Important Considerations for Reserves Estimation in Unconventional Resource Plays

Abstract

Abstract Unconventional resource plays have recently been traded favorably in Acquisitions and Divestitures "A&D" markets due to view of having lower risk and or better growth prospects compared to conventional resources "Devashish, 2014". For unconventional plays, the reservoir geological boundaries usually extend beyond the limits of the acreage holding. Some of the major uncertainties in the unconventional plays reserves and resources assessment tend to be: the basis of declaration of discovery, the definition of the project boundary (technically and commercially), the categorization of reserves/resources referenced to the degree of uncertainty, and the appropriate methods to estimate the production forecasts and ultimate recovery. In this paper we present field example from unconventional resource play. The reasons for variations between different reserve estimations for the same asset (based on real case history) are explained, with recommendations for practical considerations. These include using diagnostic techniques of production data to establish production forecasts that satisfy the reasonable certainty criteria required for booking reserves. We will discuss examples for the implementation of the reserves categorization in unconventional resource plays according to the guidelines of SEC and SPE Petroleum Resources Management System "SPE-PRMS". Additionally, some practical rules for the assessment of contingent resources in unconventional plays will be discussed. It should be noted that reserves categorization in unconventional resource plays is an area that is subject to different interpretations across the industry, resulting in variations in the results of reserves estimation between different estimators. The contribution of this work is a critical discussion on these differences, and how they relate to the uncertainty on production forecasts. It is our expectation that better understanding of the uncertainty leads toward best practices for reserves estimations throughout the industry.