OS21A-1110:
Basin-Scale Modeling of Methane Hydrate Accumulations in the Gulf of Mexico
Tuesday, 16 December 2014
Michael Nole, University of Texas at Austin, Austin, TX, United States, Hugh Daigle, University of Texas, Austin, TX, United States and Kishore K Mohanty, Univ of TX-Austin CPE 3.168, Austin, TX, United States
Abstract:
Walker Ridge Block 313 in the northern Gulf of Mexico has been investigated recently through a logging-while-drilling program and seismic data acquisition to assess the distribution and abundance of methane hydrate-bearing sand reservoirs. The data indicate that lithological heterogeneity in the region exerts control on the spatial distribution of hydrate, promoting short (diffusive) migration of methane from fine-grained intervals into hydrate-bearing sands. To better understand the mechanisms governing the formation and distribution of methane hydrate in marine sediments such as these, we employ a basin-scale reservoir model. We modified a methane hydrate reservoir simulator to include the effects of basin sedimentation, pore water salinity, and microbial methanogenesis. The output of the model is compared to well-characterized methane hydrate distributions at Walker Ridge in the Gulf of Mexico. Our approach employs new methods for determining pore-scale properties. Rather than using empirical formulas that approximate the permeability distribution with depth as a function of compaction porosity, we constrain input permeability directly from analysis of downhole logs. Pore size is determined using a similar method and is used to constrain hydrate equilibrium conditions. Given the expected sand/clay pore size contrast at WR 313 (factor of roughly 3), the dissolved methane concentration gradient between sands and clays caused by their pore size difference is relatively small. This manifests in slower hydrate formation in sands at shallower intervals, with hydrate forming more rapidly deeper in the section due to the diffusive gradients being enhanced by greater spatial solubility gradients. This work is an important step in furthering our ability to properly predict subsurface methane hydrate distributions.