Basic exampleΒΆ
In the example below you can see how to:
- read a LAS file in
- look at the information in the header
- see basic curve information
- make a graph
In [29]: import lasio
In [30]: las = lasio.read(r"C:\Users\kent\Code\las\examples\2.0\49-005-30258.las")
In [31]: las.header
Out[31]:
{'Curves': [CurveItem(mnemonic=DEPT, unit=F, value=, descr=1 DEPTH, original_mnemonic=DEPT, data.shape=(235,)),
CurveItem(mnemonic=DT, unit=US/F, value=, descr=2 SONIC DELTA-T, original_mnemonic=DT, data.shape=(235,)),
CurveItem(mnemonic=RESD, unit=OHMM, value=, descr=3 DEEP RESISTIVITY, original_mnemonic=RESD, data.shape=(235,)),
CurveItem(mnemonic=SP, unit=MV, value=, descr=4 SP CURVE, original_mnemonic=SP, data.shape=(235,)),
CurveItem(mnemonic=GR, unit=GAPI, value=, descr=5 GAMMA RAY, original_mnemonic=GR, data.shape=(235,))],
'Other': '',
'Parameter': [HeaderItem(mnemonic=BHT, unit=DEGF, value=194.0, descr=BOTTOM HOLE TEMPERATURE, original_mnemonic=BHT),
HeaderItem(mnemonic=RMF, unit=OHMM, value=0.441, descr=MUD FILTRATE RESISTIVITY, original_mnemonic=RMF),
HeaderItem(mnemonic=RMFT, unit=DEGF, value=68.0, descr=MEASURE TEMPERATURE OF RMF, original_mnemonic=RMFT),
HeaderItem(mnemonic=EKB, unit=F, value=4642.0, descr=ELEVATION KELLY BUSHING, original_mnemonic=EKB),
HeaderItem(mnemonic=SECT, unit=, value=36, descr=SECTION, original_mnemonic=SECT),
HeaderItem(mnemonic=TOWN, unit=, value=47N, descr=TOWNSHIP, original_mnemonic=TOWN),
HeaderItem(mnemonic=RANG, unit=, value=71W, descr=RANGE, original_mnemonic=RANG)],
'Version': [HeaderItem(mnemonic=VERS, unit=, value=2.0, descr=CWLS log ASCII Standard - Version 2.0, original_mnemonic=VERS),
HeaderItem(mnemonic=WRAP, unit=, value=NO, descr=One Line per Depth Step, original_mnemonic=WRAP),
HeaderItem(mnemonic=CREA, unit=, value=02-08-2006, descr=LAS File Creation Date (MM-DD-YYYY), original_mnemonic=CREA)],
'Well': [HeaderItem(mnemonic=STRT, unit=F, value=10180.0, descr=START DEPTH, original_mnemonic=STRT),
HeaderItem(mnemonic=STOP, unit=F, value=10414.0, descr=STOP DEPTH, original_mnemonic=STOP),
HeaderItem(mnemonic=STEP, unit=F, value=1.0, descr=STEP, original_mnemonic=STEP),
HeaderItem(mnemonic=NULL, unit=, value=-999.25, descr=NULL VALUE, original_mnemonic=NULL),
HeaderItem(mnemonic=COMP, unit=, value=Cramer Oil, descr=COMPANY, original_mnemonic=COMP),
HeaderItem(mnemonic=WELL, unit=, value=#36-16 State, descr=WELL, original_mnemonic=WELL),
HeaderItem(mnemonic=LOC, unit=, value=SE SE 36-47N-71W, descr=LOCATION, original_mnemonic=LOC),
HeaderItem(mnemonic=CNTY, unit=, value=Campbell, descr=COUNTY, original_mnemonic=CNTY),
HeaderItem(mnemonic=FLD, unit=, value=, descr=FIELD, original_mnemonic=FLD),
HeaderItem(mnemonic=STAT, unit=, value=Wyoming, descr=STATE, original_mnemonic=STAT),
HeaderItem(mnemonic=CTRY, unit=, value=U.S.A., descr=COUNTRY, original_mnemonic=CTRY),
HeaderItem(mnemonic=DATE, unit=, value=11/91, descr=COMPLETION DATE (MM/YY), original_mnemonic=DATE),
HeaderItem(mnemonic=API, unit=, value=49-005-30258-0000, descr=API NUMBER, original_mnemonic=API),
HeaderItem(mnemonic=SRVC, unit=, value=, descr=SERVICE COMPANY, original_mnemonic=SRVC)]}
In [33]: type(las.data)
Out[33]: numpy.ndarray
In [34]: las.data.shape
Out[34]: (235, 5)
In [35]: for curve in las.curves:
...: print(curve.mnemonic)
...: print(curve.unit)
...: print(curve.data)
...: print("\n")
...:
DEPT
F
[ 10180. 10181. 10182. 10183. 10184. 10185. 10186. 10187. 10188.
10189. 10190. 10191. 10192. 10193. 10194. 10195. 10196. 10197.
10198. 10199. 10200. 10201. 10202. 10203. 10204. 10205. 10206.
10207. 10208. 10209. 10210. 10211. 10212. 10213. 10214. 10215.
10216. 10217. 10218. 10219. 10220. 10221. 10222. 10223. 10224.
10225. 10226. 10227. 10228. 10229. 10230. 10231. 10232. 10233.
10234. 10235. 10236. 10237. 10238. 10239. 10240. 10241. 10242.
10243. 10244. 10245. 10246. 10247. 10248. 10249. 10250. 10251.
10252. 10253. 10254. 10255. 10256. 10257. 10258. 10259. 10260.
10261. 10262. 10263. 10264. 10265. 10266. 10267. 10268. 10269.
10270. 10271. 10272. 10273. 10274. 10275. 10276. 10277. 10278.
10279. 10280. 10281. 10282. 10283. 10284. 10285. 10286. 10287.
10288. 10289. 10290. 10291. 10292. 10293. 10294. 10295. 10296.
10297. 10298. 10299. 10300. 10301. 10302. 10303. 10304. 10305.
10306. 10307. 10308. 10309. 10310. 10311. 10312. 10313. 10314.
10315. 10316. 10317. 10318. 10319. 10320. 10321. 10322. 10323.
10324. 10325. 10326. 10327. 10328. 10329. 10330. 10331. 10332.
10333. 10334. 10335. 10336. 10337. 10338. 10339. 10340. 10341.
10342. 10343. 10344. 10345. 10346. 10347. 10348. 10349. 10350.
10351. 10352. 10353. 10354. 10355. 10356. 10357. 10358. 10359.
10360. 10361. 10362. 10363. 10364. 10365. 10366. 10367. 10368.
10369. 10370. 10371. 10372. 10373. 10374. 10375. 10376. 10377.
10378. 10379. 10380. 10381. 10382. 10383. 10384. 10385. 10386.
10387. 10388. 10389. 10390. 10391. 10392. 10393. 10394. 10395.
10396. 10397. 10398. 10399. 10400. 10401. 10402. 10403. 10404.
10405. 10406. 10407. 10408. 10409. 10410. 10411. 10412. 10413.
10414.]
DT
US/F
[ 59.9 59.9 60.5 63.5 64.5 64.6 61.5 59.2 55.9 52.1 49.1 47.8
47.2 47.2 48.5 49.6 48.3 46.9 46.6 46.8 46.7 47.8 51.2 51.6
51.1 51.4 52.3 52.3 51.5 51.2 53.3 57.6 60.6 60.8 59.5 59.7
61.1 61.6 61.8 62. 62.2 62.2 62.2 60.9 60.8 61.5 61.4 61.9
63.2 64.4 62.6 61.4 61. 61.1 62.8 65.4 66.3 66.2 68.3 69.8
70.6 72.4 74.2 74.3 71.5 63.5 60.1 65.2 68.2 66.4 63.2 63.4
65.3 65.1 64.1 63.9 63.9 63.9 63.9 63.5 62.7 63.1 63.6 61.1
58.4 58.1 58.1 57.7 57.1 56.6 56.8 59.5 61.3 61.9 61.9 62.1
62.5 62.5 62.5 62.4 62. 60.7 57.5 56. 56. 57.8 60. 60.3
60.2 59.9 60.4 60.9 61.4 61.4 56.1 51.2 48.4 48.5 49.8 49.8
50. 50.9 50.5 47.9 46.3 46.1 46.4 46.4 45.8 45.9 46.5 46.7
47.3 51.9 55.7 61.2 66.5 68.9 69.6 69.6 69.1 68. 66.9 66.7
66.6 66. 65. 64.4 64. 64.6 64.7 64.4 64.4 65.5 67.4 69.3
70.9 72.4 73.3 73.7 73.8 73.4 73.4 74.4 75.4 75.2 72.6 71.6
72. 74.3 74.6 74.7 72.3 71.9 75.5 77.6 78.3 75.8 73.8 71.6
69.3 67.1 65. 64. 63.8 63.9 65.1 65.5 64.3 64.4 66. 66.
64.6 64.9 65. 62.6 60.4 59.3 59.3 62.6 63.6 61.5 61.7 62.3
61.9 62.3 63.2 63.5 63.5 62.7 60. 57. 54. 49.1 47.2 46.7
47.1 47.6 48.8 49.8 50.8 51.1 50.2 49. 48.4 50.6 50.7 50.4
49.9 49.7 49.6 51.5 52.5 53.2 54.1]
RESD
OHMM
[ 2.20000000e+01 2.10000000e+01 1.97000000e+01 1.89000000e+01
1.82000000e+01 1.80000000e+01 1.80000000e+01 2.10000000e+01
2.90000000e+01 5.30000000e+01 3.90000000e+02 1.50100000e+03
2.09300000e+03 1.67700000e+03 1.07700000e+03 7.65000000e+02
5.64000000e+02 5.54000000e+02 4.87000000e+02 1.59000000e+02
7.40000000e+01 5.70000000e+01 5.00000000e+01 4.80000000e+01
4.80000000e+01 4.90000000e+01 5.60000000e+01 5.90000000e+01
6.10000000e+01 5.20000000e+01 2.40000000e+01 1.75000000e+01
1.54000000e+01 1.52000000e+01 1.52000000e+01 1.52000000e+01
1.47000000e+01 1.29000000e+01 1.20000000e+01 1.10000000e+01
1.06000000e+01 1.05000000e+01 1.05000000e+01 1.08000000e+01
1.11000000e+01 1.12000000e+01 1.07000000e+01 9.90000000e+00
9.30000000e+00 9.00000000e+00 9.40000000e+00 1.01000000e+01
1.02000000e+01 1.00000000e+01 8.00000000e+00 7.10000000e+00
6.50000000e+00 5.80000000e+00 5.00000000e+00 4.20000000e+00
3.60000000e+00 3.30000000e+00 3.20000000e+00 3.30000000e+00
4.00000000e+00 4.90000000e+00 5.40000000e+00 5.80000000e+00
6.20000000e+00 6.60000000e+00 7.60000000e+00 8.90000000e+00
1.01000000e+01 1.12000000e+01 1.24000000e+01 1.51000000e+01
1.66000000e+01 1.75000000e+01 1.80000000e+01 1.80000000e+01
1.80000000e+01 1.80000000e+01 1.90000000e+01 2.10000000e+01
2.30000000e+01 2.70000000e+01 3.00000000e+01 3.30000000e+01
3.50000000e+01 3.50000000e+01 3.00000000e+01 2.70000000e+01
2.30000000e+01 1.99000000e+01 1.89000000e+01 1.85000000e+01
1.94000000e+01 2.00000000e+01 2.00000000e+01 2.20000000e+01
2.40000000e+01 2.60000000e+01 3.00000000e+01 3.30000000e+01
3.40000000e+01 3.00000000e+01 2.80000000e+01 2.60000000e+01
2.60000000e+01 2.90000000e+01 3.40000000e+01 3.50000000e+01
3.90000000e+01 4.40000000e+01 6.60000000e+01 1.22000000e+02
2.48000000e+02 1.72400000e+03 2.03600000e+03 2.03600000e+03
2.05500000e+03 2.09300000e+03 2.11300000e+03 2.11300000e+03
2.11300000e+03 2.09300000e+03 1.63100000e+03 7.51000000e+02
2.50000000e+02 2.16000000e+02 1.99000000e+02 1.76000000e+02
1.30000000e+02 9.50000000e+01 6.90000000e+01 4.70000000e+01
3.10000000e+01 2.10000000e+01 1.75000000e+01 1.61000000e+01
1.61000000e+01 1.61000000e+01 1.75000000e+01 1.80000000e+01
1.83000000e+01 1.83000000e+01 1.83000000e+01 1.83000000e+01
1.82000000e+01 1.74000000e+01 1.63000000e+01 1.54000000e+01
1.40000000e+01 1.27000000e+01 1.10000000e+01 9.00000000e+00
7.50000000e+00 6.70000000e+00 6.10000000e+00 5.70000000e+00
5.60000000e+00 5.30000000e+00 5.00000000e+00 4.50000000e+00
4.00000000e+00 3.50000000e+00 3.20000000e+00 2.80000000e+00
2.50000000e+00 2.20000000e+00 1.94000000e+00 1.72000000e+00
1.59000000e+00 1.50000000e+00 1.43000000e+00 1.37000000e+00
1.34000000e+00 1.34000000e+00 1.38000000e+00 1.59000000e+00
2.00000000e+00 2.90000000e+00 3.30000000e+00 3.80000000e+00
4.50000000e+00 5.00000000e+00 5.30000000e+00 5.50000000e+00
5.60000000e+00 5.60000000e+00 5.70000000e+00 5.70000000e+00
5.70000000e+00 5.70000000e+00 5.80000000e+00 6.30000000e+00
7.20000000e+00 8.10000000e+00 8.30000000e+00 8.30000000e+00
8.10000000e+00 8.00000000e+00 8.80000000e+00 1.00000000e+01
1.01000000e+01 9.20000000e+00 8.60000000e+00 8.50000000e+00
9.40000000e+00 1.14000000e+01 1.48000000e+01 1.90000000e+01
4.00000000e+01 8.90000000e+01 1.34000000e+02 2.20000000e+02
1.93000000e+02 1.22000000e+02 9.60000000e+01 8.10000000e+01
7.50000000e+01 7.50000000e+01 9.70000000e+01 1.67000000e+02
3.15000000e+02 1.69300000e+03 1.87400000e+03 1.87400000e+03
1.87400000e+03 5.91000000e+02 2.08000000e+02 1.34000000e+02
1.16000000e+02 1.13000000e+02 1.56000000e+02]
SP
MV
[ 45.6 49. 53. 55.6 58.4 62.5 64.7 66.9 69.3 71.3
73.7 75.7 76.7 77.1 77.5 77.5 77.5 77.5 77.1 76.5
75.9 74.7 73.7 71.1 67.3 63.7 60.6 57.8 53.2 48.2
42.9 37.9 34.5 31.7 30.1 28.5 27.2 26. 24.4 23.4
22.2 21.2 20.8 20.2 19.8 19.2 19. 19. 18.8 18.6
18.4 18.2 18.2 18.2 18.2 18.2 18.8 19.4 20.4 21.6
22.4 23.8 25. 26.4 28. 29.3 30.5 31.3 32.7 33.5
34.3 34.9 35.7 36.1 36.1 36.3 36.3 36.3 36.3 36.3
36.3 36.3 36.3 36.3 36.9 37.9 38.5 39.7 40.1 40.5
40.5 40.7 40.9 40.9 41.1 41.1 41.1 41.3 41.7 42.1
42.9 43.9 44.7 45.6 46.6 47.2 48. 48.6 50.2 51.2
52.8 54.2 55.2 56. 57.2 58. 59. 59.6 60.8 62.3
63.5 64.7 66.3 67.7 68.9 70.7 72.1 73.1 74.5 75.9
77.3 78.8 80.8 83.4 85.4 87.6 89.8 91.4 93.4 94.2
95.1 95.5 95.5 95.5 95.5 95.7 96.5 96.7 96.9 97.1
97.1 96.7 95.9 95.1 94.8 94.8 94.8 94.8 95.5 96.3
97.1 98.1 99.1 99.5 99.9 100.1 100.1 100.1 99.9 99.9
100.1 101.9 102.1 103.9 104.9 105.7 106.1 106.3 106.5 106.5
106.5 106.5 106.5 105.9 105.3 104.7 104.7 104.5 104.5 104.5
104.5 104.7 105.9 106.9 109.1 109.7 108.7 107.9 107.3 106.9
106.7 106.7 106.5 105.9 105.1 102.7 87.6 78.8 76.5 76.5
76.5 76.5 76.5 76.5 75.5 74.1 72.1 70.5 68.9 67.5
66.7 65.7 65.1 64.1 63.3 63.1 62.7 62.5 62.5 62.5
62.5 62.5 62.9 64.3 65.9]
GR
GAPI
[ 116. 114. 127. 150. 155. 140. 121. 106. 62. 25. 9. 11.
11. 10. 9. 8. 8. 8. 10. 15. 16. 14. 14. 18.
23. 27. 28. 20. 17. 72. 109. 131. 135. 122. 119. 128.
135. 138. 139. 139. 135. 135. 129. 119. 123. 116. 118. 135.
149. 153. 120. 108. 105. 116. 134. 138. 132. 131. 135. 140.
144. 129. 118. 119. 114. 87. 80. 99. 99. 89. 100. 118.
124. 117. 120. 123. 124. 123. 120. 120. 125. 130. 126. 113.
100. 90. 78. 66. 69. 96. 103. 113. 122. 122. 117. 118.
120. 119. 122. 130. 124. 87. 53. 46. 58. 83. 100. 101.
92. 85. 99. 105. 107. 97. 62. 46. 45. 33. 23. 20.
15. 11. 13. 16. 21. 30. 38. 39. 35. 30. 25. 24.
27. 21. 17. 16. 16. 18. 19. 19. 16. 18. 19. 17.
17. 17. 17. 17. 18. 22. 22. 21. 17. 14. 13. 18.
19. 20. 20. 18. 17. 17. 16. 14. 15. 19. 24. 24.
19. 22. 24. 22. 20. 17. 16. 16. 16. 16. 17. 17.
18. 30. 36. 34. 33. 36. 37. 30. 24. 25. 29. 32.
33. 32. 32. 27. 22. 19. 21. 27. 27. 27. 27. 30.
34. 38. 38. 40. 38. 33. 27. 27. 27. 23. 22. 25.
31. 33. 35. 5. 0. 0. 0. 0. 0. 0. 0. 0.
0. 0. 0. 0. 0. 0. 0.]
In [36]: import matplotlib.pyplot as plt
In [37]: %matplotlib inline
In [38]: plt.plot(las.index, las["GR"])
Out[38]: [<matplotlib.lines.Line2D at 0xb9dc1d0>]