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     2026:7/2

International Journal of Multidisciplinary Research and Growth Evaluation

ISSN: (Print) | 2582-7138 (Online) | Impact Factor: 9.54 | Open Access

Elastic inversion as a key to understanding reservoir dynamics: A conceptual model for 4D seismic interpretation in oilfields

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Abstract

Elastic inversion has emerged as a pivotal technique in reservoir characterization, offering unparalleled insights into subsurface dynamics, particularly in the context of 4D seismic interpretation. This approach integrates seismic data with rock physics principles to extract elastic properties such as P-wave velocity, S-wave velocity, and density, which are critical for understanding reservoir dynamics. By linking time-lapse (4D) seismic data to changes in reservoir conditions, including pressure, saturation, and temperature, elastic inversion enables precise monitoring of reservoir evolution during production. This conceptual model emphasizes the integration of elastic inversion into 4D seismic workflows to enhance reservoir management in oilfields. The methodology leverages advancements in geophysical computing and machine learning to process vast datasets, improving the resolution and accuracy of elastic property estimates. This framework incorporates a three-step approach: preconditioning of seismic data for noise reduction, inversion to derive elastic properties, and interpretation to correlate elastic variations with reservoir dynamics. A key advantage of elastic inversion in 4D seismic interpretation is its ability to delineate subtle changes in reservoir conditions that may be undetectable using conventional techniques. For example, the identification of water encroachment, gas cap expansion, and bypassed hydrocarbons is significantly improved, leading to optimized production strategies and enhanced recovery. Furthermore, elastic inversion offers a robust foundation for integrating seismic data with reservoir simulation models, fostering a more holistic understanding of subsurface processes. This study underscores the importance of adopting elastic inversion as a core component of modern reservoir monitoring practices. By addressing challenges such as data quality, computational efficiency, and interpretation uncertainties, this conceptual model provides a pathway for the practical application of elastic inversion in oilfield settings.

How to Cite This Article

Elemele Ogu, Peter Ifechukwude Egbumokei, Iki omoworio Nicholas Dienagha, Wags Num oipiri Digitemie (2023). Elastic inversion as a key to understanding reservoir dynamics: A conceptual model for 4D seismic interpretation in oilfields . International Journal of Multidisciplinary Research and Growth Evaluation (IJMRGE), 4(1), 724-736. DOI: https://doi.org/10.54660/.IJMRGE.2023.4.1.724-736

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