Generalized Extreme Value Statistics for Scaling Oil Recovery from Water-Wet and Mixed-Wet Carbonate Rock

Ksenia M. Kaprielova, Maxim P. Yutkin, Ahmed Gmira, Subhash Ayirala, Ali Yousef, Clayton J. Radke and Tadeusz W. Patzek ()
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Ksenia M. Kaprielova: Physical Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955, Saudi Arabia
Maxim P. Yutkin: Physical Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955, Saudi Arabia
Ahmed Gmira: The Exploration and Petroleum Engineering Center-Advanced Research Center (EXPEC ARC), Saudi Aramco, Dhahran 31311, Saudi Arabia
Subhash Ayirala: The Exploration and Petroleum Engineering Center-Advanced Research Center (EXPEC ARC), Saudi Aramco, Dhahran 31311, Saudi Arabia
Ali Yousef: The Exploration and Petroleum Engineering Center-Advanced Research Center (EXPEC ARC), Saudi Aramco, Dhahran 31311, Saudi Arabia
Clayton J. Radke: Chemical and Biomolecular Engineering Department, University of California, Berkeley, CA 94720, USA
Tadeusz W. Patzek: Physical Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955, Saudi Arabia

Energies, 2025, vol. 18, issue 21, 1-16

Abstract: Counter-current, spontaneous imbibition of brine into oil-saturated rocks is a critical process for recovery of bypassed oil in carbonate reservoirs. However, the classic Amott-cell test introduces experimental artifacts that distort the true dynamics of oil recovery, complicating the interpretation and modeling of recovery histories. In this study, we applied a modified Amott procedure to eliminate these artifacts, producing smooth and reproducible recovery histories for both water-wet and mixed-wet carbonate core plugs saturated with brine and oil. By applying Generalized Extreme Value (GEV) statistics, we modeled cumulative oil production and showed that a GEV model is able to capture the essentially non-equilibrium nature of spontaneous imbibition. Our results demonstrate that water-wet systems exhibit faster recovery rates and shorter induction times due to favorable capillary forces, while mixed-wet samples have slower dynamics and longer induction times, reflecting the influence of wettability alterations. We demonstrate that the GEV fitting parameters systematically correlate with key rock–fluid properties, such as wettability, oil viscosity, and pore network characteristics, offering a semi-quantitative approach to analyze recovery behavior. This study demonstrates the potential of a GEV-based statistical model to deepen understanding of the spontaneous imbibition mechanisms and to enhance predictive capabilities for oil production dynamics.

Keywords: spontaneous imbibition; waterflood; transition zone; amott-cell experiment; mixed-wet wettability; Generalized Extreme Value (GEV); non-equilibrium process (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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