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Summary of the analyses for recovery factors

Mahendra K. Verma
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Abstract

Introduction In order to determine the hydrocarbon potential of oil reservoirs within the U.S. sedimentary basins for which the carbon dioxide enhanced oil recovery (CO 2- EOR) process has been considered suitable, the CO 2 Prophet model was chosen by the U.S. Geological Survey (USGS) to be the primary source for estimating recovery-factor values for individual reservoirs. The choice was made because of the model’s reliability and the ease with which it can be used to assess a large number of reservoirs. The other two approaches—the empirical decline curve analysis (DCA) method and a review of published literature on CO 2 -EOR projects—were deployed to verify the results of the CO 2 Prophet model. This chapter discusses the results from CO 2 Prophet (chapter B, by Emil D. Attanasi, this report) and compares them with results from decline curve analysis (chapter C, by Hossein Jahediesfanjani) and those reported in the literature for selected reservoirs with adequate data for analyses (chapter D, by Ricardo A. Olea). To estimate the technically recoverable hydrocarbon potential for oil reservoirs where CO 2 -EOR has been applied, two of the three approaches—CO 2 Prophet modeling and DCA—do not include analysis of economic factors, while the third approach—review of published literature—implicitly includes economics. For selected reservoirs, DCA has provided estimates of the technically recoverable hydrocarbon volumes, which, in combination with calculated amounts of original oil in place (OOIP), helped establish incremental CO 2 -EOR recovery factors for individual reservoirs. The review of published technical papers and reports has provided substantial information on recovery factors for 70 CO 2 -EOR projects that are either commercially profitable or classified as pilot tests. When comparing the results, it is important to bear in mind the differences and limitations of these three approaches.

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Mahendra K. Verma. 2017-07-17. Summary of the analyses for recovery factors. https://doi.org/10.3133/sir20175062e

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