SS1: Machine Learning for Coupled Processes in the Earth Sciences and Engineering
DISTINGUISHED INVITED SPEAKERS:
David D. Nolte
Purdue University, USA
Occidental Petroleum, USA
Gregory C. Beroza
Stanford University, USA
Sandia National Laboratories, USA
University of Bristol, UK
Los Alamos National Laboratory, USA
Conveners: Mengsu Hu, Laura J. Pyrak-Nolte
This Special Session of Machine Learning for Coupled Processes in the Earth Sciences and Engineering will have six Distinguished Invited Lectures on state-of-the-art machine learning applications. These cover a diverse range of topics from classifying acoustic sources in multiphysical laboratory tests (Nolte) to analyzing volcanic ground deformation with InSAR data (Anantrasirichai), to gaining a clearer understanding of induced seismicity (Beroza), and to achieving more precise control for optimized reservoir production (Ben, Viswanathan, Yoon).
We invite submissions that present the latest research on the development and applications of machine learning toolsets to advance a predictive understanding of fundamental Earth processes and to enable adaptive control of coupled processes fractured geological media.