Simultaneous Bayesian Estimation of Non‐Planar Fault Geometry and Spatially‐Variable Slip

Large earthquakes are usually modeled with simple planar fault surfaces or a combination of several segments. However, in general, occur on faults that non-planar and exhibit significant geometrical variations both the along-strike down-dip directions at all spatial scales. Mapping surface ruptures high-resolution geodetic observations increasingly revealing complex geometries near accurate locations aftershocks often indicate complexities depth. With better data ruptures, more details can be estimated resulting realistic models large earthquakes. To address this topic, we here parametrize set polynomial parameters allow for geometry. Our methodology uses Bayesian inference to estimate from data, yielding an ensemble plausible characterize uncertainties geometry slip. The method is demonstrated using synthetic tests considering slip spatially distributed single continuous finite varying dip strike angles directions. results show fault-slip estimations biased when assumed presence variations. help model earthquake sources way may extended include multiple segments other complexities.