The continuous rise of CO2 concentration in the atmosphere has a series of negative impacts on the Earth's climate and environment, such as rising temperatures, ocean acidification, forest fires, and increased frequency of extreme weather events. Therefore, as a bottom-line method to reduce CO2 content, carbon sequestration technology will play an increasingly important role in mitigating climate change. During the process of CO2 injection in carbon storage, the migration behavior and specific state of CO2 are closely related to formation pressure. Obtaining formation pressure facilitates better reservoir prediction and flow monitoring, while also providing information for formation stability (e.g., calculating geomechanical parameters such as in-situ stress). Considering the characteristics of shallow offshore reservoir (typically loose in texture and mostly unconsolidated), a rock physics model is proposed to calculate the formation pressure more accurately. This rock physics model considered multiple influencing factors, including various mineral compositions, fluid distribution condition and formation pressure. Through the use of a field data in China, the forward modeling results generated by the rock physics model are used to form the training dataset for Deep Belief Network (DBN). Then the formation pressure is calculated by the trained DBN. The proposed approach yields a notably small error. This method enables the rapid calculation method of formation pressure, providing indispensable information and a reliable basis for late-stage site selection, fluid flow monitoring, and safety assessment for CO2 storage.
Keywords
Natural gas hydrates; CO2-CH4 replacement; CO2 sequestration; continuous CO2 injection; dual-well injection-production
Speaker
Fan Wu
assistant researcherBeijing Huairou Laboratory
Submission Author
Fan WuBeijing Huairou Laboratory
Qingping LiBeijing Huairou Laboratory
Haishan ZhuBeijing Huairou Laboratory;China National Offshore Oil Corporation Research Institute Co. Ltd
Chuiqian MengBeijing Huairou Laboratory
Ting ZhouBeijing Huairou Laboratory
Jinqiu YuChina University of Petroleum-Beijing;Beijing Huairou Laboratory
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