Learning Pore-scale Multiphase Flow from 4D Velocimetry

TL;DR

This paper presents a multimodal machine learning framework that predicts 3D multiphase flow and interface dynamics in porous media from 4D velocimetry data, enabling rapid and realistic pore-scale simulations.

Contribution

It introduces a novel coupled graph network and 3D U-Net model that infers pore-scale multiphase flow directly from experimental 4D velocimetry measurements.

Findings

Captures transient flow perturbations and interface rearrangements.

Reduces complex simulations to seconds of inference.

Provides a tool for digital experiments in porous media.

Abstract

Multiphase flow in porous media underpins subsurface energy and environmental technologies, including geological CO$_2$ storage and underground hydrogen storage, yet pore-scale dynamics in realistic three-dimensional materials remain difficult to characterize and predict. Here we introduce a multimodal learning framework that infers multiphase pore-scale flow directly from time-resolved four-dimensional (4D) micro-velocimetry measurements. The model couples a graph network simulator for Lagrangian tracer-particle motion with a 3D U-Net for voxelized interface evolution. The imaged pore geometry serves as a boundary constraint to the flow velocity and the multiphase interface predictions, which are coupled and updated iteratively at each time step. Trained autoregressively on experimental sequences in capillary-dominated conditions ($Ca\approx10^{-6}$), the learned surrogate captures transient, nonlocal flow perturbations and abrupt interface rearrangements (Haines jumps) over rollouts spanning seconds of physical time, while reducing hour-to-day--scale direct numerical simulations to seconds of inference. By providing rapid, experimentally informed predictions, the framework opens a route to ''digital experiments'' to replicate pore-scale physics observed in multiphase flow experiments, offering an efficient tool for exploring injection conditions and pore-geometry effects relevant to subsurface carbon and hydrogen storage.