Rock Physics (geobrain.physics.rock)

Rock Physics (geobrain.physics.rock)#

The rock physics module transforms geological properties (porosity, mineralogy, fluid saturation) into elastic parameters (Vp, Vs, density) for seismic modeling. It provides 70+ differentiable PyTorch models organized by category.

Effective Medium Models#

Voigt-Reuss-Hill (VRH) Averaging#

Compute effective mineral moduli from constituent minerals:

from geobrain.physics.rock import VRH
import torch

vrh = VRH()
vol_fractions = torch.tensor([0.9, 0.1])  # Quartz, clay
K_minerals = torch.tensor([36.6, 21.0])   # Bulk moduli (GPa)

K_voigt, K_reuss, K_hill = vrh(vol_fractions, K_minerals)

Soft Sand Model#

Granular rock model based on Hertz-Mindlin contact theory:

from geobrain.physics.rock import SoftSand

soft_sand = SoftSand()
K_dry, G_dry = soft_sand(
    K_mineral=36.6,
    G_mineral=44.0,
    porosity=phi,
    critical_porosity=0.4,
    coordination_number=7,
    pressure=pressure,       # Effective pressure (MPa)
)

Fluid Substitution#

Gassmann’s Equation#

Compute saturated rock moduli from dry-frame properties:

from geobrain.physics.rock import Gassmann

gassmann = Gassmann()
K_sat, G_sat = gassmann(K_dry, G_dry, K_mineral, K_fluid, porosity)

Density Model#

from geobrain.physics.rock import DensityModel

density = DensityModel()(porosity, rho_mineral, rho_fluid)

Velocity Computation#

Convert bulk and shear moduli to P- and S-wave velocities:

from geobrain.physics.rock import v_from_moduli

vp, vs = v_from_moduli(K_sat, G_sat, density)
../_images/05_rock_physics_fields.png

Fig. 16 Rock physics workflow: porosity to Vp, Vs, density fields.#

Rock Physics Workflow#

Use presets for common scenarios:

from geobrain.physics.rock import RockPhysicsWorkflow

workflow = RockPhysicsWorkflow.from_preset('shaly_sand')
vp, vs, rho = workflow(porosity, sw)
../_images/05_crossplot.png

Fig. 17 Vp-porosity crossplot with rock physics model overlay.#

Mineral & Fluid Database#

from geobrain.physics.rock import MINERALS, FLUIDS, get_mineral, get_fluid

quartz = MINERALS['quartz']    # K, G, rho
brine = FLUIDS['brine']        # K, rho

Available Models#

Category

Models

Effective medium

VRH, Hashin-Shtrikman, DEM, Self-Consistent, Critical Porosity, Hudson, Eshelby-Cheng

Granular media

Hertz-Mindlin, SoftSand, StiffSand, ContactCement, Walton, MUHS, PCM, Digby, Thomas-Stieber

Fluid substitution

Gassmann (forward & inverse), Wood, Brie, Batzle-Wang, Biot, CO2 properties, LiveOil, CO2-Brine, Brown-Korringa

Empirical

Gardner, Han, Castagna, Krief, Raymer-Hunt, Storvoll, Japsen, Hillis, Scherbaum

Anisotropy

Thomsen (VTI/HTI), Backus averaging, Bond transform

Permeability

Kozeny-Carman, Owolabi, Panda-Lake, Revil, Fredrich, Bloch, Bernabe

Resistivity

Archie’s law

Quantitative Interpretation

QI tools for crossplot analysis

All models are differentiable PyTorch modules and can be composed into end-to-end inversion workflows.

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