petekIO

The subsurface data layer — a Rust library (with optional PyO3 bindings) that turns raw subsurface files into clean, validated, interpreted data: surfaces, wells (trajectories / tops / logs), points, and polygons, with loading, mnemonic and unit normalisation, validation, petrophysical interpretation, interpolation, and statistics.

The pipeline is the point:

ingest → normalize → validate → interpret → characterise

Why build on it

Subsurface data is the unglamorous, error-prone groundwork under every reservoir application: vendor LAS mnemonics, mismatched units, out-of-range samples, cutoffs, gridding that has to honour its control points, uncertainty. petekIO does that work once and behind a stable API, so the application on top stays thin and stays in its own domain:

• The whole path, not just parsing. Files in; normalized, validated, interpreted domain objects out — no re-implementing LAS aliasing, unit harmonisation, petrophysical cutoffs (net pay included), or surface gridding/resampling further up the stack.
• Values know what they are. Results come back in canonical units, each carrying an uncertainty distribution and a provenance flag (measured / interpolated / defaulted) — so downstream code propagates uncertainty rather than re-deriving it.
• A substrate, not a grab-bag. Load a project once into a GeoData and operations broadcast across the whole collection. Immutable, strictly layered, fluent.
• Rust core, thin Python. Fast and embeddable, with PyO3 bindings that mirror the Rust API.

Built in gates

petekIO grows in gated phases against a locked contract: every public signature is specified in API.md (a change needs sign-off), and the design + build roadmap live in SPEC.md.

Status: early development. The public API is locked and the core data path (ingest → normalize → validate → interpret → characterise) is in place; breadth is still filling in — more ingest formats, fluid contacts, richer interpretation.

Design at a glance

• Strictly layered, one-way deps: foundation → io → core → analysis → manager → py.
• A manager substrate (GeoData): load once, operations broadcast across the collection — no per-item loops.
• Domain objects carry their operations (arithmetic, filters, interpolation, stats) — fluent and chainable.
• Rust core + thin PyO3; the Python API mirrors the Rust API.

Built on

• petekAlgorithms — standalone numerics / geostatistics kernels (gridding, interpolation) that petekIO builds on.

License

MIT — see LICENSE-MIT.