Subsurface4D is an open-source framework designed to advance subsurface imaging to monitoring. We build 4-dimensional, uncertainty-quantified models by integrating wave physics, fiber-optic sensing, and Bayesian inference to track and reveal the Earth's changing interior. Our work provides critical insights for groundwater resources, carbon sequestration, volcanology, and energy exploration and storage.
Maintained by Haipeng Li (haipeng@stanford.edu), Stanford University.
Reproducible code for Bayesian Full-Waveform Monitoring of CO2 Storage With Fluid-Flow Priors via Generative Modeling (Li, Wang, Durlofsky & Biondi, JGR: Machine Learning and Computation, 2026).
Generic cable class for Distributed Acoustic Sensing (DAS) data modeling (forward) and inversion (adjoint).
Analytical particle velocity/displacement/strain/strain rate solution for the 3D/2D wave equation due to a moment tensor source in a homogeneous, isotropic elastic medium based on Aki & Richards (2002).
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