Optimization Methodology of Artificial Lift Rates for Brazilian Offshore Field

Author:

Bezerra Matheus De Freitas1,Vigano Guilherme Cosme1,Giuriatto Jean Luis1

Affiliation:

1. Schlumberger

Abstract

Abstract Nowadays gas-lift is still a very expressive artificial lift method, for instance considering the whole Brazilian oil production profiles, gas lifted wells are responsible for 30% of monthly production. Due this huge importance, the injection efficiency should be ensured to avoid lid gas losses and maximize the production. Then, this study had as objective to develop a Gas Lift Optimization workflow and define the optimum lift rates to increase the reservoir recovery and improve gas usability due to platform constraints of a Brazilian deep-water field. That workflow comprises a reservoir and flow assurance simulators, achieving more accurate responses compared to regular workflows. Taking advantages of the proposed method, multidisciplinary teams could work together which increases the representativeness of such studies providing important outcomes for decision makers. At this study, due to a gas-lift optimization was observed an increase of 0.5% at cumulative production with a huge gas-lift reduction of around 40%, resulting in a better financial balance of the project, saving a considerable amount of lift-gas. The methodology adopted to optimize the injected gas lift rate and consequently increase/maintain cumulative oil production proved adequate for application in oil fields that are highly dependent on artificial lift methods. Therefore, exploration and production projects can be financial healthier.

Publisher

OTC

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

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