2020/05/20 by Bharath Shekar, Shekar, Bharath
Earth and Planetary Sciences · Engineering · Environmental Science · Physics and Astronomy · #FOS: Physical sciences #Geophysical Methods and Applications #Geophysics (physics.geo-ph) #Groundwater flow and contamination studies #Hydrocarbon exploration and reservoir analysis #Seismic Imaging and Inversion Techniques #physics.geo-ph
paper · pdf · doi:10.48550/arxiv.2005.09899
Submitted for review, 90th Annual International Meeting, SEG, Expanded Abstracts
openalex publication_date 2020/05/20 · arxiv created 2020/05/22 · arxiv updated 2020/05/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Full waveform inversion (FWI) is a powerful yet computationally expensive technique that can yield subsurface models at high resolution. Randomly selected shots ("mini-batches") can be used to approximate the misfit and the gradient of FWI, thereby reducing its computational cost. Here, we present a methodology to perform mini-batch FWI using the Adam algorithm, an adaptive optimization scheme based on stochastic gradient descent. It provides for stable model updates by smoothing the gradient across iterations and can also account for the curvature of the optimization landscape. We describe empirical criteria to choose the hyperparameters of the Adam algorithm and the optimal mini-batch size. The performance of the outlined scheme is illustrated on synthetic data from the Marmousi model.