Does this skill support 3D spatial modeling?

Yes, the skill includes functions like kb3d for 3D kriging and sgsim for 3D sequential Gaussian simulation to handle volumetric spatial data.

What is GeostatsPy used for in Claude Code?

It is used for advanced spatial data analysis, specifically for tasks like kriging interpolation, variogram modeling, and sequential Gaussian simulation (SGSIM) in geoscience workflows.

Is GeostatsPy compatible with original GSLIB programs?

Yes, GeostatsPy is a Python port of the original GSLIB (Geostatistical Software Library) programs, maintaining compatibility with GSLIB parameter conventions and workflows.

Why choose GeostatsPy over generic libraries like scikit-learn?

GeostatsPy is purpose-built for geosciences, offering specific features like declustering, normal score transforms, and GSLIB-compatible simulation engines not found in general ML libraries.

GeostatsPy Geostatistical Analysis

Name: GeostatsPy Geostatistical Analysis
Author: SteadfastAsArt

bySteadfastAsArt

•

Ciencia de Datos y ML

Performs GSLIB-inspired geostatistical analysis including variogram modeling, kriging interpolation, and spatial simulations.

GeostatsPy is a specialized Claude Code skill designed for geoscientists and data scientists working with spatial data. It provides a comprehensive suite of tools for calculating experimental variograms, fitting models, performing simple and ordinary kriging, and running sequential Gaussian simulations (SGSIM). By bringing robust GSLIB workflows into the Python environment, it enables advanced spatial estimation, declustering, and uncertainty quantification directly within AI-assisted coding sessions, making it ideal for reservoir characterization and environmental modeling.

Características Principales

01Calculate experimental variograms and fit complex variogram models with anisotropy.

02Execute Sequential Gaussian (SGSIM) and Indicator (SISIM) simulations for uncertainty modeling.

0312 GitHub stars

04Apply normal score transforms and back-transformations for Gaussian-based workflows.

05Perform 2D and 3D Simple and Ordinary Kriging for precise spatial interpolation.

06Decluster spatial data using cell-based methods to mitigate sampling bias.

Casos de Uso

01Generating multiple stochastic realizations of geological properties to quantify spatial uncertainty.

02Analyzing spatial continuity and anisotropy in complex environmental or geophysical datasets.

03Estimating mineral or hydrocarbon reserves from sparse well-log and borehole data.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add steadfastasart/geoscience-skills geostatspy

For use in Claude.ai and ChatGPT

Download Skill