Optimizing vertical and deviated wells based on advanced initialization using new productivity potential map

Ding, Shuaiwei; Lu, Rong; Xi, Yi; Ye, Jun; Liu, Guangwei; Reynolds, Albert C.; Yu, Ho‐Shing

doi:10.1016/j.petrol.2020.108263

Cited by 9 publications

(1 citation statement)

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“…Therefore, to find the optimal infilling well location efficiently and accurately, some researchers use the way of production potential map to determine. Production potential mapping [28,29] is a method developed by Cruz and Horne to simplify the optimization of infill well placement. A well is arranged in all or part of the grid of the reservoir, and a reservoir numerical simulator is run to predict the cumulative oil production of the reservoir at each well location, and the kriging interpolation method is used to obtain the cumulative oil production map, that is, the production potential map.…”

Section: Introductionmentioning

confidence: 99%

Infill Well Location Optimization Method based on Remaining Oil Recoverable Potential Evaluation

Liu,

Feng,

Zhou

et al. 2024

Preprint

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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 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 factors influencing the recoverable potential of remaining oil in such reservoirs. We characterize differences in reservoir heterogeneity, the 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 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 remaining oil potential and infill well location optimization. Results demonstrate that the assessment of remaining oil potential comprehensively characterizes the influence of reservoir physical properties and oil-water diversion capacity on 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, further optimization of infill well locations can effectively enhance reservoir development outcomes.

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Section: Introductionmentioning

confidence: 99%