Basic example¶
>>> import lasio
You can use lasio.read() to open any file or URL. For this tutorial I
will use the lasio.examples module to load a LAS file which is bundled
with lasio:
>>> import lasio.examples
>>> las = lasio.examples.open("1001178549.las")
The lasio.read() function returns a lasio.LASFile object. Each
of the standard LAS sections can be accessed as an attribute:
>>> las.version
[HeaderItem(mnemonic="VERS", unit=, value="2.0", descr="CWLS Log ASCII Standard -V...),
HeaderItem(mnemonic="WRAP", unit=, value="YES", descr="Multiple lines per depth ...)]
Each LAS section is represented as a lasio.SectionItems object. The
others, for LAS 2.0 files, are present as las.well, las.curves, and
las.params; the ~O section is a string accessible at las.other.
You can also see the sections printed as an easier-to-read table:
>>> print(las.curves)
Mnemonic Unit Value Description
-------- ---- ----- -----------
DEPT FT 0 1 0 0 1 DEPTH
GSGR API 31 310 0 0 2 GAMMA RAY
GSTK API 31 797 0 0 3 ????????
GST API 99 999 99 0 4 ????????
GSK PERCNT 31 721 1 0 5 ????????
GSTH PPM 31 790 0 0 6 THORIUM
GSUR PPM 31 792 0 0 7 URANIUM
NCNPL PERCNT 42 890 1 0 8 NEUTRON POROSITY (LIMESTONE)
DLDPL PERCNT 43 890 10 0 9 DENSITY POROSITY (LIMESTONE)
DLDC GM/CC 43 356 0 0 10 DENSITY CORRECTION
DLPE B/E 43 358 0 0 11 PHOTO-ELECTRIC EFFECT
DLDN GM/CC 43 350 0 0 12 BULK DENSITY
DLCL INCHES 43 280 0 0 13 CALIPER
DLTN LBS 43 635 0 0 14 ????????
IDGR API 7 310 0 0 15 GAMMA RAY
ACCL1 INCHES 60 280 1 0 16 DENSITY CALIPER
ACCL2 INCHES 60 280 2 0 17 NEUTRON CALIPER
ACTC US/FT 60 520 0 0 18 SONIC INTERVAL TRANSIT TIME (COMPENSATED)
ACAPL PERCNT 60 890 20 0 19 POROSITY
IDIM OHMM 7 120 44 0 20 MEDIUM INDUCTION
IDID OHMM 7 120 46 0 21 DEEP INDUCTION
IDIDC MMHOS 7 110 46 0 22 INDUCTION (CONDUCTIVITY UNITS)
IDL3 OHMM 7 220 3 0 23 FOCUSSED RESISTIVITY
IDTN LBS 7 635 0 0 24 ????????
IDSP MVOLT 7 10 0 0 25 SPONTANEOUS POTENTIAL
MEL1 OHMM 15 250 2 0 26 MICRO INVERSE 1"
ME OHMM 15 252 2 0 27 MICRO NORMAL 2"
The data is present as a numpy.ndarray at las.data:
>>> las.data.shape
(5, 27)
>>> las.data
array([[1.7835000e+03, nan, nan, nan,
nan, nan, nan, nan,
nan, nan, nan, nan,
nan, nan, 5.0646500e+01, 8.3871000e+00,
8.4396000e+00, 5.5100000e+01, 5.6900000e-02, 5.6000000e+02,
1.7500000e+02, 5.0000000e-02, 4.5330000e-01, 1.8930420e+03,
9.2605000e+01, nan, nan],
[1.7837500e+03, nan, nan, nan,
nan, nan, nan, nan,
nan, nan, nan, nan,
nan, nan, 4.9676700e+01, 8.3951000e+00,
8.4460000e+00, 5.4355500e+01, 5.9000000e-02, 5.6000000e+02,
1.7500000e+02, 5.0000000e-02, 4.5340000e-01, 1.8523320e+03,
9.2778000e+01, nan, nan],
[1.7840000e+03, nan, nan, nan,
nan, nan, nan, nan,
nan, nan, nan, nan,
nan, nan, 4.8631300e+01, 8.4052000e+00,
8.4460000e+00, 5.4444400e+01, 5.8100000e-02, 5.6000000e+02,
1.7500000e+02, 5.0000000e-02, 4.5370000e-01, 1.8319766e+03,
9.2948200e+01, nan, nan],
[1.7842500e+03, nan, nan, nan,
nan, nan, nan, nan,
nan, nan, nan, nan,
nan, nan, 4.7771700e+01, 8.4173000e+00,
8.4438000e+00, 5.5311100e+01, 5.7700000e-02, 5.6000000e+02,
1.7500000e+02, 5.0000000e-02, 4.5380000e-01, 1.8319766e+03,
9.3110300e+01, nan, nan],
[1.7845000e+03, nan, nan, nan,
nan, nan, nan, nan,
nan, nan, nan, nan,
nan, nan, 4.8114900e+01, 8.4253000e+00,
8.4460000e+00, 5.6322200e+01, 5.8500000e-02, 5.6000000e+02,
1.7500000e+02, 5.0000000e-02, 4.5390000e-01, 1.8116211e+03,
9.3267100e+01, nan, nan]])
Although it might be easier for you to iterate over the curves:
>>> for curve in las.curves:
... print(curve.mnemonic + ": " + str(curve.data))
DEPT: [1783.5 1783.75 1784. 1784.25 1784.5 ]
GSGR: [nan nan nan nan nan]
GSTK: [nan nan nan nan nan]
GST: [nan nan nan nan nan]
GSK: [nan nan nan nan nan]
GSTH: [nan nan nan nan nan]
GSUR: [nan nan nan nan nan]
NCNPL: [nan nan nan nan nan]
DLDPL: [nan nan nan nan nan]
DLDC: [nan nan nan nan nan]
DLPE: [nan nan nan nan nan]
DLDN: [nan nan nan nan nan]
DLCL: [nan nan nan nan nan]
DLTN: [nan nan nan nan nan]
IDGR: [50.6465 49.6767 48.6313 47.7717 48.1149]
ACCL1: [8.3871 8.3951 8.4052 8.4173 8.4253]
ACCL2: [8.4396 8.446 8.446 8.4438 8.446 ]
ACTC: [55.1 54.3555 54.4444 55.3111 56.3222]
ACAPL: [0.0569 0.059 0.0581 0.0577 0.0585]
IDIM: [560. 560. 560. 560. 560.]
IDID: [175. 175. 175. 175. 175.]
IDIDC: [0.05 0.05 0.05 0.05 0.05]
IDL3: [0.4533 0.4534 0.4537 0.4538 0.4539]
IDTN: [1893.042 1852.332 1831.9766 1831.9766 1811.6211]
IDSP: [92.605 92.778 92.9482 93.1103 93.2671]
MEL1: [nan nan nan nan nan]
ME: [nan nan nan nan nan]
The first curve in the LAS file – usually the depth – is present as
las.index, and curves are also accessible from the LASFile object as
items. For example:
>>> las.index
array([1783.5 , 1783.75, 1784. , 1784.25, 1784.5 ])
>>> las["IDTN"]
array([1893.042 , 1852.332 , 1831.9766, 1831.9766, 1811.6211])