petres 0.1.0

Petres: lightweight Python library for reservoir grid modeling and visualization

Lightweight Python Library for Reservoir Grid Modeling and Simulation

Documentation • Installation • Quick Start

Introduction

Petres is a lightweight, open-source Python library for reservoir grid modeling, providing a fully programmatic approach to constructing Corner-Point grid models.

For complete documentation, see the Petres documentation.

Stability Notice
Petres is currently in early development. The API is not yet stable and may change without notice.

Why Petres?

• Open Access: Free alternative for engineers and students without access to expensive commercial softwares.

• Scriptable Modeling: Avoid UI complexity and work with code-driven workflows.

• Fully Customizable: Integrate your own code alongside built-in methods.

• AI Integration: Use the Python ecosystem to apply AI and Machine Learning techniques.

Features

• Grid Generation: Construct Corner-Point, Rectilinear, and Regular grids.
  Apply boundary polygons to deactivate cells outside the target region.

• Structural Modeling: Generate horizon and zone surfaces from well tops to support grid construction.

• Property Modeling: Assign petrophysical properties to grid cells using stochastic or deterministic methods, derived attributes, or interpolation from well data.

• Import & Export Grids: Handle Eclipse grids (SLB reservoir simulator) using the .GRDECL file format. Visualize and export modeled Corner-Point grids.

• Visualization: Interactive 2D and 3D rendering of Corner-Point grids, structural zones, horizons, and spatial property distributions.

Getting Started

To get started with Petres, refer to the Installation Guide and the Quickstart Tutorial.

Technical Architecture

Component	Implementation
Grid Operations	High-performance, vectorized array computations using NumPy
2D Plotting	Visualization via Matplotlib
3D Visualization	Interactive rendering and mesh handling via PyVista
Kriging Interpolation	Ordinary and Universal Kriging via PyKrige
RBF Interpolation	Multi-dimensional Radial Basis Function interpolation via SciPy
IDW Interpolation	In-house implementation of Inverse Distance Weighting

Contact

For questions or collaboration, please contact [e-mail] or connect via LinkedIn.