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Python library for petroleum engineering — Standing PVT, Dranchuk Z-factor, Arps decline, volumetrics, gas P/Z, Archie water saturation, density porosity, Vshale, LAS log I/O. MIT licensed.

Project description

petropt — The Python Library for Petroleum Engineering

PyPI License: MIT Python 3.10+

Petroleum engineering correlations for Python. MIT licensed.

Online Calculators · Documentation

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

Citation

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

License

MIT — see LICENSE for details.

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