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name: using-geoscience-skills description: | 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. license: MIT metadata: skill_type: meta version: 1.0.2 author: Geoscience Skills tags: '["Geoscience", "Skills", "Routing", "Discovery", "Workflows", "Agents"]' dependencies: '[]'

Using Geoscience Skills

Match the user's task to the available domain and workflow skills. Select only the steps needed for the requested result, and reuse data or code already supplied.

When to Use and Alternatives

Use this skill when the appropriate geoscience library is unclear, a request spans multiple domains, or several skills need to work together. For a named library or one focused operation, use its domain skill directly. For an established multi-step task, use the matching workflow skill below.

Routing Procedure

1. Identify the requested deliverable, data format, existing inputs, and environment.
2. Match a focused task with the domain table, or a multi-step task with the workflow table. Treat listed chains as available options, not mandatory stages.
3. Check which skills are available in the current host. Read the selected skill's SKILL.md and only the reference files needed for the task, using the host's available file or resource access.
4. If a skill is missing or unavailable, continue with available documentation and capabilities where practical. State any material limitation; do not claim to have loaded or invoked a skill that was not accessible.
5. Complete the user's requested deliverable with relevant validation. Ask for clarification only when missing information materially affects the result; continue independent work when possible.

Domain Routing Table

Match user intent keywords to the appropriate domain skill.

Keywords / Triggers	Skill	Domain
SEG-Y, seismic traces, trace headers, inline, crossline	segyio	Seismic I/O
SEG-Y to xarray, labelled seismic cube, Dask seismic	segysak	Seismic I/O
waveform, earthquake, FDSN, seismogram, miniSEED	obspy	Seismology
surface wave, dispersion, Rayleigh, Love wave	disba	Seismology
LAS, well logs, wireline, borehole curves	lasio	Well Logs
DLIS, RP66, array logs, modern well data	dlisio	Well Logs
well analysis, curve QC, multi-well, despike	welly	Well Logs
petrophysics, Sw, porosity, formation evaluation	petropy	Petrophysics
lithology, stratigraphy, striplog, facies log	striplog	Stratigraphy
3D model, geology, implicit surface, faults	gempy	3D Modelling
fold modelling, structural frame, Loop3D	loopstructural	3D Modelling
GIS, spatial data prep, borehole to GemPy	gemgis	GIS Preprocessing
existing licensed GeoLime project, mining block model API	geolime	Licensed Modelling
inversion, DC resistivity, magnetics, gravity, EM	simpeg	Inversion
TensorMesh, TreeMesh, cell/face operators, finite-volume mesh	discretize	Meshes
ERT, SRT, IP, near-surface inversion	pygimli	Inversion
PDE, wave equation, finite differences, stencil	devito	Simulation
linear operator, inverse problem, sparsity	pylops	Inverse Problems
gravity, magnetic, Bouguer, upward continuation	harmonica	Potential Fields
reference ellipsoid, normal gravity, geocentric latitude	boule	Geodesy
AVO, Zoeppritz, Gassmann, fluid substitution, wavelet	bruges	Rock Physics
gridding, interpolation, spatial, Verde	verde	Spatial Analysis
variogram, kriging, GSLIB, geostatistics	geostatspy	Geostatistics
variogram fitting, scikit-learn style geostat	scikit-gstat	Geostatistics
spatial regression, GWR, GNNWR, non-stationarity, coefficient mapping	gnnwr	Spatial Regression
groundwater, time series, pumping test	pastas	Hydrology
MODFLOW, aquifer flow, head, recharge, water budget	flopy	Hydrology
landscape, erosion, surface processes, DEM	landlab	Surface Processes
stereonet, strike, dip, poles, structural	mplstereonet	Structural Geology
geochemistry, REE, spider diagram, ternary	pyrolite	Geochemistry
GPR, ground-penetrating radar, radargram	gprpy	Near-Surface
magnetotellurics, MT, impedance tensor	mtpy	Near-Surface
NetCDF, xarray, multi-dimensional, climate	xarray	Data Formats
paleoclimate proxy, age ensemble, irregular spectrum	pyleoclim	Paleoclimate
3D visualization, mesh, VTK, point cloud	pyvista	Visualization
GMT, PyGMT, map projection, geographic grid cartography	pygmt	Cartography
data download, sample data, cache, fetch	pooch	Utilities
Fatiando datasets, explicit dataset version, Ensaio	ensaio	Datasets
existing RockHound cache, legacy PREM loader migration	rockhound	Legacy Datasets

Workflow Skills

Use the skill name directly when the host supports skill selection, or read the available workflow instructions. Natural-language requests can match these tasks.

Skill Name	Typical Task	Relevant Domain Skills
seismic-interpretation	Process or interpret seismic data; build a seismic-to-well tie	segyio, obspy, bruges, disba, pyvista
well-log-evaluation	Evaluate formations from LAS or DLIS logs	lasio, dlisio, welly, petropy, striplog, pyvista
geological-modelling	Build a 3D model from mapping, boreholes, or GIS inputs	gemgis, gempy or loopstructural, pyvista
geophysical-inversion	Recover physical properties from ERT, EM, gravity, or magnetic data	simpeg or pygimli, verde, pyvista
rock-physics-avo	Compute elastic properties, fluid substitution, AVO, or synthetics	lasio, welly, bruges, segyio
hydrogeological-analysis	Combine well logs, groundwater head time series and aquifer hypotheses	lasio, welly, pastas, optionally flopy
near-surface-geophysics	Compare GPR, ERT and MT evidence with matched coordinates and resolution	gprpy, pygimli or simpeg, mtpy
climate-analysis	Analyse climate time series and grid spatial observations without leakage	xarray, verde, optionally pyleoclim

Composition and Data Handoffs

• Start from the inputs already available. Data loading, modelling, plotting, and export are needed only when they contribute to the requested task.
• Carry units, coordinates, depth or time basis, array shapes, missing-value masks, and provenance across library boundaries. Ensure later stages use the intended processed output.
• Check each selected skill's metadata.dependencies against the environment. Dependency and complement lists are descriptive metadata, not package-installation commands or proof that another skill is available.
• Choose compatible libraries and adapters for the selected branch. Do not assume alternatives produce interchangeable objects.
• Match validation to the deliverable: a corrected script, explanation, QC report, model, plot, or exported dataset may each complete the user's request.

Optional Role References

The repository's agents/data-qc-reviewer.md, agents/geoscience-mentor.md and agents/cross-validation-reviewer.md are optional role references for hosts that support them. Ordinary skill installation may omit these files. Perform QC and explanations with available capabilities; these roles and host-specific integrations are not requirements for routing or executing the core skills.

Common Issues

Issue	Response
A recommended skill is not installed	Use available guidance or capabilities and report any material gap.
A required Python package is unavailable	Inspect the project environment and dependency guidance before choosing a compatible setup or alternative.
Data is already loaded or processed	Begin at the relevant stage and verify the supplied data's assumptions.
Several libraries match the request	Choose by data format, required operation, existing environment, and requested result.