petropt — The Python Library for Petroleum Engineering

Petroleum engineering correlations for Python. MIT licensed.

Online Calculators · Documentation

⚠️ Version notice — do not use pre-1.0.0 releases. Every version before 1.0.0 has been withdrawn and superseded by the current release line. Install only 1.0.0 or later — pip install "petropt>=1.0.0". Any copy of an older version obtained from a mirror, cache, or third-party listing should be discarded.

Install

pip install petropt

Quick Start

import petropt
import numpy as np

# Load a bundled production dataset
df = petropt.datasets.load_sample_production()

# PVT: Standing bubble point pressure
pb = petropt.correlations.standing_bubble_point(api=35, gas_sg=0.65, temp=200)

# Decline: Arps hyperbolic forecast
t = np.arange(0, 60)
q = petropt.correlations.arps_decline(qi=1000, di=0.05, b=0.5, t=t)

# Volumetrics: STOIIP estimate
ooip = petropt.correlations.stoiip(area=640, thickness=50, porosity=0.20, sw=0.30, bo=1.25)

# Petrophysics: water saturation from resistivity
sw = petropt.petrophysics.archie_sw(rt=20.0, phi=0.20, rw=0.05)

# Well logs: read a LAS file
logs = petropt.io.read_las("well.las")

What's Inside

Correlations

• PVT — Standing bubble point / Rs / Bo, Dranchuk Z-factor
• Decline — Arps (exponential, hyperbolic, harmonic)
• Volumetrics — STOIIP, GIIP, recovery factor
• Material balance — gas P/Z

Petrophysics

• Vshale — linear, Larionov (Tertiary / older), Clavier
• Porosity — density
• Water saturation — Archie

I/O

• LAS files — read well logs into pandas DataFrames (wraps lasio)

Datasets

• Sample production — bundled 2-well, 12-month dataset for demos

Links

• tools.petropt.com — petroleum engineering web calculators by Groundwork Analytics
• tools.petropt.com/docs/ — documentation

Citation

Shirangi, M.G. (2026). petropt: The Python Library for Petroleum Engineering.
https://pypi.org/project/petropt/

License

MIT — see LICENSE for details.