Vikram Vishal , David Lall , Yashvardhan Verma , Somali Roy , Upendra Soni , Bharath Shekar , Gaurav Mishra , Om Prakash Sinha , Kaustav Nag , T.N. Singh
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引用次数: 0
Abstract
CO2 storage is an important technology for climate change mitigation globally. While broad estimates of the storage potential of India have been reported, pore-space characterization at the reservoir scale is required for site selection. The current research is centered on India's potential pilot CCS project site, the Gandhar Field, located in India's Cambay Basin, with the primary objective of assessing its viability for CO2 storage in a saline aquifer. Our methodology encompasses seismic inversion and in-depth analysis of well-log data to delineate the distribution of porosity within the reservoir, focusing on the GS-7 sand within the Hazad Member of the Ankleshwar Formation. Leveraging probabilistic neural networks, we extrapolate the porosity for the entire reservoir volume. The results reveal that specific areas within the GS-7 sand not only meet but exceed the recommended porosity criteria (>20 %), well surpassing the globally accepted minimum standard (>10 %). We then provide a system to rank different regions in the reservoir with respect to their prospectivity for CO2 storage. Based on these results, we have characterized the GS-7 sand in the Hazad Member as a prospective reservoir zone for CO2 storage.
期刊介绍:
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