Abstract
Carbon storage projects focusing on saline reservoirs have significant uncertainties in terms of reservoir and seal characteristics. Intelligent reservoir management of an oil and gas reservoir during primary, secondary and tertiary production phases produces an understanding of its key characteristics. Hence, the use of mature or declining oil and gas reservoirs to store CO2 significantly reduces subsurface uncertainties. EOR (enhanced oil recovery) by CO2 injection is a well-established technology for increasing oil and gas production rates and improving recovery. Considering climate concerns, using CO2 injection for the twofold purposes of EOR and CO2 sequestration/storage is an optimal choice. Our focused management clearly illustrates that an effectively managed and monitored reservoir is a superior candidate to gain from carbon dioxide injection for the twofold purposes - increasing production of hydrocarbon and CO2 sequestration. Our research focuses on carbon management involving EOR and storage for an actual oil reservoir undergoing production for several years. A variety of key analytical and numerical techniques was deployed for a synergistic investigation of a mature reservoir involving several zones. The research utilized real field data from several sources involving performance of over three decades. We determined that the reservoir had a storing capacity of about five million metric tonnes, with an additional recovery efficiency of about 11% of OOIP (original oil-in-place). We learned that by skipping the waterflooding stage adds even more tonnes of storage. In addition, constant production of aquifer also creates supplemental CO2 storage. Our research clearly identifies the huge potential for over 50 reservoirs for carbon sequestration in one region. Note that most of the reservoirs in this region contain large aquifers underneath, providing huge prospects for extra CO2 storage.
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Acknowledgment
We highly appreciate OIL India, our research sponsors, the UH Energy Division, the Energy Industry Partnership Team and the Department of PETR at the Cullen College of Engineering, UH.
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Glossary
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Arkosic sandstone: feldspar rich, relatively immature sand.
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K-means clustering: It is a data clustering or classification method where the distance between each data point and the centroid of the cluster is calculated and considered to assign that data point to a cluster.
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Dynamic time warping algorithm (DTW): It is used in time series analyses, where the use of it helps to measure similarity or dissimilarity between two temporal sequences, because these may vary in rates or speed.
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Genetic algorithm: inspired by Darwin’s Theory of Evolution in nature, the genetic algorithm simulates the process of natural selection, reproduction and mutation to produce high-quality solutions for problems that requires searching and optimization.
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Tonne: A metric unit for measuring mass, equivalent to 1,000 kg or 2,204.6 lbs.
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BBO: Billions of barrels of oil.
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Thakur, G., Bose, S., Selveindran, A. (2023). Carbon Storage Focused Reservoir Management: A Practical Example to Respond to Climate Change. In: Arai, K. (eds) Proceedings of the Future Technologies Conference (FTC) 2023, Volume 1. FTC 2023. Lecture Notes in Networks and Systems, vol 813. Springer, Cham. https://doi.org/10.1007/978-3-031-47454-5_40
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DOI: https://doi.org/10.1007/978-3-031-47454-5_40
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