Characterization of subsurface natural gas hydrate systems by leveraging diverse datasets
Characterization of subsurface natural gas hydrate systems by leveraging diverse datasets
Session ID#: 125119
Session Description:
Gas hydrate occurrence in nature is the result of complex and highly coupled thermal, mechanical, chemical, geological, and biological processes in the subsurface. The expression of gas hydrate in the subsurface is thus highly heterogeneous in terms of hydrate morphology, origin and type of the guest molecule. Understanding how coupled processes interact to form gas hydrate requires multidisciplinary approaches and leveraging of diverse datasets across geoscience disciplines.
We invite contributions from geophysicists, geochemists, data scientists, as well as structural and petroleum geologists to present modeling, data analysis, and laboratory results as they pertain to better understanding coupled processes leading to hydrate occurrence in nature. We particularly encourage submissions related to novel computational techniques and machine learning analyzing gas hydrate systems from perspectives of global environmental change, resource prospecting, and geohazard mitigation.
Index Terms:
0460 Marine systems [BIOGEOSCIENCES]
1942 Machine learning [INFORMATICS]
3004 Gas and hydrate systems [MARINE GEOLOGY AND GEOPHYSICS]
Primary Convener: Michael Nole, Sandia National Laboratories, Albuquerque, NM, United States
Conveners: Jennifer Frederick, Sandia National Laboratories, Albuquerque, NM, United States and Alexey Portnov, University of Texas at Austin, Jackson School of Geosciences Institute for Geophysics, Austin, TX, United States
Primary Liaison: Michael Nole, Sandia National Labs, Albuquerque, NM, United States
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