Abstract
Abstract Mining optimization in oil and gas industry has been an important task. The production volume of oil and gas crucially depends on many factors. One of them is wells location. This study contributes to the domain of oil and gas exploration and extraction. We solve the problem of optimal wells placement on 2-D surface. We have developed a set of criteria and chosen a proportion of the field covered as objective function. In order to find the best solution satisfying these criteria, we compared different optimization algorithms. Such as, Nelder-Mead method, simulated annealing, Bayesian optimization and genetic algorithm in order to reach the maximal surface coverage with minimal number of wells in a region. To test the application of the developed algorithm on complex polygons (oil fields), we have made a generator of synthetic polygons. In this study we also compare the efficiency of regular and irregular wells placement.
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