Analog Fields Can Unlock the Secrets of a Challenging Reservoir

Analog Fields Can Unlock the Secrets of a Challenging Reservoir

This case study highlights the challenges an exploration team faced with reservoir quality and fracturing uncertainties and their approach to improving simulation accuracy.


Challenge: An exploration team faced a complex challenge with a field in Albania, a tight fractured carbonate reservoir located onshore. Despite significant interest in the field, critical uncertainties surrounding reservoir quality and fracturing metrics presented significant hurdles. The team needed to refine their assumptions about reservoir properties such as RF% and micro-scale quality in order to improve simulation models and enhance the accuracy of their analytical studies.

Solution: To overcome these obstacles, the team leveraged advanced benchmarking techniques, utilizing the cutting-edge bMark? analog field review tool. This powerful benchmarking platform enabled the identification of 26 "close" analogs from diverse regions, including Mexico, Brazil, and Iraq. These analogs provided critical insights into the previously unknown characteristics of the field's reservoir, offering a more informed starting point for the simulation and geological study.

The analogs helped constrain key inputs, such as reservoir fracturing characteristics and micro-scale reservoir quality, which were essential for refining the team's assumptions. This review of analog fields not only served as a reference but also guided the design of more accurate geological and simulation studies.

Achievements: By using the bMark? benchmarking tool and integrating analogs into the research process, the team was able to significantly improve the quality of their reservoir model. The identification of these 26 relevant analogs enabled a better understanding of the tight fractured carbonate reservoir, minimizing uncertainties and enhancing the efficiency of further geological studies. This ultimately laid the groundwork for more precise simulation models, improving the chances of success in future exploration and production activities within the field.

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