Construction of Shear Wave Models by Applying Multi-Objective Optimization to Multiple Geophysical Data Sets

For this work, our main purpose is to obtain a better understanding of the Earth’s tectonic processes in the Texas region, which requires us to analyze the Earth structure. We expand on a constrained optimization approach for a joint inversion least-squares (LSQ) algorithm to characterize a one-dimensional Earth’s structure of Texas with the use of multiple geophysical data sets. We employed a joint inversion scheme using multiple geophysical datasets for the sole purpose of obtaining a three-dimensional velocity structure of Texas in order to identify an ancient rift system within Texas. In particular, we use data from the USArray, which is part of the EarthScope experiment, a 15-year program to place a dense network of permanent and portable seismographs across the continental United States. Utilizing the USArray data has provided us with the ability to image the crust and upper mantle structure of Texas. We simultaneously inverted multiple datasets from USArray data, to help us to better obtain an estimate of the true Earth structure model. We prove through numerical and experimental testing that our Multi-Objective Optimization (MOP) scheme performs inversion in a more robust, and flexible matter than traditional inversion approaches.