B-Factor Variation in the Application of Traditional Decline Curve Analysis in Unconventional Wells

Abstract This paper focuses on investigating the applicability of using the traditional Arps Decline Curve Analysis (DCA) in unconventional resources characterized by rapid decline rates. The study focuses on the variability of the b-factor at different stages of the production life cycle and provides a sensitivity study on the magnitude of change the b-factor has on the Estimated Ultimate Recovery (EUR) of unconventional wells. The methodology adapted in this paper utilizes a reservoir simulator to run multiple DCA scenarios on an application example, providing both a quantitative and a visualized sensitivity analysis of EUR forecasts driven by multiple b-factor values. The production of the application example well was segmented to account for well clean-up post stimulation, and various operational changes throughout the life of the well. Traditional DCA was applied on the segments that most represented the general performance of the well, then benchmarked against an EUR value obtained using Rate Transient Analysis (RTA) utilizing the same reservoir simulator. During the process, the b-factor was varied to achieve the best fit with production data that yielded the lowest error. Two different scenarios were studied. The first scenario applied traditional DCA on all production data without segmentation, while the other scenario was applied on selected intervals where well behavior was considered relatively stable. Both scenarios underwent a sensitivity study estimating EUR at four different b-factor values: 0.82, 1.0, 1.5 and 2.0. It was observed, for the first scenario, that EUR estimates were far from accurate when benchmarked against RTA results, attributed to the initial rapid decline and multiple transitional periods during the production life cycle. On the other hand, for the second scenario, when only the representative segments of the well were accounted for, results were comparable to that of RTA, with a perfect match using a b-factor value of 1.5. The findings from this assessment were indicative in qualifying the traditional DCA for use in an unconventional setting provided that operating conditions are understood, and intervals considered in the forecast are filtered towards a representative well behavior. The novelty of this work lies in studying the application of traditional Arps DCA in unconventional hydrocarbon resources, generally perceived as a challenging approach due to rapid changes in well behavior. The study investigated and confirmed the feasibility of applying the traditional Arps DCA in unconventional wells through introducing an intermediate step, to segment the production life and analyzing the representative portion of the production life cycle.