INTEGRATED SEISMIC INVERSION, ROCK PHYSICS MODELING & DATA ANALYTICS FOR CARBON STORAGE

The world’s population is estimated to be 10 billion by 2050 and as a result, energy demand would increase exponentially. Additionally, global carbon emissions due to our surpassing need for energy for power generation, transportation, and industrial activities would increase significantly. Despite enormous technological advances, global warming due to greenhouse gas emissions from anthropogenic activities continue to have a deleterious effect on the climate. Geologic carbon storage provides a sustainable solution for limiting the adverse environmental footprints of anthropogenic activities, as well as for enhanced oil recovery and providing raw materials for industrial products. The high storage potential of depleted hydrocarbon reservoirs and saline aquifers can provide an abode for captured greenhouse gases like carbon dioxide. This research focuses on delineating potential geologic sites for carbon storage at the Mississippi Canyon block 118 (MC-118) field on the northern slope of the Gulf of Mexico. This site is located on a passive margin that is significantly influenced by salt tectonics and slope failure. Furthermore, salt tectonics controls the basin geometric architecture resulting in complex faulting and sediment-salt interplays. Hence, MC-118 proves to be a challenging terrain to characterize reservoirs for their storage capacities. Likewise, estimating the storage capacity of each prospective carbon storage site is of utmost importance. Rock physics modeling and petrophysical characterization involving Post-Stack Seismic Inversion are employed in estimating reservoir properties such as lithology, porosity, and water saturation. Acoustic impedance, a seismic attribute useful in delineating lithology, was extracted from post-stack seismic inversion modeling. Additionally, data analysis methods are useful in discovering correlations between reservoir properties that may be difficult for humans to observe. This research also explores the use of data analytics alongside rock physics modeling to improve reservoir property estimation. By integrating geophysical characterization with computer algorithms as well as interpolation techniques, suitable sites with ample carbon storage capacity could be delineated and these methods can be replicated for other locations.