A simplified model for predicting the minimum miscibility pressure of CO2 flooding in reservoirs of the Ordos Basin

Wei Wang, Qinglong Zhu, Jian Liu, Zhenjie Yao, Shiyu Wang and Peihao Xu

PLOS ONE, 2026, vol. 21, issue 1, 1-13

Abstract: Minimum miscibility pressure (MMP) is a critical parameter in reservoir screening and development design for CO2 flooding projects. With the expanding implementation of CO2 flooding in the Ordos Basin, practical challenges have emerged, including difficulties in acquiring crude oil samples and the high cost of testing during the screening phase. Through experimental measurements and theoretical analysis, significant compositional similarities among different crude oils were revealed. Based on this finding, a simplified MMP prediction model was developed, requiring only reservoir temperature as input. Among the evaluated models, the quadratic polynomial model achieved the highest fitting accuracy (R2 = 0.841) and the smallest root mean square error (RMSE). Validation using oil samples from a candidate block for CO2 flooding yielded absolute and relative errors of 0.93 MPa and 4.93%, respectively, indicating that the model satisfies the accuracy requirements for MMP prediction and miscibility assessment in reservoir screening. The proposed method provides robust technical support for the large-scale deployment of CO2-enhanced oil recovery and storage in the Ordos Basin.

Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0339648

DOI: 10.1371/journal.pone.0339648

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