Position Correction Algorithm of Well Pads When Solving the Problem of Developing Oil Fields

Author:

Kulakov Egor,Mikhalev Anton,Sarenkov Aleksandr,Shutalev Artem,Fedoreev Artem

Abstract

This article is devoted to the problem of automation of the stage of combining wells into clusters, considered as part of the process of designing the development of oil fields. The solution to the problem of combining wells into clusters is to determine the best location of well pads and the distribution of wells into clusters, in which the costs of developing and maintaining an oil field will be minimized, and the expected flow rate will be maximized. One of the currently used approaches to solving this problem is the use of optimization algorithms. At the same time, this task entails taking into account technological limitations when searching for the optimal option for the development of an oil field, justified, among other things, by the regulations in force in the industry, namely, the minimum and maximum allowable number of wells in a pad, as well as the minimum allowable distance between two well pads. The use of optimization algorithms does not always guarantee an optimal result, in which all specified constraints are met. Within the framework of this study, an algorithm is proposed that allows us to work out the resulting design solutions in order to eliminate the violated restrictions at the optimization stage. The algorithm consistently solves the following problems: violation of restrictions on the ultra-small and ultra-large number of wells in a pad; discrepancy between the number of pads with a given one; violation of the restriction of the ultra-close arrangement of pads. To study the effectiveness of the developed approach, a computational experiment was conducted on three generated synthetic oil fields with different geometries. As part of the experiment, the quality of the optimization method and the proposed algorithm, which is a raise to the optimization method, were compared. The comparison was carried out on different values of optimization power, which denotes the maximum number of runs of the target function. The evaluation of the quality of the work of the compared approaches is determined by the amount of the fine, which indicates the degree of violation of the values of the main restrictions. The efficiency criteria in this work are: the average value, the standard deviation, the median, and the minimum and maximum values of the penalty. Due to the use of this algorithm, the value of the penalty for the first and third oil fields is reduced on average to 0.04 and 0.03 respectively, and for the second oil field, the algorithm allowed to obtain design solutions without violating restrictions. Based on the results of the study, a conclusion was made regarding the effectiveness of the developed approach in solving the problem of oil field development.

Publisher

SPIIRAS

Subject

Artificial Intelligence,Applied Mathematics,Computational Theory and Mathematics,Computational Mathematics,Computer Networks and Communications,Information Systems

Reference44 articles.

1. Кутузова М. Катастрофа с надеждой на будущее // Нефть России. 2016. № 11–12. С. 28–31.

2. Нефтянка, шаг вперед. Справится ли Россия? URL: https://teknoblog.ru/2017/01/08/73260. (дата обращения: 10.10.2022).

3. Баскова М.Л. Анализ развития нефтяной отрасли России // NovaInfo.Ru. 2015. № 33. С. 76–81.

4. Фрай М.Е. Оценка современного состояния нефтяной промышленности России // Вестник Удмуртского университета. Серия «Экономика и право». 2015. № 2. С. 75–85.

5. Эдер Л.В., Филимонова И.В., Проворная И.В., Мамахатов Т.М. Состояние нефтяной промышленности России: добыча, переработка, экспорт // Минеральные ресурсы России. Экономика и управление. 2016. № 6. С. 41–51.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3