Well-Placement Optimization in Heavy Oil Reservoirs Using a Novel Method of In Situ Steam Generation

Author:

Moussa Tamer12,Mahmoud Mohamed12,Mokheimer Esmail M. A.345,Habib Mohamed A.6,Elkatatny Salaheldin12

Affiliation:

1. Petroleum Engineering Department, College of Petroleum Engineering and Geosciences, King Fahad University of Petroleum and Minerals (KFUPM), P. O. Box: 5049, Dhahran 31261, Saudi Arabia;

2. Center for Integrative Petroleum Research, College of Petroleum Engineering and Geosciences, King Fahad University of Petroleum and Minerals (KFUPM), P. O. Box: 5049, Dhahran 31261, Saudi Arabia e-mail:

3. Mem. ASME Mechanical Engineering Department, College of Engineering, King Fahd University of Petroleum and Minerals (KFUPM), P. O. Box: 279, Dhahran 31261, Saudi Arabia;

4. Center of Research Excellence in Energy Efficiency (CEEE), King Fahd University of Petroleum and Minerals (KFUPM), P. O. Box: 279, Dhahran 31261, Saudi Arabia;

5. Center of Research Excellence in Renewable Energy (CoRe-RE), King Fahd University of Petroleum and Minerals (KFUPM), P. O. Box: 279, Dhahran 31261, Saudi Arabia e-mail:

6. Mechanical Engineering Department, College of Engineering, King Fahd University of Petroleum and Minerals (KFUPM), P. O. Box: 1866, Dhahran 31261, Saudi Arabia e-mail:

Abstract

Determination of optimal well locations plays an important role in the efficient recovery of hydrocarbon resources. However, it is a challenging and complex task. The objective of this paper is to determine the optimal well locations in a heavy oil reservoir under production using a novel recovery process in which steam is generated, in situ, using thermochemical reactions. Self-adaptive differential evolution (SaDE) and particle swarm optimization (PSO) methods are used as the global optimizer to find the optimal configuration of wells that will yield the highest net present value (NPV). This is the first known application, where SaDE and PSO methods are used to optimize well locations in a heavy oil reservoir that is recovered by injecting steam generated in situ using thermo-chemical reactions. Comparison analysis between the two proposed optimization techniques is introduced. On the other hand, laboratory experiments were performed to confirm the heavy oil production by thermochemical means. CMG STARS simulator is utilized to simulate reservoir models with different well configurations. The experimental results showed that thermochemicals, such as ammonium chloride along with sodium nitrate, can be used to generate in situ thermal energy, which efficiently reduces heavy-oil viscosity. Comparison of results is made between the NPV achieved by the well configuration proposed by the SaDE and PSO methods. The results showed that the optimization using SaDE resulted in 15% increase in the NPV compared to that of the PSO after 10 years of production under in situ steam injection process using thermochemical reactions.

Publisher

ASME International

Subject

Geochemistry and Petrology,Mechanical Engineering,Energy Engineering and Power Technology,Fuel Technology,Renewable Energy, Sustainability and the Environment

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