Leveraging Computer Science for Advancements in Geology and Geophysics

Abstract

The integrati on of computer science with geology and geophysics has revoluti onized how Earth scienti sts collect, process, analyze, and visualize data. From the processing of seismic data and the simulati on of subsurface structures to the use of machine learning for predicti ve modeling, computati onal tools have enhanced the effi ciency, accuracy, and scope of geological and geophysical research. This review explores key applicati ons of computer science in these fi elds, including data processing, modeling, visualizati on, machine learning, and the use of high-performance computi ng (HPC) for large-scale simulati ons. Advances in arti fi cial intelligence (AI), such as automated seismic interpretati on and predicti ve hazard modeling, have further accelerated the ability to predict natural phenomena and improve resource management. Despite the progress, challenges related to data integrati on, AI interpretability, and interdisciplinary collaborati on remain. Nonetheless, the conti nued development of computati onal techniques promises to deepen our understanding of geological processes and improve real-ti me decision-
making in resource explorati on, environmental monitoring, and natural disaster predicti on.