Infill Well Location Optimization Method Based on Recoverable Potential Evaluation of Remaining Oil

Chen Liu, Qihong Feng (), Wensheng Zhou, Shanshan Li and Xianmin Zhang ()
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Chen Liu: School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China
Qihong Feng: School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China
Wensheng Zhou: State Key Laboratory of Offshore Oil Exploitation, Beijing 100028, China
Shanshan Li: School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China
Xianmin Zhang: School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China

Energies, 2024, vol. 17, issue 14, 1-17

Abstract: Infill well location optimization poses significant challenges due to its complexity and time-consuming nature. Currently, determining the scope of infill wells relies heavily on field engineers’ experience, often using single indices such as the remaining oil saturation or abundance of remaining oil reserves to evaluate the potential of remaining oil. However, this approach lacks effectiveness in guiding the precise tapping of remaining oil in ultra-high water cut reservoirs. To address this, our study comprehensively considers the factors influencing the recoverable potential of remaining oil in such reservoirs. We characterize the differences in reservoir heterogeneity, scale of recoverable remaining oil reserves, water flooding conditions, and oil–water flow capacity to construct a quantitative evaluation index system for the recoverable potential of remaining oil. Recognizing the varying degrees of influence of different indices on the recoverable potential of remaining oil, we determine the objective weight of each evaluation index by combining an accelerated genetic algorithm with the projection pursuit model. This approach enables the construction of a recoverable potential index for remaining oil and forms a quantitative evaluation method for the recoverable potential of remaining oil in ultra-high water cut reservoirs. Subsequently, we establish a mathematical model for infill well location optimization, integrating and optimizing the infill well location coordinates, well length, well inclination angle, and azimuth angle. Using the main layer sand body of an oilfield in Bohai as a case study, we conducted evaluations of the remaining oil potential and infill well location optimization. Our results demonstrate that the assessment of the remaining oil potential comprehensively characterizes the influence of the reservoir’s physical properties and oil–water diversion capacity on the remaining oil potential across different regional positions. This evaluation can effectively guide the determination of infill well location ranges based on the evaluation results. Furthermore, infill well location optimization can effectively enhance reservoir development outcomes.

Keywords: well location optimization; remaining oil; recoverable potential index; water flooding reservoir (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: 2024
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