Group B, Poster #226, Community Earth Models (CEM)

Salton Trough crustal model optimization: Wasserstein kernel

Rasheed Ajala, & Folarin Kolawole
Poster Image: 

Poster Presentation

2024 SCEC Annual Meeting, Poster #226, SCEC Contribution #13942 VIEW PDF
Earth models in high seismic risk areas must be optimized using high-frequency data to become relevant for deterministic earthquake hazard assessment and detailed subsurface geologic studies. The computational cost of such pursuit is high but has become more tractable due to advances in multiscale model merging, allowing for inversion focused on local spatial scales. Here, we present ongoing developments in inverting Imperial Valley's Salton Seismic Imaging Project (SSIP) data. Although the hybrid starting model already produces forward models with features comparable to the observed records, the long-wavelength nature of the model induces significant kinematic errors. In addition, the ...land-based SSIP dataset is high-frequency and noisy. Data misfit sensitivity analysis for various objective measures suggests convergence in local minima. Thus, we implement the optimal transport (Wp) metric, which is known to have better convexity and convergence properties. We specifically adopt the trace-by-trace approach using the linear integral wavefield method to satisfy the data nonnegativity condition while also benefiting from enhancements in convexity resulting from the low-frequency boost. We show compressional wave speed sensitivity kernels in Imperial Valley.
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Citation: Ajala, R., & Kolawole, F. (2024, 09). Salton Trough crustal model optimization: Wasserstein kernel. Poster Presentation at 2024 SCEC Annual Meeting.
Keywords: Inversion, Optimization, Optimal Transport, Active Source
SCEC Award: 23178, 24043
Relevant SCEC Themes:
Improving Observations and Closing Data Gaps
Advanced Modeling Frameworks
Applied Science Implementation