A Sensitivity Study of Potential CO2 Injection for Enhanced Gas Recovery in Barnett Shale Reservoirs

Abstract

Abstract Shale gas production has been gaining worldwide attention over the past several years. This is due to the economic gas reserves using two current advanced technologies that are horizontal drilling and multistage hydraulic fracturing. Shale has a high total organic content (TOC) that may adsorb significant amount of natural gas. In addition, laboratory and theoretical calculations indicate that organic-rich shales adsorb CO2 preferentially over CH4. Hence, the extent of organic matter in shale plays an important role in determining the feasibility of CO2 injection with potential benefit of enhanced gas recovery (EGR). The performance of CO2 injection and CH4 recovery in shale reservoirs is a complex function of several engineering parameters including fracture half-length, fracture conductivity, and fracture height, operating parameters such as injection volume and injection time, and geologic parameters including reservoir permeability, porosity, and thickness. Nevertheless, the effects of the above uncertain parameters on the process of CO2-EGR are not clearly understood and systematically studied. Therefore, it is absolutely critical to quantify uncertainties and investigate the most important influential parameters controlling this process. In this paper, we employ numerical reservoir simulation techniques to model multiple hydraulic fractures and multi-component Langmuir isotherms. Two scenarios for CO2 injection are investigated when the primary gas production decreases to the economic limit: (1) CO2 flooding in two horizontal wells, and (2) CO2 huff-n-puff in a horizontal well. A series of reservoir simulations based on Design of Experiment (DOE) are performed on the best scenario to investigate the critical parameters that control this CO2-EGR process in the Barnett Shale. This work enables operators to plan ahead of time and optimize a tertiary shale gas production process by considering the different investigated influential parameters.