Study Illustrates Evolution of EUR Estimates Over Project Life Cycle
Authors: Carpenter Chris 
Published: December 2024

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This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 215224, “The Evolution of Estimated Ultimate Recovery Estimates Over the Project Life Cycle: Lessons Learned From Three Examples,” by Wenbin Nah, SPE, and Peter A. Adam, SPE, Gaffney, Cline & Associates. The paper has not been peer reviewed.

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The complete paper presents examples covering both gas and oil fields at different stages that show how estimated ultimate recovery (EUR) and the corresponding range of EUR uncertainty vary over the life of each field. The lesson from these examples is that the range of uncertainty tends to be too narrow, both in the appraisal phase and in the production phase. It is, therefore, important for technical personnel, management, investors, and lenders to keep an open mind and not be guided into overly narrow ranges of uncertainty.

Presentation of Data and Results

This paper outlines three real-life examples of the evolution of EUR estimates over the entire life cycle of a project, focusing on the evolution in the range of EUR uncertainty, and identifies the learnings that can be drawn from these examples. The first and third of the following examples are included in this synopsis.

- Field 1A and 1B are a cluster of dry gas fields. Field 1A illustrates the evolution of EUR after a field is put on production, while Field 1B better illustrates the effects of preproduction appraisal activities.

- Field 2 is an oil field developed in two stages and illustrates how EUR is affected by development assumptions and evolving analytical procedures.

- Field 3 is a large, mature legacy gas field close to abandonment, and illustrates reasons why EUR may deviate from the previously established range.

Example 1.

A cluster of two dry gas fields is considered, with less than 2 km separating the fields. Field 1A is a shallow clastic dry gas field with excellent reservoir properties. Field 1B is adjacent to Field 1A in a limestone formation directly overlaying the clastic formation of Field 1A. Faults have been interpreted to run across both fields, and moderate aquifer drive is expected for both. The fields are jointly developed through the same offshore infrastructure.

When the EUR of the two fields is aggregated through simple arithmetic addition, the EUR estimate of these two fields narrows in a broadly consistent manner over time, in line with the idealized narrowing of the EUR trend from the appraisal phase.

When these EUR estimates are normalized against the best-case EUR estimate for each year, the range of uncertainty relative to the best-case EUR of each year is approximately –30%/+40% for the low/high case initially and narrows over time as more data is acquired. The authors write that the learnings derived from this first example include the following:

- When the results of the two fields are aggregated, the chance of the ideal narrowing of the EUR range is higher because the effect of short-term local fluctuations is minimized.

- The fact that the results trend to the best case over time is a testament to the good overall quality of technical work, in the authors’ opinion, conducted on this field because the estimates that were made early and during the life of the field eventually were validated by production results.