R Markdown
datas<-read.csv("C:/Users/iraq/Desktop/sama fw/karpur.csv",header=TRUE)
summary(datas)
## depth caliper ind.deep ind.med
## Min. :5667 Min. :8.487 Min. : 6.532 Min. : 9.386
## 1st Qu.:5769 1st Qu.:8.556 1st Qu.: 28.799 1st Qu.: 27.892
## Median :5872 Median :8.588 Median :217.849 Median :254.383
## Mean :5873 Mean :8.622 Mean :275.357 Mean :273.357
## 3rd Qu.:5977 3rd Qu.:8.686 3rd Qu.:566.793 3rd Qu.:544.232
## Max. :6083 Max. :8.886 Max. :769.484 Max. :746.028
## gamma phi.N R.deep R.med
## Min. : 16.74 Min. :0.0150 Min. : 1.300 Min. : 1.340
## 1st Qu.: 40.89 1st Qu.:0.2030 1st Qu.: 1.764 1st Qu.: 1.837
## Median : 51.37 Median :0.2450 Median : 4.590 Median : 3.931
## Mean : 53.42 Mean :0.2213 Mean : 24.501 Mean : 21.196
## 3rd Qu.: 62.37 3rd Qu.:0.2640 3rd Qu.: 34.724 3rd Qu.: 35.853
## Max. :112.40 Max. :0.4100 Max. :153.085 Max. :106.542
## SP density.corr density phi.core
## Min. :-73.95 Min. :-0.067000 Min. :1.758 Min. :15.70
## 1st Qu.:-42.01 1st Qu.:-0.016000 1st Qu.:2.023 1st Qu.:23.90
## Median :-32.25 Median :-0.007000 Median :2.099 Median :27.60
## Mean :-30.98 Mean :-0.008883 Mean :2.102 Mean :26.93
## 3rd Qu.:-19.48 3rd Qu.: 0.002000 3rd Qu.:2.181 3rd Qu.:30.70
## Max. : 25.13 Max. : 0.089000 Max. :2.387 Max. :36.30
## k.core Facies
## Min. : 0.42 Length:819
## 1st Qu.: 657.33 Class :character
## Median : 1591.22 Mode :character
## Mean : 2251.91
## 3rd Qu.: 3046.82
## Max. :15600.00
plot(datas$phi.N,datas$phi.core)
model1<-lm(phi.core ~ phi.N+Facies-1, data=datas)
summary(model1)
##
## Call:
## lm(formula = phi.core ~ phi.N + Facies - 1, data = datas)
##
## Residuals:
## Min 1Q Median 3Q Max
## -10.3530 -1.1573 -0.0206 1.0463 10.2852
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## phi.N 1.3364 1.8060 0.74 0.46
## FaciesF1 31.4805 0.2777 113.37 <2e-16 ***
## FaciesF10 20.7680 0.5072 40.95 <2e-16 ***
## FaciesF2 17.5233 0.9390 18.66 <2e-16 ***
## FaciesF3 23.1939 0.4955 46.81 <2e-16 ***
## FaciesF5 27.2953 0.3914 69.74 <2e-16 ***
## FaciesF7 22.5164 0.8730 25.79 <2e-16 ***
## FaciesF8 30.5884 0.5019 60.94 <2e-16 ***
## FaciesF9 26.4448 0.4825 54.81 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.326 on 810 degrees of freedom
## Multiple R-squared: 0.9928, Adjusted R-squared: 0.9928
## F-statistic: 1.246e+04 on 9 and 810 DF, p-value: < 2.2e-16
par(mfrow=c(2,2))
plot(model1)
phi.coreL<-predict(model1,datas)
cbind(datas$phi.core,phi.coreL)
## phi.coreL
## 1 33.9000 32.02847
## 2 33.4131 31.89082
## 3 33.1000 31.75183
## 4 34.9000 31.63957
## 5 35.0644 31.57275
## 6 35.3152 31.54468
## 7 35.6000 31.54335
## 8 34.6448 31.55404
## 9 33.7000 31.56874
## 10 33.1980 31.57943
## 11 32.7597 31.58745
## 12 32.3215 31.57542
## 13 31.4000 31.55671
## 14 32.4996 31.54602
## 15 33.9000 31.54468
## 16 33.7292 31.54736
## 17 33.5000 31.55805
## 18 33.2520 31.57141
## 19 32.9296 31.58478
## 20 32.6000 31.59814
## 21 34.3192 31.62220
## 22 36.0000 31.64358
## 23 34.6627 31.64358
## 24 33.8000 31.63155
## 25 33.2266 31.62754
## 26 32.7943 31.63423
## 27 32.5000 31.63690
## 28 32.9036 31.63957
## 29 33.2095 31.65962
## 30 33.5154 31.68902
## 31 33.8213 31.69704
## 32 34.1272 31.67165
## 33 34.5000 31.63957
## 34 35.4259 31.61284
## 35 36.3000 31.59280
## 36 35.7830 31.58478
## 37 35.3735 31.57676
## 38 34.9000 31.58478
## 39 34.7025 31.59948
## 40 34.5000 31.60750
## 41 32.4415 31.61017
## 42 31.4000 31.61418
## 43 31.0535 31.62086
## 44 30.8000 31.63556
## 45 30.6320 31.66496
## 46 30.5000 31.65427
## 47 23.9000 31.64358
## 48 27.0040 31.61284
## 49 31.6000 31.59413
## 50 31.4887 31.58611
## 51 31.3000 31.58344
## 52 30.9941 31.57810
## 53 30.7000 31.57676
## 54 29.5390 31.57676
## 55 28.5027 31.57810
## 56 27.6000 31.58344
## 57 29.6946 31.58478
## 58 31.3000 31.58077
## 59 33.0000 31.57810
## 60 32.2944 31.58210
## 61 31.2000 31.58745
## 62 31.4391 31.59146
## 63 31.9000 31.59280
## 64 31.7052 31.59547
## 65 31.5001 31.59948
## 66 31.2949 31.60215
## 67 31.0000 31.60616
## 68 30.7807 31.60750
## 69 30.3000 31.60082
## 70 30.8986 31.59413
## 71 31.7000 31.59012
## 72 31.4374 31.58879
## 73 31.1674 31.58879
## 74 31.0000 31.58745
## 75 31.1000 31.58611
## 76 31.2467 31.58478
## 77 31.4000 31.58344
## 78 31.1016 31.58210
## 79 30.8000 31.58210
## 80 30.9330 31.58344
## 81 31.2000 31.58077
## 82 31.1497 31.58077
## 83 31.1000 31.58344
## 84 30.4950 31.58210
## 85 29.8000 31.58077
## 86 29.9671 31.57943
## 87 30.2393 31.57943
## 88 30.5116 31.57943
## 89 30.7838 31.57943
## 90 31.0560 31.57943
## 91 31.3282 31.58077
## 92 31.7000 31.58077
## 93 31.6364 31.57943
## 94 31.5000 31.57943
## 95 31.4013 31.57943
## 96 31.2470 31.57943
## 97 31.1000 31.58077
## 98 31.2575 31.58210
## 99 31.4000 31.58210
## 100 31.0480 31.57943
## 101 30.8000 31.57676
## 102 30.9893 31.57409
## 103 31.1000 31.57542
## 104 29.0577 31.58344
## 105 28.2000 31.59280
## 106 15.8000 20.88824
## 107 18.6982 20.91363
## 108 22.9963 20.93768
## 109 27.8000 31.65695
## 110 26.7824 31.64625
## 111 25.5000 31.62888
## 112 24.7763 31.62353
## 113 24.2000 31.63556
## 114 21.3080 31.66095
## 115 18.4000 17.75320
## 116 17.5382 17.81868
## 117 15.7000 17.86278
## 118 16.2195 17.88283
## 119 17.2452 17.90288
## 120 18.2708 17.90421
## 121 19.2965 17.88283
## 122 20.2000 17.86278
## 123 19.0000 21.09672
## 124 18.1326 21.08737
## 125 17.5000 21.08603
## 126 17.5504 21.08469
## 127 17.5884 21.08336
## 128 17.6264 21.08603
## 129 17.6644 21.10073
## 130 17.7024 21.12479
## 131 17.7404 21.15552
## 132 17.7783 21.18092
## 133 17.8163 21.18493
## 134 17.8543 21.17557
## 135 17.8923 21.16755
## 136 17.9303 21.16488
## 137 17.9683 21.15953
## 138 18.0000 21.14884
## 139 17.5326 21.13949
## 140 17.2000 21.13414
## 141 19.8420 21.12345
## 142 22.6000 21.10474
## 143 26.0232 21.09538
## 144 30.5000 21.09939
## 145 29.7897 23.53073
## 146 29.0670 23.55211
## 147 28.3444 23.58018
## 148 27.6217 23.60290
## 149 26.8990 23.61492
## 150 26.1764 23.60557
## 151 25.6000 23.57750
## 152 24.5062 23.54543
## 153 23.5965 23.52538
## 154 22.6869 23.50934
## 155 21.7772 23.49331
## 156 20.8675 23.47861
## 157 19.9579 23.47192
## 158 19.0000 23.46925
## 159 19.0789 21.04193
## 160 19.2000 21.04326
## 161 19.2202 21.05262
## 162 19.2572 21.06866
## 163 19.3000 21.07801
## 164 21.2929 21.07935
## 165 23.6510 21.08068
## 166 26.0091 21.08336
## 167 28.5000 21.08469
## 168 25.1195 23.50801
## 169 21.5373 23.50667
## 170 19.3000 21.08737
## 171 27.2000 23.52672
## 172 22.7972 23.54142
## 173 19.6000 21.13280
## 174 18.7028 21.15285
## 175 18.0809 21.16087
## 176 17.4591 21.14350
## 177 17.0000 21.11409
## 178 18.4000 21.09538
## 179 18.3561 21.08469
## 180 18.3000 21.06999
## 181 21.4925 21.03658
## 182 23.5000 20.97778
## 183 23.0851 23.38773
## 184 22.7761 23.37303
## 185 22.4671 23.37837
## 186 22.1581 23.41713
## 187 21.8491 23.46257
## 188 21.5402 23.48663
## 189 21.2312 23.50266
## 190 20.9222 23.51736
## 191 20.6132 23.53073
## 192 20.3042 23.53607
## 193 19.9952 21.10207
## 194 19.7000 21.10474
## 195 19.7581 21.09939
## 196 19.8138 21.07133
## 197 19.8694 23.49331
## 198 19.9000 23.49331
## 199 19.9000 23.47727
## 200 21.8858 23.42916
## 201 25.4446 23.35699
## 202 30.0000 23.29952
## 203 29.0486 23.28349
## 204 27.5000 23.26745
## 205 28.2000 23.25275
## 206 27.9391 23.26077
## 207 27.4209 23.29017
## 208 26.9028 20.91229
## 209 26.3846 20.96842
## 210 25.8665 21.01921
## 211 25.3483 21.04995
## 212 24.8302 21.06732
## 213 24.3120 21.07534
## 214 23.7939 21.07667
## 215 23.2757 21.07667
## 216 22.7576 21.07801
## 217 22.2395 21.07801
## 218 21.7213 21.07935
## 219 21.2032 21.08336
## 220 20.6850 21.09138
## 221 20.1669 21.10207
## 222 19.6487 21.11276
## 223 19.1306 21.11409
## 224 18.6124 21.11677
## 225 18.0943 21.11009
## 226 17.5761 23.51469
## 227 17.3000 23.47593
## 228 23.1149 23.43049
## 229 25.4000 23.39842
## 230 20.8970 23.39307
## 231 18.5000 23.41312
## 232 18.6015 23.43985
## 233 18.6832 23.46524
## 234 18.7649 21.05796
## 235 18.8466 21.07267
## 236 18.9283 21.08068
## 237 19.0100 21.08870
## 238 19.0917 21.09806
## 239 19.1734 21.10474
## 240 19.2551 21.10474
## 241 19.3368 21.10207
## 242 19.4185 21.10073
## 243 19.5002 21.10073
## 244 19.5819 21.10474
## 245 19.6636 21.11009
## 246 19.7453 21.11276
## 247 19.8270 21.11543
## 248 19.9087 21.11810
## 249 19.9904 21.12078
## 250 20.0721 21.12078
## 251 20.1538 21.11677
## 252 20.2355 21.11142
## 253 20.3172 21.10741
## 254 20.3990 21.10875
## 255 20.4807 21.11009
## 256 20.5624 21.11409
## 257 20.6441 21.11944
## 258 20.7258 21.12345
## 259 20.8075 21.12479
## 260 20.8892 21.13147
## 261 20.9709 21.14884
## 262 21.0526 21.15285
## 263 21.1343 21.15552
## 264 21.2160 21.15018
## 265 21.2977 21.15151
## 266 21.3794 21.15419
## 267 21.4611 21.15285
## 268 21.5428 21.14884
## 269 21.6245 21.14350
## 270 21.7062 21.13681
## 271 21.7879 21.13147
## 272 21.8696 21.12479
## 273 21.9513 21.12078
## 274 22.0330 21.11810
## 275 22.1147 21.11810
## 276 22.1964 21.11944
## 277 22.2781 21.11543
## 278 22.3598 21.09271
## 279 22.4415 21.04995
## 280 22.5000 27.53181
## 281 20.4237 27.51844
## 282 18.8068 27.50642
## 283 17.7000 20.96976
## 284 21.2844 20.95773
## 285 22.9000 27.46766
## 286 24.0280 27.44895
## 287 24.6000 27.42890
## 288 26.3099 27.40886
## 289 27.7000 27.39015
## 290 25.6304 27.37411
## 291 23.1000 27.36208
## 292 24.4103 27.35272
## 293 25.9823 27.34471
## 294 27.5543 27.33669
## 295 29.1262 27.33001
## 296 30.1000 27.32332
## 297 30.2302 27.31798
## 298 30.3000 27.31530
## 299 31.2000 27.31530
## 300 30.9850 27.31664
## 301 30.7673 27.32065
## 302 30.6000 27.32466
## 303 28.8000 27.34070
## 304 29.4052 27.37010
## 305 30.5371 27.41286
## 306 31.2000 27.47701
## 307 27.3008 27.55319
## 308 23.6000 27.61333
## 309 25.0818 27.64006
## 310 27.9000 27.64941
## 311 27.9000 27.64006
## 312 27.9000 27.62402
## 313 27.6015 27.61199
## 314 27.3000 27.59328
## 315 26.8606 27.57457
## 316 26.2000 27.56522
## 317 27.5406 27.56121
## 318 28.5000 27.55987
## 319 27.5435 27.55987
## 320 26.5000 27.55586
## 321 27.6898 27.55052
## 322 29.4000 27.54784
## 323 28.7972 27.54784
## 324 28.1080 27.55052
## 325 27.5000 27.55453
## 326 26.3578 27.55453
## 327 24.9000 27.55185
## 328 25.7652 27.54918
## 329 27.2743 27.54651
## 330 28.1000 27.54517
## 331 27.7692 27.54250
## 332 27.5416 27.53983
## 333 27.3139 27.54116
## 334 27.0862 27.55319
## 335 26.8586 27.56789
## 336 26.7000 27.57190
## 337 28.2026 27.57190
## 338 28.9000 27.58259
## 339 26.7071 27.59061
## 340 24.9000 27.58526
## 341 25.0203 27.57725
## 342 25.2000 27.57190
## 343 27.5236 27.57056
## 344 30.6000 27.57457
## 345 29.7470 27.58259
## 346 28.9217 27.59195
## 347 28.5000 27.59729
## 348 31.1000 27.59596
## 349 29.7170 27.59462
## 350 27.4000 27.59729
## 351 28.2452 27.59596
## 352 29.5028 27.57858
## 353 30.6000 27.56255
## 354 27.9413 27.55185
## 355 26.6000 27.55319
## 356 27.2000 27.57457
## 357 27.2000 27.60932
## 358 27.2000 27.64540
## 359 23.3897 23.57617
## 360 18.4000 23.58819
## 361 20.8398 21.17423
## 362 24.6000 23.60824
## 363 24.9497 23.60022
## 364 25.5470 23.57884
## 365 26.1444 23.56013
## 366 26.5000 23.55211
## 367 25.0778 23.54944
## 368 24.0652 21.12078
## 369 23.0527 21.11677
## 370 22.0402 21.10608
## 371 21.0276 21.09271
## 372 20.0151 21.08202
## 373 19.2000 21.06999
## 374 20.4398 21.06465
## 375 21.4773 21.06331
## 376 22.5148 21.06465
## 377 23.6000 21.06866
## 378 26.1195 22.82115
## 379 29.2000 22.82650
## 380 30.0648 30.90645
## 381 31.4000 30.91046
## 382 31.3580 30.91447
## 383 31.2990 30.91580
## 384 31.2401 30.90912
## 385 31.2000 30.90778
## 386 31.0132 30.91313
## 387 30.9000 30.91580
## 388 31.1000 30.92115
## 389 31.2534 30.92649
## 390 31.4677 30.92917
## 391 31.6000 30.92783
## 392 30.9478 30.92516
## 393 30.6000 30.92382
## 394 30.8646 30.92248
## 395 31.0000 30.92516
## 396 30.6807 30.93184
## 397 30.5000 30.94119
## 398 31.3144 30.94387
## 399 31.9000 30.93986
## 400 31.6445 30.93718
## 401 31.4150 30.93585
## 402 31.1854 30.93451
## 403 30.9000 30.92783
## 404 30.9840 30.91714
## 405 31.1000 30.91313
## 406 30.5261 30.91580
## 407 29.9000 30.91714
## 408 30.0000 30.91313
## 409 27.7307 30.90377
## 410 24.7307 30.89976
## 411 20.4000 22.82650
## 412 20.6782 22.82249
## 413 21.1782 22.81581
## 414 21.6782 22.81046
## 415 22.3000 22.80244
## 416 22.0492 22.79710
## 417 21.7176 22.79844
## 418 21.3860 21.04594
## 419 21.0544 21.04594
## 420 20.7228 21.05128
## 421 20.3912 21.06331
## 422 20.0596 21.07935
## 423 19.7280 21.08469
## 424 19.3965 21.08603
## 425 19.0649 21.09939
## 426 18.7333 21.10875
## 427 18.4017 21.11677
## 428 18.0701 21.13280
## 429 17.7385 21.15285
## 430 17.4069 21.16889
## 431 17.0000 21.17958
## 432 17.3509 21.18626
## 433 17.8050 21.19161
## 434 18.2591 21.19428
## 435 18.7132 21.19428
## 436 19.1672 21.19428
## 437 19.6213 21.20230
## 438 20.0754 21.21433
## 439 20.5295 21.21967
## 440 20.9836 21.21967
## 441 21.4376 21.23838
## 442 21.8917 21.27714
## 443 22.3458 21.29585
## 444 22.7999 21.29585
## 445 23.2540 21.30387
## 446 23.7080 21.30521
## 447 24.1621 21.30654
## 448 24.6162 21.30521
## 449 25.0703 21.29585
## 450 25.5243 21.28115
## 451 25.9784 21.26378
## 452 26.4325 21.24507
## 453 26.8866 21.22235
## 454 27.3407 21.20631
## 455 27.7947 21.19428
## 456 28.2488 21.18092
## 457 28.7029 21.16221
## 458 29.1570 21.14483
## 459 29.6110 21.14082
## 460 30.5192 21.14082
## 461 30.9733 21.14350
## 462 31.4274 21.14216
## 463 31.7000 30.96525
## 464 31.3508 30.97193
## 465 31.0000 30.97594
## 466 31.3363 30.97460
## 467 32.1000 30.97060
## 468 32.3683 30.96659
## 469 32.9000 30.95990
## 470 32.8747 30.94788
## 471 32.8391 30.93585
## 472 32.8000 30.92649
## 473 30.7071 30.92248
## 474 28.3000 30.91847
## 475 29.4132 30.91313
## 476 30.3000 30.90912
## 477 30.3880 30.91046
## 478 30.5000 30.91313
## 479 30.5000 30.91714
## 480 30.5000 30.92783
## 481 32.3000 30.93986
## 482 32.2698 30.94520
## 483 32.2000 30.94654
## 484 32.0434 30.94387
## 485 31.7000 30.94119
## 486 31.8206 30.94119
## 487 31.9839 30.94119
## 488 32.1000 30.94119
## 489 32.0426 30.94253
## 490 32.0000 30.94119
## 491 31.7157 30.94119
## 492 31.5000 30.93451
## 493 31.7630 30.93852
## 494 31.9000 30.93852
## 495 31.9000 30.93986
## 496 31.9000 30.93852
## 497 31.9000 30.93184
## 498 31.9000 30.91714
## 499 30.6000 30.89308
## 500 30.1362 30.87304
## 501 29.7007 30.86101
## 502 29.2651 30.85833
## 503 29.0000 27.56255
## 504 29.7000 27.56121
## 505 29.1759 27.55720
## 506 28.7000 27.55185
## 507 28.7920 27.54651
## 508 28.9000 27.53983
## 509 28.4025 27.53448
## 510 27.7000 27.53448
## 511 27.8919 27.54250
## 512 28.0000 27.55854
## 513 28.2202 27.57591
## 514 28.3000 30.88105
## 515 29.3094 30.88506
## 516 29.9874 30.88640
## 517 30.6655 30.88774
## 518 31.4848 30.89709
## 519 31.9000 30.90645
## 520 31.7589 30.91313
## 521 31.6668 30.91580
## 522 31.5748 30.91447
## 523 31.5000 30.91179
## 524 31.1219 30.91046
## 525 30.8034 30.91714
## 526 30.6000 30.92382
## 527 30.5374 30.92783
## 528 30.5000 30.92649
## 529 30.5000 30.92248
## 530 30.5000 30.92248
## 531 30.5519 30.92382
## 532 30.7000 30.92248
## 533 30.7000 30.92248
## 534 30.7000 30.92382
## 535 30.7000 30.92382
## 536 30.4053 30.92783
## 537 29.8000 30.93585
## 538 30.3945 30.94387
## 539 31.4988 30.94921
## 540 32.2000 30.95055
## 541 29.5483 30.94654
## 542 28.4000 30.93318
## 543 29.7962 30.91847
## 544 31.2000 30.91313
## 545 30.5736 30.91580
## 546 29.1000 30.91847
## 547 29.5330 30.91981
## 548 30.3000 30.92248
## 549 30.3000 30.92382
## 550 30.3000 30.92649
## 551 30.7348 30.92783
## 552 31.1000 30.93184
## 553 30.0246 30.93451
## 554 29.2000 30.93184
## 555 28.4938 30.93318
## 556 27.6000 30.94119
## 557 28.4051 30.95055
## 558 30.5000 30.96124
## 559 30.8001 30.96659
## 560 31.5000 30.96792
## 561 31.2625 30.96792
## 562 30.8861 30.96792
## 563 30.6000 30.96792
## 564 29.7000 30.96659
## 565 29.9200 30.96391
## 566 30.3588 30.96124
## 567 30.7000 30.95857
## 568 29.3560 30.95589
## 569 28.5000 30.95322
## 570 30.3995 30.94654
## 571 31.3000 30.94253
## 572 31.9000 30.94119
## 573 31.9205 30.94654
## 574 31.9455 30.95189
## 575 31.9705 30.95189
## 576 32.0000 30.94921
## 577 31.9488 30.95055
## 578 31.9000 30.95322
## 579 31.9000 30.95723
## 580 31.9000 30.96258
## 581 31.1272 30.96525
## 582 30.7000 30.96525
## 583 30.3622 30.96391
## 584 30.2000 30.96659
## 585 30.5217 30.96525
## 586 30.7000 30.96258
## 587 31.3073 30.95990
## 588 31.7000 30.95322
## 589 31.0256 30.95189
## 590 30.7000 30.95322
## 591 30.5073 30.95055
## 592 30.4000 30.94387
## 593 31.1410 30.93050
## 594 31.5000 30.90778
## 595 30.1588 30.88774
## 596 29.6000 30.88774
## 597 29.9528 30.90645
## 598 30.2000 30.92783
## 599 31.0981 30.93585
## 600 31.8000 30.93585
## 601 33.2112 30.93986
## 602 33.9000 30.94921
## 603 31.6376 30.95723
## 604 30.8000 30.96124
## 605 31.1000 30.95990
## 606 30.8607 30.95589
## 607 30.5000 30.95456
## 608 31.3120 30.95189
## 609 32.4000 30.95322
## 610 32.7522 30.95589
## 611 33.3000 30.96258
## 612 32.5681 30.97460
## 613 32.1000 30.98396
## 614 32.2147 30.98396
## 615 32.3000 30.98129
## 616 30.4321 30.97728
## 617 29.2000 30.97460
## 618 32.7000 30.97460
## 619 32.7000 30.97861
## 620 32.7000 30.98530
## 621 32.7000 30.98931
## 622 32.4000 30.98931
## 623 31.0435 30.98663
## 624 29.5000 30.98396
## 625 28.7544 30.97861
## 626 28.2285 30.97193
## 627 27.9000 26.81904
## 628 27.8367 26.80701
## 629 27.8000 26.79498
## 630 27.0259 26.78830
## 631 26.4000 26.78295
## 632 31.7000 26.78295
## 633 29.3212 26.78696
## 634 26.1000 26.79097
## 635 27.6000 26.79231
## 636 27.7100 26.79097
## 637 27.7507 26.79231
## 638 27.7037 26.79365
## 639 27.6566 26.79231
## 640 27.6096 26.79097
## 641 27.5625 26.79231
## 642 27.5155 26.79632
## 643 27.4684 26.79766
## 644 27.4000 26.79766
## 645 26.5112 26.79498
## 646 24.1000 26.79365
## 647 24.3573 26.79498
## 648 25.0000 26.79766
## 649 24.9655 26.80166
## 650 24.9000 26.80701
## 651 25.0481 26.81236
## 652 25.3000 26.81369
## 653 25.2234 26.81236
## 654 25.1000 26.80701
## 655 25.2124 26.80300
## 656 25.3921 26.80166
## 657 25.5000 26.80300
## 658 26.0000 26.80166
## 659 25.9482 26.80033
## 660 25.8583 26.79632
## 661 25.8000 26.79498
## 662 25.5999 26.79632
## 663 25.5000 26.79365
## 664 24.5000 26.78696
## 665 24.8623 26.78162
## 666 25.5808 26.77761
## 667 26.1000 26.77494
## 668 26.6048 26.77627
## 669 26.9000 26.78162
## 670 27.2095 26.78429
## 671 27.4000 26.78696
## 672 26.8537 26.79365
## 673 26.5000 26.79632
## 674 27.0408 26.79632
## 675 27.5000 26.79632
## 676 27.1781 26.79632
## 677 26.9000 26.79766
## 678 26.8429 26.80033
## 679 26.8000 26.80300
## 680 26.6323 26.80567
## 681 26.5000 26.80701
## 682 26.6823 26.80835
## 683 26.8000 26.80835
## 684 27.1462 26.80701
## 685 27.4000 26.80434
## 686 27.1677 26.80033
## 687 27.0000 26.79766
## 688 27.4886 26.79766
## 689 27.8000 26.79766
## 690 28.8644 26.79766
## 691 29.4000 26.79899
## 692 29.3019 26.80567
## 693 29.2313 26.81369
## 694 29.1608 26.81904
## 695 29.1000 26.82171
## 696 28.7308 26.82438
## 697 28.4066 26.82706
## 698 28.0824 26.82839
## 699 27.7583 26.82572
## 700 27.4341 26.82305
## 701 27.0000 26.82305
## 702 27.0891 26.82305
## 703 27.2238 26.82037
## 704 27.3585 26.81369
## 705 27.4932 26.80434
## 706 27.6279 26.79766
## 707 27.7627 26.78696
## 708 27.9000 26.77627
## 709 27.5274 26.77895
## 710 27.1474 26.78563
## 711 26.7674 26.78696
## 712 26.3874 26.78295
## 713 25.9000 26.78295
## 714 26.0536 26.78429
## 715 26.2676 26.78830
## 716 26.4817 26.78696
## 717 26.6957 26.78563
## 718 26.9098 26.78830
## 719 27.2000 26.79097
## 720 27.3354 26.78696
## 721 27.4177 26.77895
## 722 27.5000 26.77093
## 723 27.5824 26.76692
## 724 27.7000 26.76692
## 725 27.6248 26.77226
## 726 27.4930 26.78028
## 727 27.3613 26.79097
## 728 27.2296 26.79498
## 729 27.0978 26.78964
## 730 26.9661 26.78295
## 731 26.9000 26.77895
## 732 27.4181 26.77895
## 733 27.7638 26.77895
## 734 28.1096 26.77761
## 735 28.4554 26.77360
## 736 28.8012 26.77226
## 737 29.0000 26.77627
## 738 28.5072 26.77627
## 739 28.1614 26.75088
## 740 27.8156 26.70410
## 741 27.4698 26.67069
## 742 27.1240 26.66802
## 743 26.9000 26.69609
## 744 27.4343 26.73885
## 745 27.8295 26.75222
## 746 28.2247 26.75623
## 747 28.6199 26.75088
## 748 29.0151 26.74153
## 749 28.9249 26.74553
## 750 28.6315 26.74687
## 751 28.3382 26.74553
## 752 28.0449 26.74286
## 753 27.7516 26.73885
## 754 27.4000 26.73484
## 755 27.1447 26.72950
## 756 26.8260 26.71079
## 757 26.5073 26.69475
## 758 26.1886 26.69074
## 759 25.8699 26.70544
## 760 25.4000 26.72816
## 761 25.2557 26.74553
## 762 24.9813 26.75355
## 763 24.7069 26.75489
## 764 24.4324 26.75355
## 765 24.1580 26.75355
## 766 23.9000 26.75756
## 767 24.2038 26.76424
## 768 24.4904 26.76692
## 769 25.0637 26.75623
## 770 25.3503 26.75222
## 771 25.6000 26.75088
## 772 26.1148 26.74821
## 773 26.5710 26.74553
## 774 27.0271 26.74553
## 775 27.4832 26.74420
## 776 27.9393 26.74687
## 777 28.2000 26.75623
## 778 26.5962 26.76558
## 779 25.4735 26.76558
## 780 24.3507 26.75756
## 781 23.2280 26.74153
## 782 21.8000 26.72950
## 783 22.3628 26.73083
## 784 23.1358 26.74420
## 785 23.9088 26.75489
## 786 24.6818 26.75355
## 787 25.4548 26.75088
## 788 26.5000 26.75355
## 789 26.4295 26.75489
## 790 26.3206 26.75222
## 791 26.2117 26.74954
## 792 26.1028 26.74153
## 793 25.9939 26.74153
## 794 25.9000 26.75222
## 795 26.4587 26.76558
## 796 26.9499 26.77627
## 797 27.4411 26.78162
## 798 27.9323 26.77761
## 799 28.7000 27.59596
## 800 29.2799 27.58927
## 801 29.6834 27.58794
## 802 30.0869 27.58393
## 803 30.4903 27.57324
## 804 30.6122 27.56655
## 805 30.0859 27.57992
## 806 29.5596 27.58393
## 807 29.0333 27.58927
## 808 28.5071 27.59061
## 809 27.9000 27.58927
## 810 27.7563 27.59328
## 811 27.5865 27.59729
## 812 27.4167 27.59596
## 813 27.2470 27.58794
## 814 26.9000 27.57324
## 815 25.7547 27.58126
## 816 24.5569 27.59997
## 817 23.3592 27.62001
## 818 22.1614 27.63739
## 819 20.9637 27.64941
plot(phi.coreL,datas$k.core)
model2<-lm(k.core ~ phi.coreL+Facies-1,data=datas)
summary(model2)
##
## Call:
## lm(formula = k.core ~ phi.coreL + Facies - 1, data = datas)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5613.4 -596.9 -130.3 475.0 10449.1
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## phi.coreL -4123.5 898.1 -4.591 5.11e-06 ***
## FaciesF1 132659.2 28386.2 4.673 3.47e-06 ***
## FaciesF10 87869.2 18968.5 4.632 4.21e-06 ***
## FaciesF2 73979.5 16049.0 4.610 4.69e-06 ***
## FaciesF3 97909.7 21087.4 4.643 4.00e-06 ***
## FaciesF5 118915.8 24729.2 4.809 1.81e-06 ***
## FaciesF7 95868.0 20496.1 4.677 3.40e-06 ***
## FaciesF8 130990.3 27786.3 4.714 2.86e-06 ***
## FaciesF9 111323.9 24049.6 4.629 4.28e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1546 on 810 degrees of freedom
## Multiple R-squared: 0.7652, Adjusted R-squared: 0.7626
## F-statistic: 293.2 on 9 and 810 DF, p-value: < 2.2e-16
par(mfrow=c(2,2))
plot(model2)
k.core_log<-predict(model2,datas)
cbind(datas$k.core,k.core_log)
## k.core_log
## 1 2442.5901 589.23713
## 2 3006.9888 1156.85158
## 3 3370.0000 1729.97686
## 4 2270.0000 2192.88573
## 5 2530.7581 2468.42673
## 6 2928.3137 2584.15395
## 7 3380.0000 2589.66477
## 8 3053.2048 2545.57821
## 9 2730.0000 2484.95919
## 10 2802.1687 2440.87263
## 11 2865.1624 2407.80771
## 12 2928.1562 2457.40509
## 13 2960.0000 2534.55657
## 14 2368.7905 2578.64313
## 15 2550.4099 2584.15395
## 16 2759.4919 2573.13231
## 17 3040.0000 2529.04575
## 18 2558.1506 2473.93755
## 19 1931.9360 2418.82935
## 20 1291.5699 2363.72115
## 21 2155.4353 2264.52639
## 22 3000.0000 2176.35327
## 23 3066.8655 2176.35327
## 24 3110.0000 2225.95065
## 25 2686.7124 2242.48311
## 26 2367.5498 2214.92901
## 27 2150.3301 2203.90737
## 28 2163.2437 2192.88573
## 29 2173.0312 2110.22343
## 30 2182.8186 1988.98540
## 31 2192.6060 1955.92048
## 32 2202.3936 2060.62606
## 33 2214.3201 2192.88573
## 34 2613.3105 2303.10213
## 35 2990.0000 2385.76443
## 36 2832.4385 2418.82935
## 37 2707.6108 2451.89427
## 38 2563.3101 2418.82935
## 39 3090.0657 2358.21033
## 40 3630.0000 2325.14541
## 41 2531.0762 2314.12377
## 42 1975.0400 2297.59131
## 43 2147.4971 2270.03721
## 44 2273.6499 2209.41819
## 45 1712.4135 2088.18016
## 46 1271.3800 2132.26671
## 47 418.6400 2176.35327
## 48 1362.4678 2303.10213
## 49 2760.0000 2380.25361
## 50 2602.4993 2413.31853
## 51 2335.4399 2424.34017
## 52 2495.1360 2446.38345
## 53 2648.6399 2451.89427
## 54 2463.9275 2451.89427
## 55 2299.0537 2446.38345
## 56 2155.4399 2424.34017
## 57 2322.1902 2418.82935
## 58 2450.0000 2435.36181
## 59 2371.0400 2446.38345
## 60 2049.1858 2429.85099
## 61 1550.0200 2407.80771
## 62 1722.9451 2391.27525
## 63 2056.2000 2385.76443
## 64 2023.9753 2374.74279
## 65 1990.0415 2358.21033
## 66 1956.1077 2347.18869
## 67 1907.3199 2330.65623
## 68 2196.3706 2325.14541
## 69 2830.0000 2352.69951
## 70 2697.3630 2380.25361
## 71 2519.8000 2396.78607
## 72 2274.8657 2402.29689
## 73 2023.0345 2402.29689
## 74 1866.9200 2407.80771
## 75 2200.3501 2413.31853
## 76 2067.3738 2418.82935
## 77 1928.4800 2424.34017
## 78 1789.1849 2429.85099
## 79 1648.4301 2429.85099
## 80 1866.0350 2424.34017
## 81 2302.9199 2435.36181
## 82 2225.8699 2435.36181
## 83 2149.6299 2424.34017
## 84 2276.3159 2429.85099
## 85 2421.8501 2435.36181
## 86 2427.4851 2440.87263
## 87 2436.6628 2440.87263
## 88 2445.8406 2440.87263
## 89 2455.0183 2440.87263
## 90 2464.1960 2440.87263
## 91 2473.3740 2435.36181
## 92 2485.9099 2435.36181
## 93 2483.5156 2440.87263
## 94 2478.3799 2440.87263
## 95 2523.2039 2440.87263
## 96 2593.2590 2440.87263
## 97 2660.0000 2435.36181
## 98 2638.9934 2429.85099
## 99 2620.0000 2429.85099
## 100 2423.1160 2440.87263
## 101 2284.4299 2451.89427
## 102 2011.7695 2462.91591
## 103 1852.2700 2457.40509
## 104 1467.6908 2424.34017
## 105 1306.1700 2385.76443
## 106 50.1500 1736.14150
## 107 822.9766 1631.43592
## 108 1969.0728 1532.24116
## 109 3250.0000 2121.24507
## 110 2448.0698 2165.33163
## 111 1437.5200 2236.97229
## 112 1641.8264 2259.01557
## 113 1804.5400 2209.41819
## 114 1040.1243 2104.71261
## 115 271.4900 773.90008
## 116 185.0957 503.86990
## 117 0.8100 322.01284
## 118 92.4887 239.35054
## 119 273.4974 156.68824
## 120 454.5060 151.17742
## 121 635.5146 239.35054
## 122 794.9600 322.01284
## 123 193.4600 876.45358
## 124 126.0047 915.02932
## 125 76.8100 920.54014
## 126 85.0097 926.05096
## 127 91.1881 931.56178
## 128 97.3665 920.54014
## 129 103.5448 859.92112
## 130 109.7232 760.72636
## 131 115.9015 633.97750
## 132 122.0799 529.27193
## 133 128.2582 512.73947
## 134 134.4366 551.31521
## 135 140.6149 584.38012
## 136 146.7933 595.40176
## 137 152.9717 617.44504
## 138 158.1300 661.53160
## 139 116.5507 700.10734
## 140 86.9600 722.15062
## 141 63.8231 766.23718
## 142 39.6700 843.38866
## 143 282.9963 881.96440
## 144 601.2100 865.43194
## 145 599.3371 880.37886
## 146 597.4316 792.20574
## 147 595.5261 676.47852
## 148 593.6207 582.79459
## 149 591.7152 533.19721
## 150 589.8097 571.77295
## 151 588.2900 687.50016
## 152 522.3776 819.75984
## 153 467.5622 902.42214
## 154 412.7467 968.55198
## 155 357.9313 1034.68182
## 156 303.1158 1095.30084
## 157 248.3004 1122.85494
## 158 190.5800 1133.87658
## 159 181.7682 1102.39720
## 160 168.2400 1096.88638
## 161 149.2137 1058.31064
## 162 114.3747 992.18080
## 163 74.1400 953.60506
## 164 146.0790 948.09424
## 165 231.2015 942.58342
## 166 316.3239 931.56178
## 167 406.2400 926.05096
## 168 308.4382 974.06280
## 169 204.7999 979.57362
## 170 140.0700 915.02932
## 171 173.4400 896.91132
## 172 73.2072 836.29230
## 173 0.4200 727.66144
## 174 2.2869 644.99914
## 175 3.5809 611.93422
## 176 4.8748 683.57488
## 177 5.8300 804.81292
## 178 35.8600 881.96440
## 179 44.5030 926.05096
## 180 55.5300 986.66998
## 181 1599.2813 1124.44048
## 182 2570.0000 1366.91656
## 183 2294.7261 1470.03660
## 184 2089.7009 1530.65562
## 185 1884.6757 1508.61234
## 186 1679.6505 1348.79856
## 187 1474.6252 1161.43068
## 188 1269.6000 1062.23592
## 189 1064.5748 996.10608
## 190 859.5496 935.48706
## 191 654.5244 880.37886
## 192 449.4991 858.33558
## 193 244.4739 854.41030
## 194 48.6200 843.38866
## 195 43.9438 865.43194
## 196 39.4679 981.15916
## 197 34.9919 1034.68182
## 198 32.5300 1034.68182
## 199 54.2100 1100.81166
## 200 906.6724 1299.20118
## 201 2434.4473 1596.78546
## 202 4390.0000 1833.75072
## 203 4804.8022 1899.88055
## 204 5480.0000 1966.01039
## 205 4900.0000 2026.62941
## 206 4786.5928 1993.56449
## 207 4561.4106 1872.32645
## 208 4336.2285 1636.94674
## 209 4111.0464 1405.49230
## 210 3885.8645 1196.08114
## 211 3660.6824 1069.33228
## 212 3435.5005 997.69162
## 213 3210.3184 964.62670
## 214 2985.1362 959.11588
## 215 2759.9543 959.11588
## 216 2534.7722 953.60506
## 217 2309.5901 953.60506
## 218 2084.4082 948.09424
## 219 1859.2261 931.56178
## 220 1634.0441 898.49686
## 221 1408.8621 854.41030
## 222 1183.6799 810.32374
## 223 958.4979 804.81292
## 224 733.3159 793.79128
## 225 508.1339 821.34538
## 226 282.9518 946.50870
## 227 162.9400 1106.32248
## 228 1109.5569 1293.69036
## 229 1481.5601 1425.95004
## 230 534.7041 1447.99332
## 231 30.6700 1365.33102
## 232 70.1081 1255.11462
## 233 101.8555 1150.40904
## 234 133.6028 1036.26736
## 235 165.3502 975.64834
## 236 197.0975 942.58342
## 237 228.8449 909.51850
## 238 260.5923 870.94276
## 239 292.3396 843.38866
## 240 324.0869 843.38866
## 241 355.8343 854.41030
## 242 387.5817 859.92112
## 243 419.3290 859.92112
## 244 451.0764 843.38866
## 245 482.8237 821.34538
## 246 514.5711 810.32374
## 247 546.3184 799.30210
## 248 578.0658 788.28046
## 249 609.8132 777.25882
## 250 641.5605 777.25882
## 251 673.3079 793.79128
## 252 705.0552 815.83456
## 253 736.8026 832.36702
## 254 768.5499 826.85620
## 255 800.2973 821.34538
## 256 832.0446 804.81292
## 257 863.7920 782.76964
## 258 895.5394 766.23718
## 259 927.2867 760.72636
## 260 959.0341 733.17226
## 261 990.7814 661.53160
## 262 1022.5287 644.99914
## 263 1054.2761 633.97750
## 264 1086.0234 656.02078
## 265 1117.7709 650.50996
## 266 1149.5182 639.48832
## 267 1181.2655 644.99914
## 268 1213.0129 661.53160
## 269 1244.7603 683.57488
## 270 1276.5076 711.12898
## 271 1308.2550 733.17226
## 272 1340.0023 760.72636
## 273 1371.7496 777.25882
## 274 1403.4971 788.28046
## 275 1435.2444 788.28046
## 276 1466.9917 782.76964
## 277 1498.7391 799.30210
## 278 1530.4865 892.98604
## 279 1562.2338 1069.33228
## 280 1584.9600 5387.87440
## 281 1066.3792 5442.98260
## 282 662.5491 5492.57998
## 283 386.1200 1399.98148
## 284 1821.4403 1449.57886
## 285 2468.4099 5652.39376
## 286 2346.7214 5729.54524
## 287 2285.0200 5812.20754
## 288 4135.5439 5894.86983
## 289 5640.0000 5972.02131
## 290 3580.1563 6038.15115
## 291 1061.7000 6087.74853
## 292 2019.7881 6126.32427
## 293 3169.1899 6159.38919
## 294 4318.5918 6192.45411
## 295 5467.9937 6220.00821
## 296 6180.0000 6247.56231
## 297 6844.0718 6269.60559
## 298 7200.0000 6280.62723
## 299 8390.0000 6280.62723
## 300 7956.4258 6275.11641
## 301 7517.4834 6258.58395
## 302 7180.0000 6242.05149
## 303 562.5400 6175.92165
## 304 1348.7238 6054.68361
## 305 2818.8896 5878.33737
## 306 3680.0000 5613.81802
## 307 2216.6179 5299.70128
## 308 827.6600 5051.71438
## 309 1538.3466 4941.49798
## 310 2890.0000 4902.92224
## 311 2383.2690 4941.49798
## 312 2029.4900 5007.62782
## 313 3820.7578 5057.22520
## 314 5630.0000 5134.37668
## 315 5202.5576 5211.52816
## 316 4560.0000 5250.10390
## 317 6232.8345 5266.63636
## 318 7430.0000 5272.14718
## 319 6186.6069 5272.14718
## 320 4830.0000 5288.67964
## 321 5338.7207 5310.72292
## 322 6070.0000 5321.74456
## 323 6447.5181 5321.74456
## 324 6879.2051 5310.72292
## 325 7260.0000 5294.19046
## 326 5067.7798 5294.19046
## 327 2270.0000 5305.21210
## 328 1917.3143 5316.23374
## 329 1302.1428 5327.25538
## 330 965.5400 5332.76620
## 331 2610.9341 5343.78784
## 332 3743.4775 5354.80948
## 333 4876.0210 5349.29866
## 334 6008.5645 5299.70128
## 335 7141.1079 5239.08226
## 336 7930.0000 5222.54980
## 337 8742.7529 5222.54980
## 338 9120.0000 5178.46324
## 339 9898.4785 5145.39832
## 340 10540.0000 5167.44160
## 341 9533.3623 5200.50652
## 342 8030.0000 5222.54980
## 343 6911.2437 5228.06062
## 344 5430.0000 5211.52816
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karpur2<-cbind(datas,k.core_log)
write.csv(karpur2,"karpur2.csv")
par(mfrow=c(1,5))
plot(y=y<-(datas$depth),ylim=rev(range(datas$depth)),x=x<-(datas$phi.core),
type="l", col="darkgreen", lwd = 5, pch=17, xlab='phi.core',
ylab='depth, m', xlim=c(14.1,37.2), cex=1.5, cex.lab=1.5, cex.axis=1.2)
plot(y=y<-(datas$depth),ylim=rev(range(datas$depth)),x=x<-(datas$k.core),
type="l", col="darkblue", lwd = 5, pch=17, xlab='k.core',
ylab='depth, m', xlim=c(0.3,17000), cex=1.5, cex.lab=1.5, cex.axis=1.2)
plot(y=y<-(datas$depth),ylim=rev(range(datas$depth)),x=x<-(datas$phi.N),
type="l", col="yellow", lwd = 5, pch=17, xlab='phi.N',
ylab='depth, m', xlim=c(0.014,0.52), cex=1.5, cex.lab=1.5, cex.axis=1.2)
plot(y=y<-(datas$depth),ylim=rev(range(datas$depth)),x=x<-(phi.coreL),
type="l", col="red", lwd = 5, pch=17, xlab='phi.coreL',
ylab='depth, m',xlim=c(16,34), cex=1.5, cex.lab=1.5, cex.axis=1.2)
plot(y=y<-(datas$depth),ylim=rev(range(datas$depth)),x=x<-(k.core_log),
type="l", col="black", lwd = 5, pch=17, xlab='k.core_log',
ylab='depth, m',xlim=c(10,6300), cex=1.5, cex.lab=1.5, cex.axis=1.2)
