EXERCISE — well log calculations

This notebook looks at reading a well log, performing some petrophysical calculations.

First, the usual preliminaries.


In [1]:
import numpy as np
import matplotlib.pyplot as plt
from welly import Well

% matplotlib inline

In [2]:
ls


Build_and_test_environment.ipynb
Index.ipynb*
LICENSE
Part1a_Fundamentals_of_Programming.ipynb
Part1b_Intro_to_scientific_computing.ipynb*
Part2a__Well_log_calculations.ipynb
Part2b__Synthetic_seismogram.ipynb
Part2c__Seismic_arrays.ipynb*
README.md
data/
environment.yml
scripts/

In [4]:
data_dir = 'data/'
fname = 'L30.las'
file = data_dir + '/' + fname

Q: from welly's Well module, use the from_las function to create a well object from the las file


In [ ]:
# your code here

In [6]:
# it should looks like this
well


Out[6]:
PENOBSCOT L-30
tdNone
crsCRS({})
countyNOVA SCOTIA SHELF
location44deg 09' 43.558"N LAT|60deg 04' 0
dataCALD, CALS, DRHO, DT, GRD, GRS, ILD, ILM, LL8, NPHILS, NPHISS, RHOB, SP

In [9]:
pslow = well.data['DT']
rhob = well.data['RHOB']
gr = well.data['GRD']

Q. Write a function that converts slowness (us/m) into velocity (m/s) your code here


In [ ]:
# your code here

Q. Create an acoustic impedance log


In [ ]:
# your code here

Q. Using a Sand-Shale cutoff for Gamma-Ray of 60 API, what is the Gross sand thickness from 2200 - 3000 m?


In [ ]:
# your code here

Q. Use the porosity log, NPHISS to determine the average value of porosity for a) sands, b) shales, c) carbonates.


In [ ]:
# your code here

Q. Explore the data distributions based on the actual lithologies based in


In [ ]:
lithfile = 'data/L30_samples.txt'