petropt 0.3.1

Open-source Python library for petroleum & reservoir engineering — PVT, IPR, decline, multiphase flow, material balance, petrophysics (Archie/Simandoux/Timur), rate transient analysis (Blasingame / Agarwal-Gardner / NPI), drilling (API 5C3 collapse, Barlow burst), production (Turner/Coleman/Katz/Gilbert), economics, well log I/O. MIT licensed.

petropt — The Python Library for Petroleum Engineering

Free, open-source petroleum engineering tools for Python. MIT licensed — use anywhere, no restrictions.

Online Calculators · Documentation · Enterprise Support

Install

pip install petropt

Quick Start

import petropt

# Load a 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
import numpy as np
t = np.arange(0, 60)
q = petropt.correlations.arps_decline(qi=1000, di=0.05, b=0.5, t=t)

# IPR: Vogel inflow performance
ipr = petropt.correlations.vogel_ipr(qmax=1500, pr=3500, num_points=50)

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

# RTA: Blasingame variables for type-curve matching
bg = petropt.rta.blasingame_variables(t, q, cum, pwf, pi=3000)

# Economics: NPV of a well
npv = petropt.economics.npv(cash_flows=[-500000, 80000, 70000, 60000], discount_rate=0.10, periods_per_year=1)

What's Inside

Correlations (50+ functions)

• PVT — Standing bubble point/Rs/Bo, Beggs-Robinson viscosity, Sutton & Piper pseudocritical, Hall-Yarborough & Dranchuk Z-factor, Lee-Gonzalez-Eakin gas viscosity, gas Bg/density/compressibility
• Water PVT — McCain Bw/viscosity/density, Osif compressibility, gas solubility
• IPR — Vogel, Fetkovich, Rawlins-Schellhardt (C&n), PI-based, composite (Vogel + PI)
• Decline Curves — Arps (exponential, hyperbolic, harmonic), cumulative production, EUR
• Multiphase Flow — Beggs-Brill pressure gradient (all flow patterns, any inclination)
• Hydraulics — Darcy-Weisbach with Churchill friction factor
• Relative Permeability — Corey, Brooks-Corey, LET models (oil/water/gas)
• Material Balance — Gas P/Z, Havlena-Odeh, OOIP estimation, drive indices
• Volumetrics — STOIIP, GIIP, drainage radius, recovery factor

Petrophysics

• Vshale — linear, Larionov (Tertiary / older), Clavier
• Porosity — density, sonic (Wyllie / Raymer-Hunt-Gardner), neutron-density, effective
• Water saturation — Archie, Simandoux, Indonesian (Poupon-Leveaux)
• Permeability — Timur, Coates (NMR)
• Pay — cutoff-based net pay, NTG, pay-weighted averages, hydrocarbon pore thickness

Rate Transient Analysis (RTA)

• Transforms — pressure-normalized rate, material balance time
• Type curves — Blasingame, Agarwal-Gardner, NPI variables
• Flowing material balance — contacted OOIP/OGIP from producing-well data
• Linear flow — sqrt(t) analysis, sqrt(k)·xf extraction from fracture wells

Drilling

• Well control — hydrostatic, ECD, MAASP, kill mud weight, ICP/FCP (Driller's / Wait-and-Weight)
• Hydraulics — annular velocity, nozzle TFA, bit pressure drop
• Tubulars — Barlow burst with API 0.875 factor, full API 5C3 collapse (yield / plastic / transition / elastic regimes)

Production Engineering

• Liquid loading — Turner (1969) and Coleman (1991) critical droplet-lift velocities
• Flow assurance — Katz hydrate formation temperature, Hammerschmidt methanol/MEG/ethanol inhibitor dosing
• Piping — API RP 14E erosional velocity
• Choke flow — Gilbert (1954) critical-flow rate correlation

Economics

• NPV, IRR, payback period, oil & gas monthly cashflow (WI/NRI/severance/opex/capex)

I/O

• LAS files — Read well logs to pandas DataFrame (wraps lasio)
• Production CSV — Auto-detect date/oil/gas/water columns from any naming convention

Datasets

• Petrobras 3W — Labeled well events for fault detection (CC BY 4.0)
• NPD Wellbore — Norwegian Continental Shelf well metadata (NLOD)
• Sample Production — Bundled 2-well, 12-month dataset for demos

Notebooks

• student_intro.ipynb — Your first petroleum dataset in Python
• decline_analysis.ipynb — Arps decline curve analysis tutorial

Why petropt?

	petropt	pyResToolbox	DIY scripts
License	MIT (use anywhere)	GPL (copyleft)	N/A
Datasets	Built-in (3W, NPD, samples)	No	No
LAS reader	Yes	No	Manual
Student notebooks	Yes	No	No
Web calculators	tools.petropt.com	No	No
Economics	NPV, IRR, cashflow	No	Manual
Need more?	Enterprise support, custom correlations, training — by Groundwork Analytics	—	—

petropt is MIT licensed — use it freely in commercial projects, consulting, research, and AI applications. No copyleft restrictions.

History

This repository was first initiated 8 years ago, in July 2018 (see master branch for the original placeholder). Most of the code was developed and used privately over the years. We consolidated the collected work and released the open-source version on April 24, 2026.

For AI Builders

pip install petro-mcp  # MCP server that wraps petropt for Claude/ChatGPT/LLMs

Links

• tools.petropt.com — Free online PE calculators
• tools.petropt.com/docs/ — Documentation
• petropt.com/enterprise — Enterprise support, custom correlations, training (Groundwork Analytics)
• github.com/petropt/petropt — Source, issues, releases

Citation

If you use petropt in academic work, please cite:

Shirangi, M.G. (2026). petropt: The Python Library for Petroleum Engineering.
https://github.com/petropt/petropt

License

MIT — see LICENSE for details.