pimsr-forward

Forward modeling engine for the PIMSR (Physics-Informed Multi-modal Subsurface Reconstruction) project.

Turns stochastic geology models from pimsr-geogen into realistic geophysical observables:

• Magnetotellurics (MT), 2D TE+TM (mt2d.py) — SimPEG-based finite-volume forward for 2D sections: TE (Simulation2DElectricField) and TM (Simulation2DMagneticField) apparent resistivity + phase pseudo-sections at 16 stations x 24 periods. Validated against the 1D analytic response to 0.4% (TE) / 0.13% (TM) median error on layered models.
• Magnetotellurics (MT), 1D analytic — exact impedance recursion for layered media (Wait recursion). Apparent resistivity + phase over a configurable period band.
• Gravity — vertical attraction of right rectangular prisms (Nagy 1966 closed form), evaluated on a surface profile.
• Sensor / noise model — realistic MT error floors (impedance-proportional + absolute floor), AR(1)-correlated galvanic distortion calibrated on real USArray residuals, per-station static shift, and per-mode severity: TM curves receive stronger per-section static shifts and distortion than TE, matching real yx-impedance behaviour.
• Dataset builders — 1D per-station (dataset.py) and 2D section (dataset2d.py, chunk-resumable, shard merging) HDF5 training sets for pimsr-inversion. The 2D builder writes 4-channel TE+TM observations.

Physics validation

The 1D MT kernel is cross-checked against half-space and two-layer analytic limits in tests (tests/test_mt1d.py), and against SimPEG's 1D MT simulation in pimsr-benchmarks. The 2D TE/TM forwards are validated against the 1D analytic response on layered sections (tests/test_mt2d.py).

The gravity kernel is checked against the infinite-slab Bouguer limit and prism symmetry identities (tests/test_gravity.py).

Install

pip install -e .

Usage

from pimsr_forward import mt1d_response, prism_gz, SensorModel

rho_app, phase = mt1d_response(resistivities, thicknesses, periods)

Dataset generation CLI:

# 1D per-station dataset
pimsr-forward-dataset --geology geology.h5 --out dataset.h5 --seed 42
# 2D TE+TM section dataset (requires the mt2d extra: pip install -e ".[mt2d]")
pimsr-forward-dataset2d --n 1000 --seed 7 --out ds2d.h5

License

MIT