Probabilistic Predictions of Gas Hydrate Formation near Blake Ridge using Dakota and PFLOTRAN

Methane hydrates are solid structures containing volumes of methane inside of a water lattice. The stability of these structures is pressure- and temperature-dependent; appropriate conditions of low temperature and relatively high pressure exist in different global settings, such as those along continental shelves or associated with permafrost. Hydrates have garnered significant scientific interest due to both the potential to serve as an energy resource of natural gas and their role in global carbon cycles (e.g., risks to global warming due to release of methane into the water column and subsequently the atmosphere). While methane hydrates have been collected and identified in several geographic locations including the Gulf of Mexico, offshore Japan, and in the Arctic, the locations and quantity are poorly constrained and observations are sparse. Based on statistical and machine learning approaches, we have developed a workflow to probabilistically predict locations of methane hydrate occurrence. This approach utilizes the Global Predictive Seabed Model (GPSM) developed by the Naval Research Laboratory as inputs for Sandia National Laboratories' software packages, Dakota and PFLOTRAN. Dakota is used to sample the GPSM values and their uncertainties using Latin hypercube sampling and feeds simulation parameters (e.g., total organic carbon (TOC) and heat flux). Then, PFLOTRAN simulates gas hydrate and free gas formation in 1-D resulting from local microbial sourcing (methanogenesis) over 10 Myr. We ran 100 simulations at 5,285 locations near Blake Ridge at 5 × 5 arcminute spacing down to a maximum of 1,000 meters below seafloor (mbsf) and the predicted hydrate saturation profiles were used to determine the mass of hydrate formed at each location. Elevated hydrate formation is predicted to occur at depths greater than 500 m below sealevel and is strongly associated with high TOC values at the seafloor. Gas saturation can be used to improve predictions of seafloor acoustic characteristics and this workflow can be extended to other geologic settings. Based on the average of multiple realizations, we produce representative maps of hydrate occurrence for the study area which can be validated against geophysical observations.

SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525. SAND2020-7586 A