🌍 30 AI-powered geoscience skills for Claude Code, Cursor & GitHub Copilot. Seismic, well logs, 3D modelling, inversion, geostatistics, spatial regression, NetCDF, and more.
Read, write, and manipulate SEG-Y seismic data files. Fast C library with Python bindings for trace, header, inline, and crossline access. Use when the agent needs to: (1) Read/inspect SEG-Y files, (2) Extract trace data or headers, (3) Access 3D survey data by inline/crossline, (4) Create new SEG-Y files from arrays…
Simulation and Parameter Estimation in Geophysics. Framework for geophysical forward modeling and inversion. Use when the agent needs to: (1) Run geophysical inversions (DC resistivity, magnetics, gravity, EM), (2) Create forward models for potential fields or electromagnetic methods, (3) Build survey geometries and…
Create, visualize, and analyze lithological and stratigraphic logs for well data. Use when the agent needs to: (1) Create lithology columns from depth intervals, (2) Parse geological descriptions into structured logs, (3) Visualize stratigraphic columns with patterns and colors, (4) Perform well-to-well correlations…
Spatial data gridding and interpolation with a machine-learning style API. Process geographic and Cartesian point data onto regular grids. Use when the agent needs to: (1) Grid scattered spatial data onto regular grids, (2) Interpolate point data using splines, linear, or cubic methods, (3) Process geographic…
Subsurface well data analysis toolkit for loading, processing, and analyzing well logs, projects, and formation tops. Built on lasio with enhanced curve processing. Use when the agent needs to: (1) Load wells from LAS files with metadata, (2) Work with multi-well Projects, (3) Process curves (despike, smooth…
3D geological modelling workflow from spatial data preparation through implicit surface modelling and 3D visualization. Use when building geological models from surface data, boreholes, or GIS inputs.
Geophysical data inversion workflow from data loading through mesh creation, forward modelling, inversion, and result visualization. Use when inverting ERT, magnetics, gravity, or EM survey data.
Rock physics and AVO analysis workflow from well log preparation through elastic property calculation, fluid substitution, AVO modelling, and synthetic seismogram generation. Use when performing rock physics studies or AVO feasibility analysis.
End-to-end seismic interpretation workflow from SEG-Y loading through signal processing, rock physics, and visualization. Use when working with seismic data analysis pipelines.
Complete well log evaluation workflow from LAS/DLIS loading through QC, petrophysical analysis, lithology classification, and visualization. Use when performing formation evaluation from well log data.
N-dimensional labeled arrays for geoscience data. Read/write NetCDF, work with climate and oceanographic datasets, perform multi-dimensional analysis with labeled coordinates. Use when the agent needs to: (1) Read/write NetCDF or Zarr files, (2) Work with multidimensional arrays with labeled dimensions, (3) Analyze…
Discover and compose geoscience skills for Python coding tasks. Use when choosing a geoscience library, finding a skill for a data format or method, or planning work across seismic, well logs, geological modelling, inversion, and other geoscience domains.
Calculate reference-ellipsoid geometry, normal gravity and geodetic/geocentric coordinate conversions with Boule. Use for gravity reference corrections and planetary ellipsoids; this does not transform between geodetic datums or compute terrain corrections.
Create finite-volume meshes and discrete differential operators with discretize. Use for TensorMesh or TreeMesh geometry, cell/face/edge ordering, divergence, interpolation and meshes supporting SimPEG; use a physics solver for inversion itself.
Fetch versioned Fatiando geoscience datasets with Ensaio and preserve their hashes, citations and data conventions. Use for reproducible sample-data acquisition and replacing supported RockHound datasets; the fetchers return paths for format-specific readers.
Build, run, inspect and diagnose MODFLOW groundwater flow models with FloPy. Use for aquifer discretization, recharge and boundary conditions, hydraulic heads, groundwater budgets and MODFLOW 6 output; use Pastas for statistical head time series.
Assess and maintain licensed GeoLime geological or mining-model workflows, checking the installed vendor API, drillhole conventions and model validation. Use when a project explicitly uses GeoLime; the public PyPI placeholder does not provide a working modelling API.
Make geographic maps and process geospatial grids with PyGMT and GMT, including projection, regions, grid registration and vector/raster export. Use for GMT cartography and map-ready scientific data; check the separate GMT shared library before plotting.
Analyse paleoclimate proxy time series with Pyleoclim, including irregular sampling, spectra and comparisons across uncertain chronologies. Use for proxy Series and EnsembleSeries analysis, spectral peaks and age-model sensitivity; use xarray for gridded climate fields.
Maintain or migrate legacy RockHound geoscience dataset downloads, caches and loaders such as PREM. Use when an existing project imports RockHound; prefer maintained Ensaio fetchers for supported new dataset workflows.
Read SEG-Y as labelled xarray datasets with SEGY-SAK, inspect header-defined survey dimensions and process seismic volumes lazily. Use for SEG-Y/xarray/Dask workflows; use segyio for exact low-level trace and header editing.
Analyse labelled climate time series and gridded or station observations with checked calendars, aggregation, climatological baselines and spatial validation. Use for climate anomalies, regional summaries or station-to-grid analysis; distinguish descriptive analysis from future-time prediction.
Combine groundwater observations, well logs, and meteorological stresses into a checked hydrogeological interpretation or groundwater-level model. Use for aquifer monitoring and recharge/pumping response analysis, with spatial flow modelling only when its geometry and boundary data are available.
Plan and validate near-surface interpretation from GPR, electrical resistivity tomography, or magnetotelluric data. Use when selecting acquisition-dependent processing and inversion branches, comparing survey results, or relating geophysical anomalies to independently supported geological hypotheses.
★not rated 73▲
+2 1mo agoA56 tokens
originalMIT
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: