CREST-PRF: Optimization of Joint Inversion of Geophysical Data to Improve 3-Dimensional Models of Earth Structures

Zamora Azucena, El Paso TX

Investigators

Abstract

Optimization of Joint Inversion of Geophysical Data to Improve 3-Dimensional Models of Earth Structures The Centers of Research Excellence in Science and Technology-Postdoctoral Research Fellowship (CREST-PRF) track within the CREST program supports beginning CREST Center investigators with significant potential and provides them with training and research experiences that will broaden perspectives, facilitate interdisciplinary interactions and establish them in positions of leadership within the scientific community. This CREST-PRF project is aligned with the research focus of the CREST Cyberinfrastructure for Sharing resources to Advance Research and Education (Cyber-ShARE) Center of Excellence at the University of Texas at El Paso. Earth sciences aim to determine the interior composition of the Earth by using a wide array of methods to understand its changes throughout the millennia and predict possible future behavior. For example, regions with relatively low seismic activity have experienced earthquakes due to motion of tectonic faults within the Earth's dynamic interior. Moreover, atypical plate tectonic processes, such as the breaking of a subducting oceanic plate that occurred with recent Mexico earthquakes in September 2017 make understanding the complex processes imperative to avoid future catastrophes. This research project will characterize the location and condition of seismological faults and the current state of ancient strains in the lower crust and address fundamental questions about the tectonic evolution of the Earth. Specifically, the project will develop and improve 3-Dimensional (3-D) Earth models in targeted regions through the optimization of the joint inversion of complementary seismic (surface wave group velocities and teleseismic P-wave receiver functions) and non-seismic (Bouguer gravity anomalies) datasets. The combined resolution of these datasets will allow pinpointing of key features within the subsurface that may be overlooked by the geophysical surveys. Early college, high school and traditional K-12 students will be engaged in this project. The proposed research will develop and apply numerical optimization to improve the resolution of 3-D Earth structure models. Although important methods have been previously developed to optimize the results obtained from the inversion of complementary datasets for increasingly complex geological environments, recent more powerful mathematical tools have provided evidence that constrained optimization techniques can greatly improve final structural models for the interior of the Earth. The use of primal-dual interior point methods for the joint inversion of seismic and non-seismic datasets can provide further improvement to 3-D imaging of the Earth by constraining the solution space and focusing only on feasible structural models. Part 1 of this project involves the development of computational algorithms to optimize the results obtained from the joint inversion of multiple datasets. In Part 2, the processes involved in the optimization will be analyzed to determine the optimal and most cost-effective division of work to simultaneously execute the code (parallel programming) in a multi-core environment. These algorithms will be applied to datasets from Colombia to obtain a new tectonic understanding of its complex substructure-characterized by a unique geological setting where the Cocos, Caribbean, and South American plates converge. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.