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Probabilistic net present value analysis for designing techno-economically optimal sequential CO2 sequestration and geothermal energy extraction

文献类型：期刊论文

作者Rajabi, Mohammad Mahdi1; Chen, Mingjie2; Javaran, Mohammad Reza Hajizadeh1; Al-Maktoumi, Ali2,3; Izady, Azizallah2; Dong, Yanhui4
刊名JOURNAL OF HYDROLOGY
出版日期2022-09-01
卷号612页码:11
关键词Depleted oil reservoir CO2 plume geothermal system Risk-aware design Hybrid Monte Carlo-genetic algorithm Neural network
ISSN号0022-1694
DOI10.1016/j.jhydrol.2022.128237
英文摘要The use of CO2 as the heat transmission fluid, increases the efficiency of geothermal energy extraction from low-enthalpy resources such as depletion oil and gas reservoirs. In the resulting so-called CO2 plume geothermal (CPG) systems, the optimal choice of well position and operational parameters represents a strategic decision problem, due to its profound effect on efficiency. Combined simulation-optimization (S-O) schemes have been recognized as a valuable tool in making these strategic decisions. Noting that the total lifespan of a CPG system consists of a 'sequestration' and a 'circulation' stage, past CPG S-O studies only focus on the circulation stage, assuming that the reservoir is initially saturated with CO2. Hence they neglect the realistic state of the reservoir following CO2 sequestration, ignore brine-based power generation, and either neglect the sequestration costs or assume that the sequestration costs are part of the fixed initial investment. This study aims to fill this gap by developing a S-O algorithm that takes into account both the sequestration and circulation stages of a CPG system lifespan in choosing optimal well location and operations. We frame the problem as a probabilistic risk-minimization scheme to allow for the consideration of geological uncertainty, and solve it through the combined application of a multi-phase numerical model, artificial neural networks, and a hybrid Monte Carlo-genetic algorithm method. Under this context, we successfully minimize the probability of having a negative net present value from the operation. We also examine the influence of economic factors on the profitability of the proposed system, and show that the net CO2 storage income is the economic variable that most affects the risk of non-profitability. Our case study involves a homogeneous, fault-blocked, inclined thin formation that is commonly present in oil and gas fields, but has been the subject of a very limited number of CPG studies.
WOS关键词COASTAL GROUNDWATER ; CPG SYSTEM ; SIMULATION ; OPTIMIZATION ; INJECTION ; STORAGE ; OUTPUT ; RATES ; WELLS
资助项目BP Oman[BP-DVC-WRC-18-01] ; Sultan Qaboos University[IG/DVC/WRC/22/02] ; Oman National Research Grant[RC/RG-DVC/WRC/21/02] ; Sultan Qaboos University, Oman[DR/RG/17]
WOS研究方向Engineering ; Geology ; Water Resources
语种英语
WOS记录号WOS:000879583800006
出版者ELSEVIER
资助机构BP Oman ; BP Oman ; Sultan Qaboos University ; Sultan Qaboos University ; Oman National Research Grant ; Oman National Research Grant ; Sultan Qaboos University, Oman ; Sultan Qaboos University, Oman ; BP Oman ; BP Oman ; Sultan Qaboos University ; Sultan Qaboos University ; Oman National Research Grant ; Oman National Research Grant ; Sultan Qaboos University, Oman ; Sultan Qaboos University, Oman ; BP Oman ; BP Oman ; Sultan Qaboos University ; Sultan Qaboos University ; Oman National Research Grant ; Oman National Research Grant ; Sultan Qaboos University, Oman ; Sultan Qaboos University, Oman ; BP Oman ; BP Oman ; Sultan Qaboos University ; Sultan Qaboos University ; Oman National Research Grant ; Oman National Research Grant ; Sultan Qaboos University, Oman ; Sultan Qaboos University, Oman
源URL[http://ir.iggcas.ac.cn/handle/132A11/107701]  
专题地质与地球物理研究所_中国科学院页岩气与地质工程重点实验室
通讯作者Chen, Mingjie
作者单位1.Tarbiat Modares Univ, Fac Civil & Environm Engn, Tehran, Iran
2.Sultan Qaboos Univ, Water Res Ctr, Muscat, Oman
3.Sultan Qaboos Univ, Dept Soils Water & Agr Engn, Muscat, Oman
4.Chinese Acad Sci, Inst Geol & Geophys, Key Lab Shale Gas & Geoengn, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Rajabi, Mohammad Mahdi,Chen, Mingjie,Javaran, Mohammad Reza Hajizadeh,et al. Probabilistic net present value analysis for designing techno-economically optimal sequential CO2 sequestration and geothermal energy extraction[J]. JOURNAL OF HYDROLOGY,2022,612:11.
APA Rajabi, Mohammad Mahdi,Chen, Mingjie,Javaran, Mohammad Reza Hajizadeh,Al-Maktoumi, Ali,Izady, Azizallah,&Dong, Yanhui.(2022).Probabilistic net present value analysis for designing techno-economically optimal sequential CO2 sequestration and geothermal energy extraction.JOURNAL OF HYDROLOGY,612,11.
MLA Rajabi, Mohammad Mahdi,et al."Probabilistic net present value analysis for designing techno-economically optimal sequential CO2 sequestration and geothermal energy extraction".JOURNAL OF HYDROLOGY 612(2022):11.

入库方式： OAI收割

来源：地质与地球物理研究所

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