Abstract

The close proximity of large CO2 emitters and depleted oil and gas reservoirs in the Louisiana Chemical Corridor (LCC) provide unique opportunities for CO2 geological sequestration in coastal Louisiana. The identification of sites with good storage capacity and retention characteristics is of prime importance for successful CO2 storage projects. In this study, the Bayou Sorrel field area located within close proximity of some of the large CO2 emitters in the LCC, is analyzed as a potential candidate site for aquifer storage. The results of static and dynamic aquifer storage capacity estimates are presented in this study. A volumetric approach is used to estimate the static storage capacity, and reservoir simulations are performed to compute dynamic storage capacity. The field and well data from publically available data sources are compiled to characterize the sands for prospective CO2 sequestration intervals (i.e., non-productive sands), and pressure and temperature conditions.

Information of total areal extent, gross formation thickness, and total porosity are used along with a storage efficiency factor to find the pore volume available for storage. The upper depth limit for CO2 injection is dictated by the pressure and temperature conditions at which CO2 exists in a supercritical state. The Peng-Robinson (PR) equation of state is used in conjunction with subsurface pressure and temperature to determine the minimum depth at which CO2 is supercritical. Multiple geological realizations are used for a realistic site specific storage capacity estimate. The reservoir simulations capture the transient nature of the process and provide estimation of storage capacity under dynamic conditions. The sensitivity of injection location and boundaries is also evaluated in the dynamic storage capacity estimates.

The results of the dynamic storage capacity estimate for a 1,000 ft thick interval at an average depth of 7,100 ft show that reasonable values of storage efficiency factors for this region are in the range of 1.14 to 2%. The results of the dynamic model also show that the nature of the storage zone boundary type, end point saturation and injection rate play significant role in estimation of dynamic storage capacity. These factors may induce more than 30% change in estimated dynamic storage value. The calculated storage efficiency factor may be applicable to other potential sites in this region, having similar geological characteristics.

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