PetroPy - Petrophysical Analysis
Quick Reference
import petropy as pp
# Load and inspect
log = pp.Log('well.las')
print(log.keys()) # Available curves
depth, gr = log['DEPT'], log['GR']
# Calculate properties
log.shale_volume(gr_curve='GR', gr_clean=20, gr_shale=120)
log.formation_porosity(rhob_curve='RHOB', rhob_matrix=2.65, rhob_fluid=1.0)
log.water_saturation(method='archie', rt_curve='RT', porosity_curve='PHIT', rw=0.05)
log.permeability(method='timur', porosity_curve='PHIT', sw_curve='SW')
Key Classes
| Class | Purpose |
|---|
Log | Main well log container, extends lasio.LASFile |
electrofacies | Facies classification utilities |
Formations | Zone/formation management |
Essential Operations
Shale Volume (Vsh)
log.shale_volume(
gr_curve='GR',
gr_clean=20, # GR of clean sand (API)
gr_shale=120, # GR of shale (API)
method='linear' # or 'larionov_young', 'larionov_old', 'clavier'
)
vsh = log['VSH']
Porosity
# Density porosity with shale correction
log.formation_porosity(
rhob_curve='RHOB',
rhob_matrix=2.65, # g/cc (sandstone)
rhob_fluid=1.0, # g/cc (water)
rhob_shale=2.45, # optional shale correction
vsh_curve='VSH' # requires VSH curve
)
phi = log['PHIT']
Water Saturation
log.water_saturation(
method='archie', # or 'simandoux', 'indonesia'
rt_curve='RT',
porosity_curve='PHIT',
rw=0.05, # Formation water resistivity (ohm-m)
a=1.0, m=2.0, n=2.0 # Archie parameters
)
sw = log['SW']
Permeability
log.permeability(
method='timur', # or 'coates'
porosity_curve='PHIT',
sw_curve='SW'
)
perm = log['PERM'] # Result in mD
Pay Flag and Net Pay
import numpy as np
pay = (log['VSH'] < 0.4) & (log['PHIT'] > 0.08) & (log['SW'] < 0.6)
log['PAY'] = pay.astype(float)
net_pay = np.sum(pay) * log.step
Export Results
log.to_las('well_interpreted.las')
# Or to CSV
import pandas as pd
df = pd.DataFrame({'DEPT': log['DEPT'], 'VSH': log['VSH'], 'PHIT': log['PHIT'], 'SW': log['SW']})
df.to_csv('results.csv', index=False)
Archie Parameters
| Parameter | Symbol | Range | Description |
|---|
| Tortuosity | a | 0.6-1.0 | Formation factor coefficient |
| Cementation | m | 1.8-2.2 | Pore geometry factor |
| Saturation exp | n | 1.8-2.2 | Wettability factor |
Matrix Properties
| Lithology | rhob (g/cc) | nphi (v/v) | DT (us/ft) |
|---|
| Sandstone | 2.65 | -0.02 | 55.5 |
| Limestone | 2.71 | 0.00 | 47.5 |
| Dolomite | 2.87 | 0.02 | 43.5 |
| Shale | 2.45 | 0.30-0.45 | 70-130 |
When to Use vs Alternatives
| Tool | Best For |
|---|
| petropy | Automated formation evaluation, standard petrophysical workflows |
| welly | Well data management, curve processing, multi-well projects |
| custom calculations | Non-standard equations, full control over methodology |
Use petropy when you need a streamlined formation evaluation pipeline: Vsh, porosity, Sw, permeability, and pay flags with standard methods (Archie, Simandoux, Timur). It extends lasio so file I/O is built in.
Use welly instead when your focus is data management, curve QC, and multi-well projects rather than petrophysical calculations.
Use custom calculations instead when you need non-standard saturation models, proprietary equations, or more control over the computation steps than petropy's built-in methods provide.
Common Workflows
Complete formation evaluation from raw logs
- [ ] Load well with `pp.Log('well.las')`, verify required curves exist
- [ ] Pick clean sand and shale GR values from histogram or crossplot
- [ ] Compute shale volume: `log.shale_volume()`
- [ ] Compute porosity: `log.formation_porosity()` with matrix parameters
- [ ] Determine Rw from water zone or catalog; set Archie parameters
- [ ] Compute water saturation: `log.water_saturation()`
- [ ] Compute permeability: `log.permeability()`
- [ ] Apply pay flag cutoffs (Vsh, porosity, Sw) and calculate net pay
- [ ] Export interpreted log to LAS or CSV
References
Scripts
