiList 593 | 594 | fModel = h5py.File(hdf5File,'a') 595 | dt = h5py.special_dtype(vlen=str) 596 | 597 | for well in wells.values(): 598 | groupName = "DynamicGroup/Field/"+well.name 599 | wellentry = fModel.create_group(groupName) 600 | wellentry.attrs[u'name'] = well.name 601 | wellentry.attrs[u'id'] = well.id 602 | wellentry.attrs[u'headI'] = well.head_I 603 | wellentry.attrs[u'headJ'] = well.head_J 604 | wellentry.attrs[u'comp'] = well.comp 605 | #wellentry.attrs[u'prodDate'] = well.prod_date 606 | df_to_nparray = well.df_prod.to_records(index=True) 607 | #wellentry.create_dataset(u'prod', data=df_to_nparray) 608 | fModel[groupName+'/'+'prodData'] = df_to_nparray 609 | wellentry.create_dataset('date', (len(well.prod_date),), data=well.prod_date,dtype=dt) 610 | 611 | fModel.close() 612 | 613 | def outputIOSection(f): 614 | f.write('TITLE1 GENERATED FROM EXCEL\nTITLE2 CASE 1\n') 615 | f.write('##################### I/O SECTION #######################\n') 616 | f.write('IO_CONTROL\nSUMMARY\nPRINTGRID 13*0\n') 617 | 618 | def outputDimSection(f,fModel): 619 | f.write('############# DYNAMIC DIMENSIONING SECTION ##############\n') 620 | f.write('DIMENSION\n') 621 | datasetNames = [n for n in fModel.keys()] 622 | nx = 0 623 | ny = 0 624 | nz = 0 625 | for n in datasetNames: 626 | if(n=='StaticGroup'): 627 | staticG = fModel[n] 628 | modelShape = [] 629 | #staticG.items() 630 | for item in staticG.attrs.keys(): 631 | modelShape.append(staticG.attrs[item]) 632 | elif(n=='DynamicGroup'): 633 | dynamicG = fModel[n] 634 | fieldG = dynamicG['Field'] 635 | 636 | dateArray = [] 637 | for wellG in fieldG.keys(): 638 | well = fieldG[wellG] 639 | wellDate = well[u'date'] 640 | dateArray.append(wellDate) 641 | 642 | date_tuple = tuple(dateArray) 643 | mergedDate = np.concatenate(date_tuple) 644 | uniqueDate = np.unique(mergedDate, return_index=True)[0] 645 | 646 | 647 | 648 | nx = modelShape[0] 649 | ny = modelShape[1] 650 | nz = modelShape[2] 651 | f.write('NX {} NY {} NZ {}\n'.format(nx,ny,nz)) 652 | 653 | f.write('NCMAX 3 NWMAX 2\nBLACKOIL\n') 654 | 655 | startDate = uniqueDate[0] 656 | intDate = int(float(startDate)) 657 | #formatedDate = datetime.datetime.strptime(str(intDate), '%Y%m').strftime('%Y %m %d') 658 | 659 | firstDate = datetime.datetime.strptime(str(intDate), '%Y%m') 660 | #delta = datetime.timedelta(days=1) 661 | prevDate = firstDate #-delta 662 | f.write('FIRSTDAY {}\n'.format(prevDate.strftime('%Y %m %d'))) 663 | 664 | def dumpGridSection(f,fModel): 665 | f.write('################### GRID SECTION #######################') 666 | f.write('\nGRID\nCARTESIAN\n') 667 | datasetNames = [n for n in fModel.keys()] 668 | for n in datasetNames: 669 | if(n=='StaticGroup'): 670 | staticG = fModel[n] 671 | modelShape = [] 672 | #staticG.items() 673 | for item in staticG.attrs.keys(): 674 | modelShape.append(staticG.attrs[item]) 675 | 676 | # keys() is used for iter 677 | for item in staticG.keys(): 678 | x = staticG[item].value 679 | 680 | 681 | if(item!='tops'): 682 | f.write('{} XYZALL\n'.format(kwMap[item])) 683 | for indexes, value in np.ndenumerate(x): 684 | z,y,x = indexes 685 | if(x==modelShape[0]-1): 686 | f.write('{:.3f}\n'.format(value)) 687 | else: 688 | f.write('{:.3f} '.format(value)) 689 | else: 690 | f.write('TOPS CON {}'.format(x[0][0])) 691 | 692 | f.write('\n\n') 693 | 694 | elif(n=='PvtGroup'): 695 | pvtG = fModel[n] 696 | fCRock = pvtG.attrs[u'ROCK'] 697 | f.write('CROCK CON {}\n'.format(fCRock)) 698 | 699 | 700 | def dumpPvtSection(f,fModel): 701 | f.write('##################### PVT SECTION #######################\n') 702 | f.write('PVT\n#\n') 703 | f.write('COMPONENTS H2O HOIL SGAS\n') 704 | f.write('# ---- ---- ----\n') 705 | f.write('MW 18.015 210.0 22.9674\n') 706 | f.write('COMPRESS 2.88E-6 1.3687E-5 0\n') 707 | f.write('CTEXP 0 3.8E-5 0.00038\n') 708 | f.write('DENSITY 64.79 49.111 0.0605438\n') 709 | f.write('GRAVITY 1.0383 0.7411 0.7928\n') 710 | f.write('PHASE_ID WATER OIL GAS\n') 711 | 712 | datasetNames = [n for n in fModel.keys()] 713 | for n in datasetNames: 714 | if(n=='PvtGroup'): 715 | pvtG = fModel[n] 716 | fPb = pvtG.attrs[u'PB'] 717 | fBo_s= pvtG.attrs[u'BO_SLOPE'] 718 | 719 | pvto = pvtG[u'PVTO'] 720 | a = pvto[...] 721 | df_pvto = pd.DataFrame(a) 722 | pvtg = pvtG[u'PVTG'] 723 | a = pvtg[...] 724 | df_pvtg = pd.DataFrame(a) 725 | df_merged = pd.merge(df_pvto,df_pvtg,how='outer',on='P') 726 | df_merged = df_merged.sort_values(by = 'P',ascending = True) 727 | df_merged = df_merged.interpolate(method='linear') 728 | 729 | cols = df_merged.columns.tolist() 730 | cols.insert(1,cols.pop(cols.index('RSO'))) 731 | cols.insert(2,cols.pop(cols.index('BO'))) 732 | cols.insert(3,cols.pop(cols.index('BG'))) 733 | cols.insert(4,cols.pop(cols.index('MUO'))) 734 | cols.insert(5,cols.pop(cols.index('MUG'))) 735 | 736 | df_merged = df_merged[cols] 737 | df_merged = df_merged.rename(columns={df_merged.columns[0]:'PTAB' 738 | ,df_merged.columns[2]:'BO' 739 | ,df_merged.columns[3]:'BG' 740 | ,df_merged.columns[4]:'VIS_OIL' 741 | ,df_merged.columns[5]:'VIS_GAS'}) 742 | 743 | df_merged.to_csv(f,sep=' ',float_format='%.3f',index=False) 744 | 745 | f.write('\n#\nPB {}\n'.format(fPb)) 746 | pvtw = pvtG[u'PVTW'] 747 | a = pvtw[...] 748 | df_pvtw = pd.DataFrame(a) 749 | mx_pvtw = df_pvtw.as_matrix(columns=None) 750 | mx_pvto = df_merged.as_matrix(columns=None) 751 | pvtoRows= df_pvto.iloc[:,0].size 752 | fPusat = mx_pvto[pvtoRows-1,0] 753 | # 754 | maxPress = fPusat+200 755 | pvtG.attrs[u'MAXPRESS'] = maxPress 756 | # 757 | BoPb = 0 758 | if(df_pvto[df_pvto[u'P']==fPb].empty): 759 | #df_prodByDate = df_pvto[df_pvto[u'P'].isin([fPb])] 760 | df_pvto.loc[df_pvto.shape[0]+1] = {'P':fPb,'MUO':np.nan,'BO':np.nan,'RSO':np.nan} 761 | df_pvto = df_pvto.interpolate(method='linear') 762 | BoPb = df_pvto[df_pvto[u'P']==fPb]['BO'] 763 | mx_BoPb = BoPb.as_matrix(columns=None) 764 | fBoPb = mx_BoPb[0] 765 | else: 766 | df_pb = df_pvto[df_pvto[u'P'].isin([fPb])] 767 | BoPb = df_pb['BO'] 768 | 769 | mx_BoPb = BoPb.as_matrix(columns=None) 770 | 771 | fBoPb = mx_BoPb[0] 772 | 773 | fBusat = (1 + fBo_s * (fPusat - fPb))* fBoPb 774 | 775 | fBW = mx_pvtw[0,2] 776 | fRefPw = mx_pvtw[0,0] 777 | fVisW = mx_pvtw[0,1] 778 | f.write('BWI {}\nREFERPW {}\nVIS_WAT {}\n'.format(fBW,fRefPw,fVisW)) 779 | f.write('CVISW {}\nCVISO {}\n'.format(0.0,0.0)) 780 | f.write('PUSAT {}\nBUSAT {:.3f}\n'.format(fPusat,fBusat)) 781 | 782 | 783 | f.write('#WATER-OIL RELATIVE PERMEABILITY TABLE\n') 784 | f.write('RELPERM TABLE 1\n') 785 | f.write('STONE2\n') 786 | f.write('WATER-OIL\n') 787 | f.write('# SW KRW KROW PCWO (PSIA)\n') 788 | 789 | swof = pvtG[u'SWOF'] 790 | a = swof[...] 791 | df_swof = pd.DataFrame(a) 792 | df_swof.drop(u'index',axis=1,inplace=True) 793 | df_swof.to_csv(f,sep=' ',float_format='%.5f',index=False,header=False) 794 | 795 | f.write('#\n#GAS-OIL RELATIVE PERMEABILITY TABLE\n#\n') 796 | f.write('GAS-LIQUID\n') 797 | f.write('#SLIQ KRG KROG PCOG (PSIA)\n') 798 | sglf = pvtG[u'SGLF'] 799 | a = sglf[...] 800 | df_sglf = pd.DataFrame(a) 801 | df_sglf.drop(u'index',axis=1,inplace=True) 802 | df_sglf.to_csv(f,sep=' ',float_format='%.5f',index=False,header=False) 803 | 804 | def dumpInitSection(f,fModel): 805 | f.write('############### EQUILLIBRATION SECTION #################\n') 806 | f.write('EQUIL MODEL 1\n') 807 | datasetNames = [n for n in fModel.keys()] 808 | for n in datasetNames: 809 | if(n=='InitGroup'): 810 | initG = fModel[n] 811 | fRefPress = initG.attrs[u'RefPress'] 812 | fRefDepth = initG.attrs[u'RefDepth'] 813 | fwoc = initG.attrs[u'OWC'] 814 | fgoc = initG.attrs[u'OGC'] 815 | 816 | f.write('PRESI CON {}\n'.format(fRefPress)) 817 | f.write('TRESI CON {}\n'.format(100.0)) 818 | f.write('PCGRAVITY\n') 819 | f.write('DEPTH {} DWOC {} DGOC {} PCWOR 0. PCGOC 0.\n'.format(fRefDepth,fwoc,fgoc)) 820 | 821 | def dumpSolutionSection(f,fModel): 822 | f.write('############### SOLUTION SECTION #######################\n') 823 | f.write('SOLUTION\n') 824 | 825 | datasetNames = [n for n in fModel.keys()] 826 | for n in datasetNames: 827 | if(n=='PvtGroup'): 828 | pvtG = fModel[n] 829 | maxpress = pvtG.attrs[u'MAXPRESS'] 830 | f.write('MAXPRES {}\n'.format(maxpress)) 831 | 832 | f.write('RELTOL 0.0005\n') 833 | 834 | def dumpSchduleSection(f,fModel): 835 | f.write('############### RECURRENT SECTION #######################\n') 836 | f.write('RUN\n') 837 | 838 | datasetNames = [n for n in fModel.keys()] 839 | for n in datasetNames: 840 | if(n=='DynamicGroup'): 841 | dynamicG = fModel[n] 842 | fieldG = dynamicG['Field'] 843 | 844 | wellProd_dfs = [] 845 | dateArray = [] 846 | for wellG in fieldG.keys(): 847 | well = fieldG[wellG] 848 | wellDate = well[u'date'] 849 | 850 | prod = well[u'prodData'] 851 | a = prod[...] 852 | df_prod = pd.DataFrame(a) 853 | df_prod[u'wellName'] = well.attrs[u'name'] 854 | df_prod[u'wellId'] = well.attrs[u'id'] 855 | df_prod[u'Date'] = wellDate 856 | 857 | df_prod[u'wopr'] = df_prod[u'Monthly Oil Production']/df_prod[u'Production Days'] 858 | 859 | wellProd_dfs.append(df_prod) 860 | dateArray.append(wellDate) 861 | 862 | df_mergedProd = pd.concat(wellProd_dfs) 863 | mergedDate = df_mergedProd[u'Date'] 864 | uniqueDate = np.unique(mergedDate,return_index=True)[0] 865 | # 866 | #date_tuple = tuple(dateArray) 867 | #mergedDate = np.concatenate(date_tuple) 868 | #uniqueDate = np.unique(mergedDate, return_index=True)[0] 869 | date = uniqueDate[0] 870 | 871 | f.write('WELSPECS\n') 872 | 873 | for wellG in fieldG.keys(): 874 | well = fieldG[wellG] 875 | wellName = well.attrs[u'name'] 876 | wellId = well.attrs[u'id'] 877 | headI = well.attrs[u'headI'] 878 | headJ = well.attrs[u'headJ'] 879 | f.write('WELL {} \'{}\' PRODUCER VERTICAL {} {}\n'.format(wellId,wellName,headI,headJ)) 880 | 881 | f.write('COMPLETION\n') 882 | for wellG in fieldG.keys(): 883 | well = fieldG[wellG] 884 | wellName = well.attrs[u'name'] 885 | wellId = well.attrs[u'id'] 886 | comps = well.attrs[u'comp'] 887 | f.write('WELL {} \'{}\' RW 0.25\n'.format(wellId,wellName)) 888 | for comp in comps: 889 | f.write(' WPIV_KXYH {} -1.0 4*0\n'.format(comp)) 890 | 891 | f.write('\nOPERATION\n') 892 | df_prodByDate = df_mergedProd[df_mergedProd[u'Date'].isin([date])] 893 | for index,prodItem in df_prodByDate.iterrows(): 894 | wellName = prodItem[u'wellName'] 895 | wellId = prodItem[u'wellId'] 896 | wopr = prodItem[u'wopr'] 897 | f.write(' WELL {} \'{}\' BHP 14.7 MAXOIL {:.3f}\n'.format(wellId,wellName,wopr)) 898 | 899 | for i, date in enumerate(uniqueDate): 900 | if i==0: 901 | continue 902 | 903 | intDate = int(float(date)) 904 | formatedDate = datetime.datetime.strptime(str(intDate), '%Y%m').strftime('%Y %m %d') 905 | f.write('DATE {}'.format(formatedDate)) 906 | f.write('\nOPERATION\n') 907 | df_prodByDate = df_mergedProd[df_mergedProd[u'Date'].isin([date])] 908 | for index,prodItem in df_prodByDate.iterrows(): 909 | wellName = prodItem[u'wellName'] 910 | wellId = prodItem[u'wellId'] 911 | wopr = prodItem[u'wopr'] 912 | f.write(' WELL {} \'{}\' BHP 14.7 MAXOIL {:.3f}\n'.format(wellId,wellName,wopr)) 913 | 914 | def dumpModel2XXSim(): 915 | f = open(filename,'w') 916 | 917 | fModel = h5py.File(hdf5File,'r+') 918 | 919 | outputIOSection(f) 920 | outputDimSection(f,fModel) 921 | dumpGridSection(f,fModel) 922 | dumpPvtSection(f,fModel) 923 | dumpInitSection(f,fModel) 924 | dumpSolutionSection(f,fModel) 925 | dumpSchduleSection(f,fModel) 926 | 927 | f.write('\nSTOP') 928 | f.flush() 929 | f.close() 930 | fModel.close() 931 | 932 | 933 | def runXXSim(): 934 | defineGrid() 935 | readGrid() 936 | 937 | readPropSection() 938 | 939 | readInitSection() 940 | 941 | readScheduleSection() 942 | 943 | dumpModel2XXSim() 944 | 945 | -------------------------------------------------------------------------------- /2018.04.30/simulation.xlsm: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ReservoirSimulator/ExcelPySim/107d2fd1089c81e099dce9f6f7e69500de46c1c1/2018.04.30/simulation.xlsm -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 2, June 1991 3 | 4 | Copyright (C) 1989, 1991 Free Software Foundation, Inc., 5 | 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA 6 | Everyone is permitted to copy and distribute verbatim copies 7 | of this license document, but changing it is not allowed. 8 | 9 | Preamble 10 | 11 | The licenses for most software are designed to take away your 12 | freedom to share and change it. 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If this is what you want to do, use the GNU Lesser General 339 | Public License instead of this License. 340 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # ExcelPySim 2 | A reservoir simulation processing software based on the combination of Excel and Python. ![main banner](material/pythonExcel.png?raw=True "main banner") 3 | 4 | ## What 5 | It's a reservoir simulation processing software based on Microsoft Excel, but is developed with Python language. That's, Microsoft Excel is the main work platform or main frame for reservoir simulation work, but the software is developed with Python, not the embedded VBA. 6 | ## Why 7 | Reservoir or geological engineers are born data analyst！And Python is the popular language for data analysis, machine learning and AI, refer to [How popular is Python](https://www.quora.com/How-popular-is-python "Python is popular"). At the same time, Microsoft Excel is the software we use frequently when we work. Why not write a reservoir simulation processing software based on Excel+Python, which will enable us to learn new python skill while working in a familiar Excel environment？ 8 | ## How 9 | ### *How to integrate Python into Excel?* 10 | Thanks [XlWings](https://github.com/ZoomerAnalytics/xlwings "XlWings"), it provides the solution for us because it makes it easy to call Python from Excel and vice versa. Please install [XlWings](https://github.com/ZoomerAnalytics/xlwings "XlWings") and read its documents at first before you try ExcelPySim. 11 | ### *How it work?* 12 | A xlsm file is open to input data which is read by and converted into a deck file for XXSim reservoir simulation software. After finishing input, a button in the xlsm file could be clicked to call the XXSim simulator to run. Please visit [XXSim Github](https://github.com/ReservoirSimulator/XXSim "xxsim") or [XXSim Website](https://www.peclouds.com "xxsim website") for more. 13 | ## Getting Started 14 | It is started with a simple black oil case. 15 | ### Tutorial 1 16 | ![tutor 1](material/tutor1.2019-02-14.gif?raw=True "tutor1 dynamic") 17 | There are two files, 'tutor1.xlsm' and 'tutor1.py' which process the grid section of black oil case. By tutorial 1, it is shown that the combination of [XlWings](https://github.com/ZoomerAnalytics/xlwings "XlWings") and Excel can provide a solution to a Excel-based reservoir simulation pre-processing tool. The use of xlwings is simple, just call your Python functions in your VBA macros. As follow is the python code to read and write Excel, 18 | ```python 19 | # read value from excel 20 | nx = sheet.range('B3').options(numbers=int).value 21 | # write value to excel 22 | sheet.range('A10').value = 'Grid Size: DX' 23 | ``` 24 | 25 | ### Tutorial 2 26 | ![tutor 2](material/tutor2.gif?raw=True "tutor2 dynamic") 27 | Reservoir engineers need to process production data frequently， so the reading and plotting of well production data is put forward to the tutorial 2. The production data format in tutor2.xlsm is just an example, so when you use it, it is need to adjust the Excel format and edit the code according to the actual situation. Two important libs for data analysis, numpy and pandas, have been imported in Tutorial 2 to process chunks of production data, which is much more convenient and effective than VBA. Just one line code to read production data: 28 | ```python 29 | df_prod = sheet.range((iRow,2),(iEndRow,7)).options(pd.DataFrame,index=False).value 30 | ``` 31 | Please visit [pandas tutorial](https://pandas.pydata.org/pandas-docs/stable/getting_started/tutorials.html "Pandas") to learn more. 32 | ### Tutorial 3 33 | In this tutorial, PVT and SCAL data are readed and shown in graph. Also [Pandas](https://pandas.pydata.org "Pandas") is used to read and store table data. 34 | ## Joining us? 35 | Reservoir simulation technology is important one of reservoir engineering methods and reservoir simulation tool should be one of tools at hand of a reservoir engineer. I hope it is helpful by the open source method to those that want to learn or use reservoir simulation technology and even python or machine learning. Anyone is welcome to participate. 36 | ### About me 37 | **Wang Tao, Co-Founder of XXSim reservoir simulation software** 38 | *Reservoir simulation engineer, C++ coder* 39 | Found more about Wang Tao check out these links: 40 | [LinkedIn](https://www.linkedin.com/in/tao-wang-xxsim/ "Linkedin") | [AAPG Blog](https://www.aapg.org/publications/blogs/learn/article/Articleid/42130/interview-with-tao-wang-pecloud "aapg") | [Twitter](https://twitter.com/wangtao74 "Twitter") | [Website](https://www.peclouds.com "peclouds") 41 | -------------------------------------------------------------------------------- /Tutor 2/gridsection.py: -------------------------------------------------------------------------------- 1 | from __future__ import division 2 | import sys 3 | import os 4 | import matplotlib.pyplot as plt 5 | import xlwings as xw 6 | 7 | 8 | gridVaryOpt={ } 9 | defaultDim = 200 10 | kwMap = {'dx':'DX','dy':'DY','dz':'DZ','por':'POROSITY','permx':'KX','permy':'PERMY', 11 | 'permz':'PERMZ'} 12 | 13 | 14 | def readGeneralInfo(sht): 15 | 16 | nx = sht.range('B3').options(numbers=int).value 17 | ny = sht.range('C3').options(numbers=int).value 18 | nz = sht.range('D3').options(numbers=int).value 19 | 20 | gridVaryOpt['xopt'] = sht.range('B4').value 21 | gridVaryOpt['yopt'] = sht.range('C4').value 22 | gridVaryOpt['zopt'] = sht.range('D4').value 23 | 24 | gridVaryOpt['por'] = sht.range('F3').value 25 | gridVaryOpt['kx'] = sht.range('G3').value 26 | gridVaryOpt['ky'] = sht.range('H3').value 27 | gridVaryOpt['kz'] = sht.range('I3').value 28 | 29 | return (nx,ny,nz) 30 | 31 | 32 | def reset(sht): 33 | 34 | whiteColor = (255,255,255) 35 | sht.range((9,3),(9,defaultDim+3-1)).color = whiteColor 36 | sht.range((10,3),(10,defaultDim+3-1)).color = whiteColor 37 | sht.range((11,3),(11,defaultDim+3-1)).color = whiteColor 38 | sht.range((17,3),(17,defaultDim+3-1)).color = whiteColor 39 | sht.range((18,3),(18,defaultDim+3-1)).color = whiteColor 40 | sht.range((19,3),(19,defaultDim+3-1)).color = whiteColor 41 | sht.range((20,3),(20,defaultDim+3-1)).color = whiteColor 42 | 43 | sht.range((9,3),(9,defaultDim+3-1)).value = "" 44 | sht.range((10,3),(10,defaultDim+3-1)).value = "" 45 | sht.range((11,3),(11,defaultDim+3-1)).value = "" 46 | sht.range((17,3),(17,defaultDim+3-1)).value = "" 47 | sht.range((18,3),(18,defaultDim+3-1)).value = "" 48 | sht.range((19,3),(19,defaultDim+3-1)).value = "" 49 | sht.range((20,3),(20,defaultDim+3-1)).value = "" 50 | 51 | def DxInterface(sht,gridDimn,backColor): 52 | if gridVaryOpt['xopt'] == 'CON': 53 | sht.range('A9').value = 'Grid Size: DX' 54 | sht.range('B9').value = 'Constant' 55 | sht.range('C9').color = backColor 56 | elif gridVaryOpt['xopt'] == 'XVAR': 57 | sht.range('A9').value = 'Grid Size: DX' 58 | sht.range('B9').value = 'Variable by X direction' 59 | sht.range((9,3),(9,gridDimn[0]+3-1)).color = backColor 60 | 61 | def DyInterface(sht,gridDimn,backColor): 62 | if gridVaryOpt['yopt'] == 'CON': 63 | sht.range('A10').value = 'Grid Size: DY' 64 | sht.range('B10').value = 'Constant' 65 | sht.range('C10').color = backColor 66 | elif gridVaryOpt['yopt'] == 'YVAR': 67 | sht.range('A10').value = 'Grid Size: DY' 68 | sht.range('B10').value = 'Variable by Y direction' 69 | sht.range((10,3),(10,gridDimn[1]+3-1)).color = backColor 70 | 71 | def DzInterface(sht,gridDimn,backColor): 72 | if gridVaryOpt['zopt'] == 'CON': 73 | sht.range('A11').value = 'Grid Size: DZ' 74 | sht.range('B11').value = 'Constant' 75 | sht.range('C11').color = backColor 76 | elif gridVaryOpt['zopt'] == 'ZVAR': 77 | sht.range('A11').value = 'Grid Size: DZ' 78 | sht.range('B11').value = 'Variable by Z direction' 79 | sht.range((11,3),(11,gridDimn[2]+3-1)).color = backColor 80 | 81 | def PoroInterface(sht,gridDimn,backColor): 82 | if gridVaryOpt['por'] == 'CON': 83 | sht.range('A17').value = 'Porosity' 84 | sht.range('B17').value = 'Constant' 85 | sht.range('C17').color = backColor 86 | elif gridVaryOpt['por'] == 'ZVAR': 87 | sht.range('A17').value = 'Porosity' 88 | sht.range('B17').value = 'Variable by Z direction' 89 | sht.range((17,3),(17,gridDimn[2]+3-1)).color = backColor 90 | 91 | def PermxInterface(sht,gridDimn,backColor): 92 | if gridVaryOpt['kx'] == 'CON': 93 | sht.range('A18').value = 'PERMX' 94 | sht.range('B18').value = 'Constant' 95 | sht.range('C18').color = backColor 96 | elif gridVaryOpt['kx'] == 'ZVAR': 97 | sht.range('A18').value = 'PERMX' 98 | sht.range('B18').value = 'Variable by Z direction' 99 | sht.range((18,3),(18,gridDimn[2]+3-1)).color = backColor 100 | 101 | def PermyInterface(sht,gridDimn,backColor): 102 | if gridVaryOpt['ky'] == 'CON': 103 | sht.range('A19').value = 'PERMY' 104 | sht.range('B19').value = 'Constant' 105 | sht.range('C19').color = backColor 106 | elif gridVaryOpt['ky'] == 'ZVAR': 107 | sht.range('A19').value = 'PERMY' 108 | sht.range('B19').value = 'Variable by Z direction' 109 | sht.range((19,3),(19,gridDimn[2]+3-1)).color = backColor 110 | 111 | def PermzInterface(sht,gridDimn,backColor): 112 | if gridVaryOpt['kz'] == 'CON': 113 | sht.range('A20').value = 'PERMZ' 114 | sht.range('B20').value = 'Constant' 115 | sht.range('C20').color = backColor 116 | elif gridVaryOpt['kz'] == 'ZVAR': 117 | sht.range('A20').value = 'PERMZ' 118 | sht.range('B20').value = 'Variable by Z direction' 119 | sht.range((20,3),(20,gridDimn[2]+3-1)).color = backColor 120 | 121 | def GridStep0(): 122 | 123 | greenColor = (102,255,102) 124 | 125 | sht = xw.Book.caller().sheets[1] 126 | 127 | reset(sht) 128 | 129 | gridDimension = readGeneralInfo(sht) 130 | 131 | DxInterface(sht,gridDimension,greenColor) 132 | 133 | DyInterface(sht,gridDimension,greenColor) 134 | 135 | DzInterface(sht,gridDimension,greenColor) 136 | 137 | PoroInterface(sht,gridDimension,greenColor) 138 | 139 | PermxInterface(sht,gridDimension,greenColor) 140 | 141 | PermyInterface(sht,gridDimension,greenColor) 142 | 143 | PermzInterface(sht,gridDimension,greenColor) 144 | -------------------------------------------------------------------------------- /Tutor 2/tutor2.py: -------------------------------------------------------------------------------- 1 | from __future__ import division 2 | import sys 3 | import os 4 | import numpy as np 5 | import pandas as pd 6 | import matplotlib.pyplot as plt 7 | from mpl_toolkits.mplot3d import Axes3D 8 | from matplotlib import cm 9 | from matplotlib.ticker import LinearLocator, FormatStrFormatter 10 | 11 | import xlwings as xw 12 | 13 | import datetime 14 | 15 | class CWell: 16 | wellCount = 0 17 | 18 | def __init__(self, name, hI,hJ): 19 | self.name = name 20 | self.head_I = hI 21 | self.head_J = hJ 22 | CWell.wellCount += 1 23 | self.id = CWell.wellCount 24 | 25 | 26 | def getKeyWordBeginRow(sht,iRow,strKW): 27 | index = 'A' 28 | while (sht.range(index+str(iRow)).value != strKW): 29 | iRow = iRow+1 30 | 31 | return iRow 32 | 33 | def getKeyWordEndRow(sht,irow): 34 | irow = irow+1 35 | index = 'B' 36 | while (sht.range(index+str(irow)).value != None): 37 | irow = irow+1 38 | 39 | return irow-1 40 | 41 | def draw2YCurve(ax,title,xlabel,leftMaps,rightMaps): 42 | lineColor = ['b+-','ro-','gs-','h--'] 43 | lmaxV = 0 44 | lminV = 10000 45 | rmaxV = 0 46 | rminV = 10000 47 | 48 | for lMap in leftMaps: 49 | x = lMap['x'] 50 | y = lMap['y'] 51 | i = lMap['id'] 52 | ax.plot(x,y,lineColor[i],lw=2,label=lMap['ylabel']) 53 | 54 | maxNum = max(y) 55 | minNum = min(y) 56 | if(maxNum>lmaxV): 57 | lmaxV = maxNum 58 | if(minNumrmaxV): 72 | rmaxV = maxNum 73 | if(minNum0): 82 | ax2.legend(loc='upper right') 83 | ax2.set_ylim(rminV,rmaxV) 84 | 85 | def drawWells(wells): 86 | fig = plt.figure('WELL PRODUCTION') 87 | 88 | wellNUm = len(wells) 89 | subRow = int(wellNUm/2) 90 | if(wellNUm%2>0): 91 | subRow += 1 92 | wellId = 1 93 | for well in wells.values(): 94 | wellName = well.name 95 | df_prod = well.df_prod 96 | df_prod['Date'] = df_prod['Date'].astype('int64') 97 | df_prod['Date'] = pd.to_datetime(df_prod['Date'],format="%Y%m") 98 | x = df_prod['Date'] 99 | 100 | y1 = df_prod[u'Monthly Oil Production'] 101 | y2 = df_prod[u'Monthly Water Production'] 102 | 103 | ax = fig.add_subplot(subRow,2,wellId) 104 | 105 | lMap1 = {'x':x,'y':y1,'id':0,'ylabel':'Monthly Oil Production Rate'} 106 | lMap2 = {'x':x,'y':y2,'id':1,'ylabel':'Monthly Water Production Rate'} 107 | leftMaps = [lMap1,lMap2] 108 | rightMaps = [] 109 | 110 | draw2YCurve(ax,wellName,'Date',leftMaps,rightMaps) 111 | 112 | wellId += 1 113 | 114 | plt.show() 115 | 116 | def readDynamicSection(sht): 117 | iRow = 1 118 | index = 'A' 119 | wells = {} 120 | while (sht.range(index+str(iRow)).value!='END'): 121 | iRow = iRow+1 122 | kw = sht.range(index+str(iRow)).value 123 | if(kw==u'Well Name'): 124 | wellName = sht.range('B'+str(iRow)).value 125 | iwellDefRow = getKeyWordBeginRow(sht,iRow,u'well type') 126 | head_I = sht.range('D'+str(iwellDefRow)).options(numbers=int).value 127 | head_J = sht.range('F'+str(iwellDefRow)).options(numbers=int).value 128 | well = CWell(wellName,head_I,head_J) 129 | wells[wellName] = well 130 | 131 | elif(kw == u'Well Completion'): 132 | comp = [] 133 | wName = sht.range('B'+str(iRow)).value 134 | well = wells.get(wName) 135 | iRow = iRow + 3 136 | iEndComp = getKeyWordEndRow(sht,iRow) 137 | for i_layer in range(iRow,iEndComp+1): 138 | nLayer = sht.range('D'+str(i_layer)).options(numbers=int).value 139 | comp.append(nLayer) 140 | 141 | iRow = iEndComp 142 | well.comp = comp 143 | 144 | elif(kw == u'Production'): 145 | wName = sht.range('A'+str(iRow+1)).value 146 | iEndProdRow = getKeyWordEndRow(sht,iRow) 147 | prod_date = sht.range((iRow+1,2),(iEndProdRow,2)).options(numbers=str).value 148 | df_prod = sht.range((iRow,2),(iEndProdRow,7)).options(pd.DataFrame,index=False).value 149 | iRow = iEndProdRow 150 | 151 | 152 | well = wells.get(wName) 153 | well.df_prod = df_prod 154 | 155 | 156 | np_prodDate = np.array(prod_date) 157 | asciiList = [n.encode("ascii", "ignore") for n in np_prodDate] 158 | well.prod_date = asciiList 159 | 160 | drawWells(wells) 161 | 162 | def DynamicStep0(): 163 | 164 | sht = xw.Book.caller().sheets[0] 165 | 166 | readDynamicSection(sht) 167 | 168 | ''' 169 | if __name__ == '__main__': 170 | # Expects the Excel file next to this source file, adjust accordingly. 171 | xw.Book('tutor2.xlsm').set_mock_caller() 172 | DynamicStep0() 173 | ''' -------------------------------------------------------------------------------- /Tutor 2/tutor2.xlsm: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ReservoirSimulator/ExcelPySim/107d2fd1089c81e099dce9f6f7e69500de46c1c1/Tutor 2/tutor2.xlsm -------------------------------------------------------------------------------- /Tutor 3/dynamicsection.py: -------------------------------------------------------------------------------- 1 | from __future__ import division 2 | import sys 3 | import os 4 | import numpy as np 5 | import pandas as pd 6 | import matplotlib.pyplot as plt 7 | from mpl_toolkits.mplot3d import Axes3D 8 | from matplotlib import cm 9 | from matplotlib.ticker import LinearLocator, FormatStrFormatter 10 | 11 | import xlwings as xw 12 | 13 | import datetime 14 | 15 | class CWell: 16 | wellCount = 0 17 | 18 | def __init__(self, name, hI,hJ): 19 | self.name = name 20 | self.head_I = hI 21 | self.head_J = hJ 22 | CWell.wellCount += 1 23 | self.id = CWell.wellCount 24 | 25 | 26 | def getKeyWordBeginRow(sht,iRow,strKW): 27 | index = 'A' 28 | while (sht.range(index+str(iRow)).value != strKW): 29 | iRow = iRow+1 30 | 31 | return iRow 32 | 33 | def getKeyWordEndRow(sht,irow): 34 | irow = irow+1 35 | index = 'B' 36 | while (sht.range(index+str(irow)).value != None): 37 | irow = irow+1 38 | 39 | return irow-1 40 | 41 | def draw2YCurve(ax,title,xlabel,leftMaps,rightMaps): 42 | lineColor = ['b+-','ro-','gs-','h--'] 43 | lmaxV = 0 44 | lminV = 10000 45 | rmaxV = 0 46 | rminV = 10000 47 | 48 | for lMap in leftMaps: 49 | x = lMap['x'] 50 | y = lMap['y'] 51 | i = lMap['id'] 52 | ax.plot(x,y,lineColor[i],lw=2,label=lMap['ylabel']) 53 | 54 | maxNum = max(y) 55 | minNum = min(y) 56 | if(maxNum>lmaxV): 57 | lmaxV = maxNum 58 | if(minNumrmaxV): 72 | rmaxV = maxNum 73 | if(minNum0): 82 | ax2.legend(loc='upper right') 83 | ax2.set_ylim(rminV,rmaxV) 84 | 85 | def drawWells(wells): 86 | fig = plt.figure('WELL PRODUCTION') 87 | 88 | wellNUm = len(wells) 89 | subRow = int(wellNUm/2) 90 | if(wellNUm%2>0): 91 | subRow += 1 92 | wellId = 1 93 | for well in wells.values(): 94 | wellName = well.name 95 | df_prod = well.df_prod 96 | df_prod['Date'] = df_prod['Date'].astype('int64') 97 | df_prod['Date'] = pd.to_datetime(df_prod['Date'],format="%Y%m") 98 | x = df_prod['Date'] 99 | 100 | y1 = df_prod[u'Monthly Oil Production'] 101 | y2 = df_prod[u'Monthly Water Production'] 102 | 103 | ax = fig.add_subplot(subRow,2,wellId) 104 | 105 | lMap1 = {'x':x,'y':y1,'id':0,'ylabel':'Monthly Oil Production Rate'} 106 | lMap2 = {'x':x,'y':y2,'id':1,'ylabel':'Monthly Water Production Rate'} 107 | leftMaps = [lMap1,lMap2] 108 | rightMaps = [] 109 | 110 | draw2YCurve(ax,wellName,'Date',leftMaps,rightMaps) 111 | 112 | wellId += 1 113 | 114 | plt.show() 115 | 116 | def readDynamicSection(sht): 117 | iRow = 1 118 | index = 'A' 119 | wells = {} 120 | while (sht.range(index+str(iRow)).value!='END'): 121 | iRow = iRow+1 122 | kw = sht.range(index+str(iRow)).value 123 | if(kw==u'Well Name'): 124 | wellName = sht.range('B'+str(iRow)).value 125 | iwellDefRow = getKeyWordBeginRow(sht,iRow,u'well type') 126 | head_I = sht.range('D'+str(iwellDefRow)).options(numbers=int).value 127 | head_J = sht.range('F'+str(iwellDefRow)).options(numbers=int).value 128 | well = CWell(wellName,head_I,head_J) 129 | wells[wellName] = well 130 | 131 | elif(kw == u'Well Completion'): 132 | comp = [] 133 | wName = sht.range('B'+str(iRow)).value 134 | well = wells.get(wName) 135 | iRow = iRow + 3 136 | iEndComp = getKeyWordEndRow(sht,iRow) 137 | for i_layer in range(iRow,iEndComp+1): 138 | nLayer = sht.range('D'+str(i_layer)).options(numbers=int).value 139 | comp.append(nLayer) 140 | 141 | iRow = iEndComp 142 | well.comp = comp 143 | 144 | elif(kw == u'Production'): 145 | wName = sht.range('A'+str(iRow+1)).value 146 | iEndProdRow = getKeyWordEndRow(sht,iRow) 147 | prod_date = sht.range((iRow+1,2),(iEndProdRow,2)).options(numbers=str).value 148 | df_prod = sht.range((iRow,2),(iEndProdRow,7)).options(pd.DataFrame,index=False).value 149 | iRow = iEndProdRow 150 | 151 | 152 | well = wells.get(wName) 153 | well.df_prod = df_prod 154 | 155 | 156 | np_prodDate = np.array(prod_date) 157 | asciiList = [n.encode("ascii", "ignore") for n in np_prodDate] 158 | well.prod_date = asciiList 159 | 160 | drawWells(wells) 161 | 162 | def DynamicStep0(): 163 | 164 | sht = xw.Book.caller().sheets[1] 165 | 166 | readDynamicSection(sht) 167 | 168 | ''' 169 | if __name__ == '__main__': 170 | # Expects the Excel file next to this source file, adjust accordingly. 171 | xw.Book('tutor2.xlsm').set_mock_caller() 172 | DynamicStep0() 173 | ''' -------------------------------------------------------------------------------- /Tutor 3/gridsection.py: -------------------------------------------------------------------------------- 1 | from __future__ import division 2 | import sys 3 | import os 4 | import matplotlib.pyplot as plt 5 | import xlwings as xw 6 | 7 | 8 | gridVaryOpt={ } 9 | defaultDim = 200 10 | kwMap = {'dx':'DX','dy':'DY','dz':'DZ','por':'POROSITY','permx':'KX','permy':'PERMY', 11 | 'permz':'PERMZ'} 12 | 13 | 14 | def readGeneralInfo(sht): 15 | 16 | nx = sht.range('B3').options(numbers=int).value 17 | ny = sht.range('C3').options(numbers=int).value 18 | nz = sht.range('D3').options(numbers=int).value 19 | 20 | gridVaryOpt['xopt'] = sht.range('B4').value 21 | gridVaryOpt['yopt'] = sht.range('C4').value 22 | gridVaryOpt['zopt'] = sht.range('D4').value 23 | 24 | gridVaryOpt['por'] = sht.range('F3').value 25 | gridVaryOpt['kx'] = sht.range('G3').value 26 | gridVaryOpt['ky'] = sht.range('H3').value 27 | gridVaryOpt['kz'] = sht.range('I3').value 28 | 29 | return (nx,ny,nz) 30 | 31 | 32 | def reset(sht): 33 | 34 | whiteColor = (255,255,255) 35 | sht.range((9,3),(9,defaultDim+3-1)).color = whiteColor 36 | sht.range((10,3),(10,defaultDim+3-1)).color = whiteColor 37 | sht.range((11,3),(11,defaultDim+3-1)).color = whiteColor 38 | sht.range((17,3),(17,defaultDim+3-1)).color = whiteColor 39 | sht.range((18,3),(18,defaultDim+3-1)).color = whiteColor 40 | sht.range((19,3),(19,defaultDim+3-1)).color = whiteColor 41 | sht.range((20,3),(20,defaultDim+3-1)).color = whiteColor 42 | 43 | sht.range((9,3),(9,defaultDim+3-1)).value = "" 44 | sht.range((10,3),(10,defaultDim+3-1)).value = "" 45 | sht.range((11,3),(11,defaultDim+3-1)).value = "" 46 | sht.range((17,3),(17,defaultDim+3-1)).value = "" 47 | sht.range((18,3),(18,defaultDim+3-1)).value = "" 48 | sht.range((19,3),(19,defaultDim+3-1)).value = "" 49 | sht.range((20,3),(20,defaultDim+3-1)).value = "" 50 | 51 | def DxInterface(sht,gridDimn,backColor): 52 | if gridVaryOpt['xopt'] == 'CON': 53 | sht.range('A9').value = 'Grid Size: DX' 54 | sht.range('B9').value = 'Constant' 55 | sht.range('C9').color = backColor 56 | elif gridVaryOpt['xopt'] == 'XVAR': 57 | sht.range('A9').value = 'Grid Size: DX' 58 | sht.range('B9').value = 'Variable by X direction' 59 | sht.range((9,3),(9,gridDimn[0]+3-1)).color = backColor 60 | 61 | def DyInterface(sht,gridDimn,backColor): 62 | if gridVaryOpt['yopt'] == 'CON': 63 | sht.range('A10').value = 'Grid Size: DY' 64 | sht.range('B10').value = 'Constant' 65 | sht.range('C10').color = backColor 66 | elif gridVaryOpt['yopt'] == 'YVAR': 67 | sht.range('A10').value = 'Grid Size: DY' 68 | sht.range('B10').value = 'Variable by Y direction' 69 | sht.range((10,3),(10,gridDimn[1]+3-1)).color = backColor 70 | 71 | def DzInterface(sht,gridDimn,backColor): 72 | if gridVaryOpt['zopt'] == 'CON': 73 | sht.range('A11').value = 'Grid Size: DZ' 74 | sht.range('B11').value = 'Constant' 75 | sht.range('C11').color = backColor 76 | elif gridVaryOpt['zopt'] == 'ZVAR': 77 | sht.range('A11').value = 'Grid Size: DZ' 78 | sht.range('B11').value = 'Variable by Z direction' 79 | sht.range((11,3),(11,gridDimn[2]+3-1)).color = backColor 80 | 81 | def PoroInterface(sht,gridDimn,backColor): 82 | if gridVaryOpt['por'] == 'CON': 83 | sht.range('A17').value = 'Porosity' 84 | sht.range('B17').value = 'Constant' 85 | sht.range('C17').color = backColor 86 | elif gridVaryOpt['por'] == 'ZVAR': 87 | sht.range('A17').value = 'Porosity' 88 | sht.range('B17').value = 'Variable by Z direction' 89 | sht.range((17,3),(17,gridDimn[2]+3-1)).color = backColor 90 | 91 | def PermxInterface(sht,gridDimn,backColor): 92 | if gridVaryOpt['kx'] == 'CON': 93 | sht.range('A18').value = 'PERMX' 94 | sht.range('B18').value = 'Constant' 95 | sht.range('C18').color = backColor 96 | elif gridVaryOpt['kx'] == 'ZVAR': 97 | sht.range('A18').value = 'PERMX' 98 | sht.range('B18').value = 'Variable by Z direction' 99 | sht.range((18,3),(18,gridDimn[2]+3-1)).color = backColor 100 | 101 | def PermyInterface(sht,gridDimn,backColor): 102 | if gridVaryOpt['ky'] == 'CON': 103 | sht.range('A19').value = 'PERMY' 104 | sht.range('B19').value = 'Constant' 105 | sht.range('C19').color = backColor 106 | elif gridVaryOpt['ky'] == 'ZVAR': 107 | sht.range('A19').value = 'PERMY' 108 | sht.range('B19').value = 'Variable by Z direction' 109 | sht.range((19,3),(19,gridDimn[2]+3-1)).color = backColor 110 | 111 | def PermzInterface(sht,gridDimn,backColor): 112 | if gridVaryOpt['kz'] == 'CON': 113 | sht.range('A20').value = 'PERMZ' 114 | sht.range('B20').value = 'Constant' 115 | sht.range('C20').color = backColor 116 | elif gridVaryOpt['kz'] == 'ZVAR': 117 | sht.range('A20').value = 'PERMZ' 118 | sht.range('B20').value = 'Variable by Z direction' 119 | sht.range((20,3),(20,gridDimn[2]+3-1)).color = backColor 120 | 121 | def GridStep0(): 122 | 123 | greenColor = (102,255,102) 124 | 125 | sht = xw.Book.caller().sheets[1] 126 | 127 | reset(sht) 128 | 129 | gridDimension = readGeneralInfo(sht) 130 | 131 | DxInterface(sht,gridDimension,greenColor) 132 | 133 | DyInterface(sht,gridDimension,greenColor) 134 | 135 | DzInterface(sht,gridDimension,greenColor) 136 | 137 | PoroInterface(sht,gridDimension,greenColor) 138 | 139 | PermxInterface(sht,gridDimension,greenColor) 140 | 141 | PermyInterface(sht,gridDimension,greenColor) 142 | 143 | PermzInterface(sht,gridDimension,greenColor) 144 | -------------------------------------------------------------------------------- /Tutor 3/propertysection.py: -------------------------------------------------------------------------------- 1 | from __future__ import division 2 | import sys 3 | import os 4 | import numpy as np 5 | import pandas as pd 6 | import matplotlib.pyplot as plt 7 | from mpl_toolkits.mplot3d import Axes3D 8 | from matplotlib import cm 9 | from matplotlib.ticker import LinearLocator, FormatStrFormatter 10 | 11 | import xlwings as xw 12 | 13 | def getKeyWordBeginRow(sht,iRow,strKW): 14 | index = 'A' 15 | while (sht.range(index+str(iRow)).value != strKW): 16 | iRow = iRow+1 17 | 18 | return iRow 19 | 20 | def getKeyWordEndRow(sht,irow): 21 | irow = irow+1 22 | index = 'B' 23 | while (sht.range(index+str(irow)).value != None): 24 | irow = irow+1 25 | 26 | return irow-1 27 | 28 | def draw2YCurve(ax,title,xlabel,leftMaps,rightMaps): 29 | lineColor = ['b+-','ro-','gs-','h--'] 30 | lmaxV = 0 31 | lminV = 10000 32 | rmaxV = 0 33 | rminV = 10000 34 | 35 | for lMap in leftMaps: 36 | x = lMap['x'] 37 | y = lMap['y'] 38 | i = lMap['id'] 39 | ax.plot(x,y,lineColor[i],lw=2,label=lMap['ylabel']) 40 | 41 | maxNum = max(y) 42 | minNum = min(y) 43 | if(maxNum>lmaxV): 44 | lmaxV = maxNum 45 | if(minNumrmaxV): 59 | rmaxV = maxNum 60 | if(minNum0): 69 | ax2.legend(loc='upper right') 70 | ax2.set_ylim(rminV,rmaxV) 71 | 72 | def drawCurve(ax,xlabel,curvelegend,x,yArray): 73 | 74 | lineColor = ['b+-','ro-','gs-','h--'] 75 | 76 | for i,y in enumerate(yArray): 77 | ax.plot(x, y, lineColor[i], lw=2, zorder=30) 78 | 79 | ax.grid() 80 | ax.set_xlabel(xlabel, fontweight='bold', fontsize=15) 81 | ax.set_xticklabels([]) 82 | ax.set_yticklabels([]) 83 | 84 | ax.legend(ax.lines, curvelegend, fancybox=True, shadow=True, prop={'size': 15}) 85 | 86 | def drawPvtCurve(pvt): 87 | fig = plt.figure('PVT') 88 | 89 | # draw pvt_oil 90 | df_PVTo = pvt[0] 91 | o_x = df_PVTo['P'] 92 | o_y0 = df_PVTo['MUO'] 93 | o_y1 = df_PVTo['BO'] 94 | o_y2 = df_PVTo['RSO'] 95 | 96 | ax = fig.add_subplot(2,1,1) 97 | 98 | lMap1 = {'x':o_x,'y':o_y0,'id':0,'ylabel':'MUO'} 99 | lMap2 = {'x':o_x,'y':o_y1,'id':1,'ylabel':'BO'} 100 | rMap = {'x':o_x,'y':o_y2,'id':2,'ylabel':'RSO'} 101 | leftMaps = [lMap1,lMap2] 102 | rightMaps = [rMap] 103 | 104 | draw2YCurve(ax,'Oil PVT','P',leftMaps,rightMaps) 105 | 106 | # draw pvt_gas 107 | df_PVTg = pvt[2] 108 | g_x = df_PVTg['P'] 109 | g_y0 = df_PVTg['MUG'] 110 | g_y1 = df_PVTg['BG'] 111 | 112 | ax = fig.add_subplot(2,1,2) 113 | 114 | lMap1 = {'x':g_x,'y':g_y0,'id':0,'ylabel':'MUG'} 115 | lMap2 = {'x':g_x,'y':g_y1,'id':1,'ylabel':'BG'} 116 | leftMaps = [lMap1,lMap2] 117 | rightMaps = [] 118 | 119 | draw2YCurve(ax,'Gas PVT','P',leftMaps,rightMaps) 120 | 121 | plt.show() 122 | 123 | def readPvt(sht): 124 | iRowPvtSec= getKeyWordBeginRow(sht,1,'PVT') 125 | 126 | iRowPbo = getKeyWordBeginRow(sht,iRowPvtSec,'PBO') 127 | fPbo = sht.range((iRowPbo,2),(iRowPbo,2)).value 128 | iRowMuo_s = getKeyWordBeginRow(sht,iRowPvtSec,'Viso_SLOPE') 129 | fMuo_s = sht.range((iRowMuo_s,2),(iRowMuo_s,2)).value 130 | iRowBo_s = getKeyWordBeginRow(sht,iRowPvtSec,'Bo_SLOPE') 131 | fBo_s = sht.range((iRowBo_s,2),(iRowBo_s,2)).value 132 | 133 | iRowBegin = getKeyWordBeginRow(sht,iRowPvtSec,'OIL-PVT') 134 | iRowEnd = getKeyWordEndRow(sht,iRowBegin) 135 | 136 | df_PVTo = sht.range((iRowBegin,2),(iRowEnd,5)).options(pd.DataFrame,index=False).value 137 | 138 | 139 | # pvtw 140 | iRowBegin = getKeyWordBeginRow(sht,iRowPvtSec,'WATER-PVT') 141 | iRowEnd = getKeyWordEndRow(sht,iRowBegin) 142 | df_PVTw = sht.range((iRowBegin,2),(iRowEnd,4)).options(pd.DataFrame,index=False).value 143 | df_to_nparray = df_PVTw.to_records(index=True) 144 | 145 | # pvtg 146 | iRowBegin = getKeyWordBeginRow(sht,iRowPvtSec,'GAS-PVT') 147 | iRowEnd = getKeyWordEndRow(sht,iRowBegin) 148 | df_PVTg = sht.range((iRowBegin,2),(iRowEnd,4)).options(pd.DataFrame,index=False).value 149 | 150 | # density 151 | iDenRow = getKeyWordBeginRow(sht,iRowPvtSec,u'DENSITY') 152 | df_density = sht.range((iDenRow,2),(iDenRow+1,4)).options(pd.DataFrame).value 153 | 154 | # rock 155 | iRockRow = getKeyWordBeginRow(sht,iRowPvtSec,u'CROCK') 156 | fRock = sht.range((iRockRow,3),(iRockRow,3)).value 157 | 158 | return (df_PVTo,df_PVTw,df_PVTg) 159 | 160 | def drawRelPermCurve(relPerm): 161 | fig = plt.figure('Rel. Perm') 162 | 163 | # OIL-WATER 164 | df_SWOF = relPerm[0] 165 | 166 | wo_x = df_SWOF['SAT'] 167 | wo_y0 = df_SWOF['KRW'] 168 | wo_y1 = df_SWOF['KROW'] 169 | 170 | wo_yArray = [wo_y0,wo_y1] 171 | ax = fig.add_subplot(2,1,1) 172 | 173 | drawCurve(ax,'SAT',['KRW','KROW'],wo_x,wo_yArray) 174 | 175 | # GAS-LIQUID 176 | df_SGLF = relPerm[1] 177 | 178 | x = df_SGLF['SLIQ'] 179 | y0 = df_SGLF['KRG'] 180 | y1 = df_SGLF['KROG'] 181 | 182 | yArray = [y0,y1] 183 | ax = fig.add_subplot(2,1,2) 184 | 185 | drawCurve(ax,'SLIQ',['KRG','KROG'],x,yArray) 186 | 187 | plt.show() 188 | 189 | 190 | def readRelativePerm(sht): 191 | iRowPvtSec= getKeyWordBeginRow(sht,1,'PVT') 192 | # water-oil 193 | iRowBegin = getKeyWordBeginRow(sht,iRowPvtSec,'WATER-OIL') 194 | iRowEnd = getKeyWordEndRow(sht,iRowBegin) 195 | 196 | df_SWOF = sht.range((iRowBegin,2),(iRowEnd,5)).options(pd.DataFrame,index=False).value 197 | 198 | # GAS-LIQUID 199 | iRowBegin = getKeyWordBeginRow(sht,iRowPvtSec,'GAS-LIQUID') 200 | iRowEnd = getKeyWordEndRow(sht,iRowBegin) 201 | 202 | df_SGLF = sht.range((iRowBegin,2),(iRowEnd,5)).options(pd.DataFrame,index=False).value 203 | 204 | return (df_SWOF,df_SGLF) 205 | 206 | def Pvt(): 207 | sht = xw.Book.caller().sheets[0] 208 | pvt = readPvt(sht) 209 | drawPvtCurve(pvt) 210 | 211 | 212 | def RelPerm(): 213 | sht = xw.Book.caller().sheets[0] 214 | relPerm = readRelativePerm(sht) 215 | drawRelPermCurve(relPerm) 216 | 217 | ''' 218 | def readPropSection(sht): 219 | pvt = readPvt(sht) 220 | drawPvtCurve(pvt) 221 | 222 | relPerm = readRelativePerm(sht) 223 | drawRelPermCurve(relPerm) 224 | 225 | if __name__ == '__main__': 226 | # Expects the Excel file next to this source file, adjust accordingly. 227 | xw.Book('tutor3.xlsm').set_mock_caller() 228 | 229 | sht = xw.Book.caller().sheets[0] 230 | 231 | readPropSection(sht) 232 | ''' -------------------------------------------------------------------------------- /Tutor 3/tutor3.xlsm: 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-------------------------------------------------------------------------------- https://raw.githubusercontent.com/ReservoirSimulator/ExcelPySim/107d2fd1089c81e099dce9f6f7e69500de46c1c1/material/tutor2.gif -------------------------------------------------------------------------------- /tutor1.py: -------------------------------------------------------------------------------- 1 | from __future__ import division 2 | import sys 3 | import os 4 | import matplotlib.pyplot as plt 5 | import xlwings as xw 6 | 7 | 8 | sht = xw.Book.caller().sheets[0] 9 | gridVaryOpt={ } 10 | defaultDim = 200 11 | kwMap = {'dx':'DX','dy':'DY','dz':'DZ','por':'POROSITY','permx':'KX','permy':'PERMY', 12 | 'permz':'PERMZ'} 13 | 14 | 15 | def readGeneralInfo(): 16 | nx = sht.range('B3').options(numbers=int).value 17 | ny = sht.range('C3').options(numbers=int).value 18 | nz = sht.range('D3').options(numbers=int).value 19 | 20 | gridVaryOpt['xopt'] = sht.range('B4').value 21 | gridVaryOpt['yopt'] = sht.range('C4').value 22 | gridVaryOpt['zopt'] = sht.range('D4').value 23 | 24 | gridVaryOpt['por'] = sht.range('F3').value 25 | gridVaryOpt['kx'] = sht.range('G3').value 26 | gridVaryOpt['ky'] = sht.range('H3').value 27 | gridVaryOpt['kz'] = sht.range('I3').value 28 | 29 | return (nx,ny,nz) 30 | 31 | 32 | def reset(): 33 | 34 | whiteColor = (255,255,255) 35 | sht.range((9,3),(9,defaultDim+3-1)).color = whiteColor 36 | sht.range((10,3),(10,defaultDim+3-1)).color = whiteColor 37 | sht.range((11,3),(11,defaultDim+3-1)).color = whiteColor 38 | sht.range((17,3),(17,defaultDim+3-1)).color = whiteColor 39 | sht.range((18,3),(18,defaultDim+3-1)).color = whiteColor 40 | sht.range((19,3),(19,defaultDim+3-1)).color = whiteColor 41 | sht.range((20,3),(20,defaultDim+3-1)).color = whiteColor 42 | 43 | sht.range((9,3),(9,defaultDim+3-1)).value = "" 44 | sht.range((10,3),(10,defaultDim+3-1)).value = "" 45 | sht.range((11,3),(11,defaultDim+3-1)).value = "" 46 | sht.range((17,3),(17,defaultDim+3-1)).value = "" 47 | sht.range((18,3),(18,defaultDim+3-1)).value = "" 48 | sht.range((19,3),(19,defaultDim+3-1)).value = "" 49 | sht.range((20,3),(20,defaultDim+3-1)).value = "" 50 | 51 | def DxInterface(gridDimn,backColor): 52 | if gridVaryOpt['xopt'] == 'CON': 53 | sht.range('A9').value = 'Grid Size: DX' 54 | sht.range('B9').value = 'Constant' 55 | sht.range('C9').color = backColor 56 | elif gridVaryOpt['xopt'] == 'XVAR': 57 | sht.range('A9').value = 'Grid Size: DX' 58 | sht.range('B9').value = 'Variable by X direction' 59 | sht.range((9,3),(9,gridDimn[0]+3-1)).color = backColor 60 | 61 | def DyInterface(gridDimn,backColor): 62 | if gridVaryOpt['yopt'] == 'CON': 63 | sht.range('A10').value = 'Grid Size: DY' 64 | sht.range('B10').value = 'Constant' 65 | sht.range('C10').color = backColor 66 | elif gridVaryOpt['yopt'] == 'YVAR': 67 | sht.range('A10').value = 'Grid Size: DY' 68 | sht.range('B10').value = 'Variable by Y direction' 69 | sht.range((10,3),(10,gridDimn[1]+3-1)).color = backColor 70 | 71 | def DzInterface(gridDimn,backColor): 72 | if gridVaryOpt['zopt'] == 'CON': 73 | sht.range('A11').value = 'Grid Size: DZ' 74 | sht.range('B11').value = 'Constant' 75 | sht.range('C11').color = backColor 76 | elif gridVaryOpt['zopt'] == 'ZVAR': 77 | sht.range('A11').value = 'Grid Size: DZ' 78 | sht.range('B11').value = 'Variable by Z direction' 79 | sht.range((11,3),(11,gridDimn[2]+3-1)).color = backColor 80 | 81 | def PoroInterface(gridDimn,backColor): 82 | if gridVaryOpt['por'] == 'CON': 83 | sht.range('A17').value = 'Porosity' 84 | sht.range('B17').value = 'Constant' 85 | sht.range('C17').color = backColor 86 | elif gridVaryOpt['por'] == 'ZVAR': 87 | sht.range('A17').value = 'Porosity' 88 | sht.range('B17').value = 'Variable by Z direction' 89 | sht.range((17,3),(17,gridDimn[2]+3-1)).color = backColor 90 | 91 | def PermxInterface(gridDimn,backColor): 92 | if gridVaryOpt['kx'] == 'CON': 93 | sht.range('A18').value = 'PERMX' 94 | sht.range('B18').value = 'Constant' 95 | sht.range('C18').color = backColor 96 | elif gridVaryOpt['kx'] == 'ZVAR': 97 | sht.range('A18').value = 'PERMX' 98 | sht.range('B18').value = 'Variable by Z direction' 99 | sht.range((18,3),(18,gridDimn[2]+3-1)).color = backColor 100 | 101 | def PermyInterface(gridDimn,backColor): 102 | if gridVaryOpt['ky'] == 'CON': 103 | sht.range('A19').value = 'PERMY' 104 | sht.range('B19').value = 'Constant' 105 | sht.range('C19').color = backColor 106 | elif gridVaryOpt['ky'] == 'ZVAR': 107 | sht.range('A19').value = 'PERMY' 108 | sht.range('B19').value = 'Variable by Z direction' 109 | sht.range((19,3),(19,gridDimn[2]+3-1)).color = backColor 110 | 111 | def PermzInterface(gridDimn,backColor): 112 | if gridVaryOpt['kz'] == 'CON': 113 | sht.range('A20').value = 'PERMZ' 114 | sht.range('B20').value = 'Constant' 115 | sht.range('C20').color = backColor 116 | elif gridVaryOpt['kz'] == 'ZVAR': 117 | sht.range('A20').value = 'PERMZ' 118 | sht.range('B20').value = 'Variable by Z direction' 119 | sht.range((20,3),(20,gridDimn[2]+3-1)).color = backColor 120 | 121 | def GridStep0(): 122 | 123 | greenColor = (102,255,102) 124 | 125 | reset() 126 | 127 | gridDimension = readGeneralInfo() 128 | 129 | DxInterface(gridDimension,greenColor) 130 | 131 | DyInterface(gridDimension,greenColor) 132 | 133 | DzInterface(gridDimension,greenColor) 134 | 135 | PoroInterface(gridDimension,greenColor) 136 | 137 | PermxInterface(gridDimension,greenColor) 138 | 139 | PermyInterface(gridDimension,greenColor) 140 | 141 | PermzInterface(gridDimension,greenColor) -------------------------------------------------------------------------------- /tutor1.xlsm: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ReservoirSimulator/ExcelPySim/107d2fd1089c81e099dce9f6f7e69500de46c1c1/tutor1.xlsm --------------------------------------------------------------------------------