海上气田群一体化闭环优化配产研究

闫正和

doi:10.3969/j.issn.1006-6535.2022.03.013

特种油气藏 >

2022 , Vol. 29 >Issue 3: 92 - 97

DOI: https://doi.org/10.3969/j.issn.1006-6535.2022.03.013

油藏工程

海上气田群一体化闭环优化配产研究

闫正和

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中海石油(中国)有限公司深圳分公司,广东深圳 518000

闫正和(1965—),男,高级工程师,1988年毕业于西安石油学院油田开发专业,2017毕业于中国石油大学(北京)油气田开发工程专业,获硕士学位,现从事油藏研究及管理、动态分析、油气田开发评价相关研究工作。

收稿日期: 2021-05-08

修回日期: 2022-03-07

网络出版日期: 2023-01-09

基金资助

国家科技重大专项“近海大中型油气田形成条件及勘探技术”(2016ZX05024);中海石油(中国)有限公司深圳分公司科技项目“南海东部低渗储层产能评价与提升技术研究”(CCL2018SZPS0306)

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Study on Integrated Closed-Loop Optimal Production Allocation of Offshore Gas Field Clusters

Yan Zhenghe

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CNOOC Shenzhen Branch, Shenzhen, Guangdong 518000, China

Received date: 2021-05-08

Revised date: 2022-03-07

Online published: 2023-01-09

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摘要

为实现海上气田群联合开发过程中单井科学高效配产,优化气田开发决策,利用集合卡尔曼滤波数据同化方法拟合气田群实时生产和监测数据,获得预测结果与生产动态一致的气田群地质模型。以4个气田群联合开发的累计产气量为目标函数,采用数值模拟技术和粒子群算法进行气田群联合配产智能优化。研究结果表明,智能优化方案10 a累计产气为19.1×10⁸m³,较人工配产方案提高了4.2%,产能优化效果显著。该研究有效提高了开发效果,可为其他复杂油气田高效开发及储气库建设等提供了技术支持和案例参考。

关键词： 气田群; 联合配产; 闭环优化; 集合卡尔曼滤波; 粒子群算法

本文引用格式

闫正和 . 海上气田群一体化闭环优化配产研究[J]. 特种油气藏, 2022 , 29(3) : 92 -97 . DOI: 10.3969/j.issn.1006-6535.2022.03.013

Abstract

In order to achieve scientific and efficient production allocation of single wells and optimize gas field development decisions in the joint development of offshore gas field clusters, real-time production and monitoring data of gas field clusters were fitted by ensemble Kalman filter data assimilation method to obtain a geological model of gas field clusters with prediction results consistent with production performance. Taking the cumulative gas production of the four gas field clusters as the objective function, numerical simulation technologies and particle swarm algorithms were employed to realize intelligent optimization of production allocation for the clusters. The study results showed that the cumulative gas production in 10 years was 19.1×10⁸m³ after intelligent scheme optimization, which was 4.2% higher than that of the manual production allocation scheme, presenting a remarkable effect in productivity optimization. The study effectively improved the development efficiency, and provides technical support and case reference for the efficient development of other complex oil and gas fields and the construction of gas storage.

Key words： gas field group; joint production allocation; closed-loop optimization; ensemble Kalman filter; particle swarm optimization

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