Well Log Analysis

Dependencies

pip install lasio pandas matplotlib numpy

Capabilities

1. Read LAS Files

import lasio

# Read LAS file
log = lasio.read('well_log.las')

# Access well metadata
print(f"Well: {log.well['WELL'].value}")
print(f"Field: {log.well['FLD'].value if 'FLD' in log.well else 'N/A'}")
print(f"Company: {log.well['COMP'].value if 'COMP' in log.well else 'N/A'}")

# Access curve data
print(f"Curves: {[curve.mnemonic for curve in log.curves]}")
print(f"Depth range: {log.index_min} to {log.index_max} {log.index_unit}")

2. Export to DataFrame

import lasio
import pandas as pd

log = lasio.read('well_log.las')

# Convert to pandas DataFrame
df = log.df()

# Access specific curves
depth = df.index
gamma_ray = df['GR']
density = df['RHOB']
neutron = df['NPHI']

print(df.head())

3. Access Header Metadata

import lasio

log = lasio.read('well_log.las')

# Version section
print(f"Version: {log.version['VERS'].value}")
print(f"Wrap: {log.version['WRAP'].value}")

# Well section
print(log.well)

# Parameters section
print(log.params)

# Other section
for item in log.other:
    print(item)

# Curves section
for curve in log.curves:
    print(f"{curve.mnemonic}: {curve.unit} - {curve.descr}")

4. Petrophysical Calculations

import lasio
import numpy as np

log = lasio.read('well_log.las')
df = log.df()

# Calculate porosity from density
# Phi = (matrix - bulk) / (matrix - fluid)
matrix_density = 2.65  # g/cc (sandstone)
fluid_density = 1.0    # g/cc (water)

bulk_density = df['RHOB'].values
porosity = (matrix_density - bulk_density) / (matrix_density - fluid_density)
porosity = np.clip(porosity, 0, 0.5)  # Clamp to reasonable range

print(f"Average porosity: {porosity.mean():.2%}")

# Calculate water saturation (Archie equation)
# Sw = ((a * Rw) / (Phi^m * Rt))^(1/n)
a = 1.0
m = 2.0
n = 2.0
Rw = 0.1  # ohm-m (formation water resistivity)

phi = porosity
Rt = df['RT'].values  # true resistivity

Sw = ((a * Rw) / (phi**m * Rt))**(1/n)
Sw = np.clip(Sw, 0, 1)

print(f"Average water saturation: {Sw.mean():.2%}")

# Calculate shale volume from gamma ray
GR = df['GR'].values
GR_min = GR.min()
GR_max = GR.max()

Vsh = (GR - GR_min) / (GR_max - GR_min)
Vsh = np.clip(Vsh, 0, 1)

print(f"Average shale volume: {Vsh.mean():.2%}")

5. Visualize Well Logs

import lasio
import matplotlib.pyplot as plt

log = lasio.read('well_log.las')
df = log.df()

fig, axes = plt.subplots(1, 4, figsize=(15, 10), sharey=True)

# Gamma Ray
axes[0].plot(df['GR'], df.index)
axes[0].set_xlabel('GR (API)')
axes[0].set_ylabel('Depth (m)')
axes[0].invert_yaxis()
axes[0].grid(True, alpha=0.3)

# Resistivity
axes[1].semilogx(df['RT'], df.index)
axes[1].set_xlabel('RT (ohm-m)')
axes[1].grid(True, alpha=0.3)

# Density-Neutron
axes[2].plot(df['RHOB'], df.index, label='RHOB')
axes[2].set_xlabel('RHOB (g/cc)')
axes[2].grid(True, alpha=0.3)

# Caliper
axes[3].plot(df['CALI'], df.index)
axes[3].set_xlabel('CALI (in)')
axes[3].grid(True, alpha=0.3)

plt.tight_layout()
plt.savefig('well_logs.png', dpi=150)

6. Export Data

import lasio

log = lasio.read('well_log.las')

# Export to CSV
log.to_csv('output.csv')

# Export to Excel
log.to_excel('output.xlsx')

# Write new LAS file
log.write('modified.las')

7. Handle Non-Standard Files

import lasio

# Read malformed LAS files
log = lasio.read('problematic.las', ignore_header_errors=True)

# Handle encoding issues
log = lasio.read('file.las', encoding='latin-1')

# Read only headers (fast for large files)
log = lasio.read('large.las', read_policy=[])

# Custom null policy
log = lasio.read('file.las', null_policy='common')

8. Create LAS File from Scratch

import lasio
import numpy as np
from lasio import LASFile, CurveItem, HeaderItem

# Create new LAS file
las = LASFile()

# Add well metadata
las.well.append(HeaderItem('WELL', value='Well-001'))
las.well.append(HeaderItem('FLD', value='Test Field'))
las.well.append(HeaderItem('LOC', value='North Sea'))
las.well.append(HeaderItem('SRVC', value='Acme Logging'))

# Add curves
depths = np.arange(1000, 2000, 0.5)
gr = np.random.uniform(20, 150, len(depths))
rhob = np.random.uniform(2.2, 2.7, len(depths))

las.add_curve('DEPT', depths, unit='m')
las.add_curve('GR', gr, unit='API', descr='Gamma Ray')
las.add_curve('RHOB', rhob, unit='g/cc', descr='Bulk Density')

# Write file
las.write('new_well.las')

Workflow Integration

Used by:

• oil-gas-pipelines/exploration - Formation evaluation, log correlation
• oil-gas-pipelines/drilling - Real-time LWD interpretation
• oil-gas-pipelines/reservoir-production - Reservoir characterization

Common Issues

Missing curves

# Check if curve exists
if 'GR' in log.keys():
    gr = log['GR']