A reader for Canadian Well Logging Society LAS (Log ASCII Standard) files.
Project description
The las module implements a reader for LAS (Log ASCII Standard) well log files (LAS 2.0). For more information about this format, see the Canadian Well Logging Society web page (https://www.cwls.org/products/).
Example 1
The following file, “example1.las”, is from “LAS Version 2.0: A Digital Standard for Logs; Updated January 2014”:
~VERSION INFORMATION VERS. 2.0 : CWLS LOG ASCII STANDARD -VERSION 2.0 WRAP. NO : ONE LINE PER DEPTH STEP ~WELL INFORMATION #MNEM.UNIT DATA DESCRIPTION #----- ----- ---------- ------------------------- STRT .M 1670.0000 :START DEPTH STOP .M 1669.7500 :STOP DEPTH STEP .M -0.1250 :STEP NULL . -999.25 :NULL VALUE COMP . ANY OIL COMPANY INC. :COMPANY WELL . ANY ET AL 12-34-12-34 :WELL FLD . WILDCAT :FIELD LOC . 12-34-12-34W5M :LOCATION PROV . ALBERTA :PROVINCE SRVC . ANY LOGGING COMPANY INC. :SERVICE COMPANY DATE . 13-DEC-86 :LOG DATE UWI . 100123401234W500 :UNIQUE WELL ID ~CURVE INFORMATION #MNEM.UNIT API CODES CURVE DESCRIPTION #------------------ ------------ ------------------------- DEPT .M : 1 DEPTH DT .US/M 60 520 32 00 : 2 SONIC TRANSIT TIME RHOB .K/M3 45 350 01 00 : 3 BULK DENSITY NPHI .V/V 42 890 00 00 : 4 NEUTRON POROSITY SFLU .OHMM 07 220 04 00 : 5 SHALLOW RESISTIVITY SFLA .OHMM 07 222 01 00 : 6 SHALLOW RESISTIVITY ILM .OHMM 07 120 44 00 : 7 MEDIUM RESISTIVITY ILD .OHMM 07 120 46 00 : 8 DEEP RESISTIVITY ~PARAMETER INFORMATION #MNEM.UNIT VALUE DESCRIPTION #-------------- ---------------- ----------------------------------------------- MUD . GEL CHEM : MUD TYPE BHT .DEGC 35.5000 : BOTTOM HOLE TEMPERATURE BS .MM 200.0000 : BIT SIZE FD .K/M3 1000.0000 : FLUID DENSITY MATR . SAND : NEUTRON MATRIX MDEN . 2710.0000 : LOGGING MATRIX DENSITY RMF .OHMM 0.2160 : MUD FILTRATE RESISTIVITY DFD .K/M3 1525.0000 : DRILL FLUID DENSITY ~OTHER Note: The logging tools became stuck at 625 metres causing the data between 625 metres and 615 metres to be invalid. ~A DEPTH DT RHOB NPHI SFLU SFLA ILM ILD 1670.000 123.450 2550.000 0.450 123.450 123.450 110.200 105.600 1669.875 123.450 2550.000 0.450 123.450 123.450 110.200 105.600 1669.750 123.450 2550.000 0.450 123.450 123.450 110.200 105.600
Sample python session:
>>> import las >>> log = las.LASReader('example1.las') >>> log.start 1670.0 >>> log.stop 1669.75 >>> log.step -0.125 >>> log.null -999.25 >>> log.well.COMP LASItem(name='COMP', units='', data='ANY OIL COMPANY INC.', descr='COMPANY') >>> log.well.COMP.value 'ANY OIL COMPANY INC.' >>> log.well.FLD.value 'WILDCAT' >>> print(log.other) Note: The logging tools became stuck at 625 metres causing the data between 625 metres and 615 metres to be invalid.
The log data is stored as a numpy structured array in log.data:
>>> log.data array([(1670.0, 123.45, 2550.0, 0.45, 123.45, 123.45, 110.2, 105.6), (1669.875, 123.45, 2550.0, 0.45, 123.45, 123.45, 110.2, 105.6), (1669.75, 123.45, 2550.0, 0.45, 123.45, 123.45, 110.2, 105.6)], dtype=[('DEPT', '<f8'), ('DT', '<f8'), ('RHOB', '<f8'), ('NPHI', '<f8'), ('SFLU', '<f8'), ('SFLA', '<f8'), ('ILM', '<f8'), ('ILD', '<f8')]) >>> log.data['RHOB'] array([ 2550., 2550., 2550.]) >>> log.data[0] (1670.0, 123.45, 2550.0, 0.45, 123.45, 123.45, 110.2, 105.6)
The data is also available as a two-dimensional numpy array. First we’ll adjust numpy’s output format. This is not necessary, but it makes the values easier to read:
>>> import numpy as np >>> np.set_printoptions(precision=4)
The two-dimensional view of the data is called data2d:
>>> log.data2d array([[ 1.6700e+03, 1.2345e+02, 2.5500e+03, 4.5000e-01, 1.2345e+02, 1.2345e+02, 1.1020e+02, 1.0560e+02], [ 1.6699e+03, 1.2345e+02, 2.5500e+03, 4.5000e-01, 1.2345e+02, 1.2345e+02, 1.1020e+02, 1.0560e+02], [ 1.6698e+03, 1.2345e+02, 2.5500e+03, 4.5000e-01, 1.2345e+02, 1.2345e+02, 1.1020e+02, 1.0560e+02]]) >>> log.data2d.shape (3, 8)
Example 2
The next example reads a file from the Kansas Geological Survey and makes a plot of the gamma ray data versus depth using matplotlib.
First, the imports:
>>> import numpy as np >>> import matplotlib.pyplot as plt >>> import las >>> import io >>> try: ... from urllib.request import urlopen ... except ImportError: ... from urllib import urlopen ...
Next, read the file:
>>> url = "http://www.kgs.ku.edu/software/DEWL/HELP/pc_read/Shamar-1.las" >>> f = io.StringIO(urlopen(url).read().decode('iso-8859-1')) >>> log = las.LASReader(f, null_subs=np.nan)
Finally, make the plot using matplotlib:
>>> plt.figure(figsize=(9, 5)) >>> plt.plot(log.data['DEPT'], log.data['GR']) >>> plt.xlabel(log.curves.DEPT.descr + " (%s)" % log.curves.DEPT.units) >>> plt.ylabel(log.curves.GR.descr + " (%s)" % log.curves.GR.units) >>> plt.title(log.well.WELL.data + ', ' + log.well.DATE.data) >>> plt.grid() >>> plt.show()
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