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AAPG ACE 2018

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Pre-Injection Reservoir Characterization for CO2 Storage in the Near Offshore Areas of the Texas Gulf of Mexico

Abstract

The injection of CO2 into the subsurface (carbon capture and storage; CCS) is the most viable approach to significantly and rapidly reduce industrial emissions of greenhouse gasses to the atmosphere. The inner continental shelf of the northern Gulf of Mexico has incredible potential for CO2 storage, and could serve as a storage resource of national significance. This study quantitatively evaluates the CO2 storage capacity of the Lower Miocene brine-filled sandstones in the inner continental shelf of the Texas Gulf of Mexico using 3D seismic and well log data. The first part of this work investigates the relationship between elastic properties and reservoir properties (e.g. porosity, mineralogy, and pore fluid) of the Lower Miocene section using rock physics modeling and simultaneous seismic inversion. The elastic properties are related to porosity, mineralogy and pore fluid using rock physics models. These rock physics transforms are then applied to the seismically derived elastic properties to estimate the porosity and lithology away from the wells. The porosity and lithology distribution derived using this quantitative method can be interpreted to predict the best areas for CO2 storage in the inner continental shelf of the Texas Gulf of Mexico. The second part of this work studies the effect that CO2 has on the elastic properties of the Lower Miocene rocks using fluid substitution, amplitude Previous HitvariationNext Hit with Previous HitangleNext Hit (Previous HitAVANext Hit), and statistical classification to determine the ability of the seismic method to successfully monitor CO2 injected into the subsurface. The velocities and density well logs were modeled with different fluid saturations. To characterize the seismic properties corresponding to these different fluid saturations, the Previous HitAVANext Hit responses and probability density functions were calculated and used for statistical classification. The Previous HitAVATop modeling shows a high sensitivity to CO2 due to the soft clastic framework of the Lower Miocene sandstones. The statistical classification successfully discriminates between brine and CO2 saturation using Vp/Vs and P-impedance. These results shows that the Lower Miocene sandstone have the capacity to host CO2, and that the CO2 injected in these rocks is likely to be successfully monitored using seismic methods.