mlsanityData to 7 Oct 2026

Learned multiphysics inversion with differentiable programming and machine learning

arXiv 2304.05592 ↗First posted 12 Apr 2023cs.MS cs.DC cs.LGcited by 7

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Abstract (arXiv)

We present the Seismic Laboratory for Imaging and Modeling/Monitoring (SLIM) open-source software framework for computational geophysics and, more generally, inverse problems involving the wave-equation (e.g., seismic and medical ultrasound), regularization with learned priors, and learned neural surrogates for multiphase flow simulations. By integrating multiple layers of abstraction, our software is designed to be both readable and scalable. This allows researchers to easily formulate their problems in an abstract fashion while exploiting the latest developments in high-performance computing. We illustrate and demonstrate our design principles and their benefits by means of building a scalable prototype for permeability inversion from time-lapse crosswell seismic data, which aside from coupling of wave physics and multiphase flow, involves machine learning.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 29 of its 90 references that are in the map. First posted on arXiv 12 Apr 2023.

Builds on

29 of 90 references.

References · 29

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17 more
  1. 2021Preconditioned training of normalizing flows for variational inference in inverse problemscited by 19
  2. 2022Model-Parallel Fourier Neural Operators as Learned Surrogates for Large-Scale Parametric PDEscited by 13
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 4; 2024: 1; 2025: 0; 2026: 2.

7 papers.

  1. 2023WISE: full-Waveform variational Inference via Subsurface Extensionscited by 10
  2. 2023Solving multiphysics-based inverse problems with learned surrogates and constraintscited by 9
  3. 2023InvertibleNetworks.jl: A Julia package for scalable normalizing flowscited by 6
  4. 2023Inference of CO2 flow patterns -- a feasibility studycited by 4
  5. 2026Conditional neural control variates for variance reduction in Bayesian inverse problemscited by 2
  6. 2026Dual-space posterior sampling for Bayesian inference in constrained inverse problemscited by 2
  7. 2024Diffusion-based subsurface CO2 multiphysics monitoring and forecastingcited by 0