Author
Listed:
- Odoh, Benard Ifeanyi
(Department of Geophysics, Faculty of Physical Sciences, Nnamdi Azikiwe University Awka)
- Nwokeabia, Charity Nkiru
(Department of Geophysics, Faculty of Physical Sciences, Nnamdi Azikiwe University Awka)
Abstract
This article explores the integration of geophysics and rock physics for enhanced reservoir characterization, a synergy that has revolutionized the oil and gas industry’s approach to subsurface analysis. By combining advanced geophysical techniques with rock physics principles, operators can improve reservoir property predictions by up to 40%, leading to more accurate resource estimates and optimized production strategies. The integration of these disciplines has shown to increase drilling success rates from an industry average of 30% to over 50% in complex geological settings. Furthermore, this approach has demonstrated potential cost savings of 15-25% in field development plans by reducing the number of unnecessary wells and optimizing well placement. We discuss key methodologies, including multi-attribute analysis and machine learning applications, which have improved reservoir property predictions by 30-50% compared to traditional methods. Case studies highlight successful implementations, including a North Sea project where integrated analysis led to a 20% increase in recoverable reserves estimates. The article also addresses emerging trends, such as real-time monitoring and 4D seismic, which promise to further enhance reservoir management, potentially increasing recovery factors by 5-10% over the life of a field. By adopting these integrated approaches, the industry stands to unlock significant value, with potential economic benefits estimated at $10-15 billion annually across global operations.
Suggested Citation
Odoh, Benard Ifeanyi & Nwokeabia, Charity Nkiru, 2024.
"Synergy in the Subsurface: Revolutionizing Reservoir Characterization through Integrated Geophysics and Rock Physics,"
International Journal of Research and Innovation in Applied Science, International Journal of Research and Innovation in Applied Science (IJRIAS), vol. 9(8), pages 756-764, August.
Handle:
RePEc:bjf:journl:v:9:y:2024:i:8:p:756-764
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