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WITHDRAWN Crossfade Markov Chain Monte Carlo Simulation for Fault Slip Modeling

Description: 

WITHDRAWN There are many underdetermined geophysical inverse problems. For example, when we try to infer earthquake fault slip, we find that there are many potential slip models that are consistent with our observations and our understanding of earthquake physics. One way to approach these problems is to use Bayesian analysis to infer the ensemble of all potential models that satisfy the observations and our prior knowledge.

Simulating a posterior PDF can be computationally expensive. Typical earthquake rupture models with 10 km spatial resolution can require using Markov Chain Monte Carlo (MCMC) to draw tens of billions of random realizations of fault slip. And now new technological advancements like LiDAR provide enormous numbers of laser point returns that image surface deformation at submeter scale, exponentially increasing computational cost. How can we make MCMC sampling efficient enough to simulate fault slip distributions at sub-meter scale using Big Data?

Here we describe a new MCMC approach called crossfading in which we transition from an analytical posterior PDF to the desired target posterior PDF. This approach has two key efficiencies. First, the starting PDF is by construction close to the target posterior PDF, requiring very little MCMC to update the samples to match the target. Second, all PDFs are defined in model space, not data space. The forward model and data misfit are never evaluated during sampling, allowing models to be fit to Big Data with zero computational cost. It is even possible, without additional computational cost, to incorporate model prediction errors for Big Data, that is, to quantify the effects on data prediction of uncertainties in the model design. While we present earthquake models, this approach is flexible and can be applied to many geophysical problems. This approach is suitable for many hardware architectures, and our algorithm has been run on large-scale clusters, with GPU acceleration, and using vector machines.

Session: Numerical Modeling in Seismology: Developments and Applications

Type: Oral

Date: 4/20/2023

Presentation Time: 05:30 PM (local time)

Presenting Author: Sarah Minson

Student Presenter: No

Invited Presentation: 

Authors