International Journal of Multidisciplinary Research and Growth Evaluation  |  ISSN (Online): 2582-7138  |  Double-Blind Peer Review  |  Open Access  |  CC BY 4.0

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International Journal of Multidisciplinary Research and Growth Evaluation

ISSN (Online): 2582-7138 | Open Access

Data Driven Reservoir Performance Evaluation Supporting Better Redevelopment Strategies for Mature Oilfields

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Volume: 1 | Issue: 5 | Pages: 468-482

Subject: Engineering

Country: Nigeria

DOI: https://doi.org/10.54660/IJMRGE.2020.1.5.468-482

License: CC BY 4.0

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Abstract

Data-driven reservoir performance evaluation plays a pivotal role in optimizing redevelopment strategies for mature oilfields. As many oilfields age, the challenge of maximizing recovery from existing reservoirs intensifies, requiring more advanced and precise approaches. Traditional methods often lack the depth of insight necessary to guide effective decision-making in redevelopment projects. However, the integration of data analytics, machine learning, and advanced reservoir simulation models has revolutionized the field by providing a more comprehensive understanding of reservoir behavior and its evolving dynamics. By utilizing historical production data, seismic data, well performance metrics, and geophysical information, data-driven methodologies offer real-time insights that help identify underperforming zones, optimize well placement, and predict future production trends. This integrated approach allows for a more targeted and cost-effective redevelopment strategy. The application of machine learning algorithms to large datasets enables the identification of patterns and anomalies that traditional methods may overlook, thus facilitating a more efficient allocation of resources. Data-driven evaluation also aids in reducing the uncertainty associated with reservoir predictions, improving the accuracy of redevelopment forecasts. Through continuous monitoring and adaptive modeling, operators can adjust redevelopment plans based on changing conditions, mitigating risks and enhancing the long-term profitability of mature fields. Furthermore, this approach fosters sustainable development by optimizing recovery rates while minimizing environmental impact, as it facilitates more precise control over extraction techniques and reduces unnecessary intervention. In conclusion, leveraging data-driven reservoir performance evaluation represents a significant advancement in the management of mature oilfields. It supports better redevelopment strategies, leading to improved operational efficiency, reduced costs, and maximized resource recovery. As the oil and gas industry continues to focus on innovation and sustainability, data analytics will play an increasingly crucial role in shaping the future of mature field redevelopment.

How to Cite This Article

Lymmy Ogbidi, Benneth Oteh (2020). Data Driven Reservoir Performance Evaluation Supporting Better Redevelopment Strategies for Mature Oilfields . International Journal of Multidisciplinary Research and Growth Evaluation (IJMRGE), 1(5), 468-482. DOI: https://doi.org/10.54660/IJMRGE.2020.1.5.468-482

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Journal: International Journal of Multidisciplinary Research and Growth Evaluation (IJMRGE)

Publisher: Anfo Publication House

ISSN: 2582-7138 (Online)

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Language: English

Open Access: Yes - This article is distributed under the terms of the Creative Commons Attribution 4.0 International License

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