Progress of the research on productivity prediction methods for stimulated reservoir volume (SRV)-fractured horizontal wells in unconventional hydrocarbon reservoirs
被引:11
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作者:
Ren, Long
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机构:
Xian Shiyou Univ, Sch Petr Engn, Xian 710065, Shaanxi, Peoples R China
Shaanxi Key Lab Adv Stimulat Technol Oil & Gas Re, Xian 710065, Shaanxi, Peoples R ChinaXian Shiyou Univ, Sch Petr Engn, Xian 710065, Shaanxi, Peoples R China
Ren, Long
[1
,2
]
Su, Yuliang
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机构:
China Univ Petr East China, Sch Petr Engn, Qingdao 266580, Peoples R ChinaXian Shiyou Univ, Sch Petr Engn, Xian 710065, Shaanxi, Peoples R China
Su, Yuliang
[3
]
Zhan, Shiyuan
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机构:
China Univ Petr East China, Sch Petr Engn, Qingdao 266580, Peoples R ChinaXian Shiyou Univ, Sch Petr Engn, Xian 710065, Shaanxi, Peoples R China
Zhan, Shiyuan
[3
]
Meng, Fankun
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机构:
PetroChina Res Inst Petr Explorat & Dev, Beijing 100083, Peoples R ChinaXian Shiyou Univ, Sch Petr Engn, Xian 710065, Shaanxi, Peoples R China
Meng, Fankun
[4
]
机构:
[1] Xian Shiyou Univ, Sch Petr Engn, Xian 710065, Shaanxi, Peoples R China
[2] Shaanxi Key Lab Adv Stimulat Technol Oil & Gas Re, Xian 710065, Shaanxi, Peoples R China
[3] China Univ Petr East China, Sch Petr Engn, Qingdao 266580, Peoples R China
[4] PetroChina Res Inst Petr Explorat & Dev, Beijing 100083, Peoples R China
Further development of stimulated reservoir volume (SRV)-fracturing technologies for horizontal wells is necessary to address the current situation of decreasing energy production from conventional sources and continuous increases in the proportion of alternative energy sources (unconventional hydrocarbons). To this end, the theoretical productivity prediction methods used for SRV-fractured horizontal wells must be studied. In this article, based on a structural description of hydraulic fracture networks around horizontal wells, we summarize and evaluate various types of productivity prediction models built by researchers using analytical, semi-analytical, and numerical methods. We find that while these models are convenient and efficient, analytical models are overly ideal and differ considerably from actual fracture network patterns. We also find that semi-analytical models offer high computational accuracy but are applicable only to the prediction of single-well single-phase productivity. Furthermore, numerical models can address more complex fracture network patterns and can be used to calculate the multi-phase productivity of well patterns but involve a complex initial input process. On this basis, we summarize the problems and challenges associated with the existing productivity prediction models and specify five pertinent key techniques involved in building more accurate productivity prediction models: the techniques for describing complex fracture network structures; the technique for simulating multi-phase flows in reservoirs; the multi-scale multi-field flow coupling theory; the technique for calculating numerical solutions for complex models; and the technique for matching well type, well pattern, and fracture network systems.
机构:
China Univ Petr, Sch Petr Engn, Qingdao 266580, Peoples R ChinaChina Univ Petr, Sch Petr Engn, Qingdao 266580, Peoples R China
Jiang, Ruizhong
Xu, Jianchun
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China Univ Petr, Sch Petr Engn, Qingdao 266580, Peoples R ChinaChina Univ Petr, Sch Petr Engn, Qingdao 266580, Peoples R China
Xu, Jianchun
Sun, Zhaobo
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机构:
China Univ Petr, Sch Petr Engn, Qingdao 266580, Peoples R ChinaChina Univ Petr, Sch Petr Engn, Qingdao 266580, Peoples R China
Sun, Zhaobo
Guo, Chaohua
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机构:
Missouri Univ Sci & Technol, Dept Geol Sci & Engn, Rolla, MO 65409 USAChina Univ Petr, Sch Petr Engn, Qingdao 266580, Peoples R China
Guo, Chaohua
Zhao, Yulong
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机构:
Southwest Petr Univ, State Key Lab Oil & Gas Reservoir Geol & Exploita, Chengdu 610500, Peoples R ChinaChina Univ Petr, Sch Petr Engn, Qingdao 266580, Peoples R China
机构:
Southwest Petr Univ, Sch Sci, Chengdu 610500, Sichuan, Peoples R ChinaSouthwest Petr Univ, Sch Sci, Chengdu 610500, Sichuan, Peoples R China
Ren, Junjie
Guo, Ping
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Southwest Petr Univ, State Key Lab Oil & Gas Reservoir Geol & Exploita, Chengdu 610500, Sichuan, Peoples R ChinaSouthwest Petr Univ, Sch Sci, Chengdu 610500, Sichuan, Peoples R China
机构:
Southwest Petr Univ, State Key Lab Oil & Gas Reservoir Geol & Exploita, Chengdu 610500, Peoples R ChinaSouthwest Petr Univ, State Key Lab Oil & Gas Reservoir Geol & Exploita, Chengdu 610500, Peoples R China
Xu, Youjie
Li, Xiaoping
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Southwest Petr Univ, State Key Lab Oil & Gas Reservoir Geol & Exploita, Chengdu 610500, Peoples R ChinaSouthwest Petr Univ, State Key Lab Oil & Gas Reservoir Geol & Exploita, Chengdu 610500, Peoples R China
Li, Xiaoping
Liu, Qiguo
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Southwest Petr Univ, State Key Lab Oil & Gas Reservoir Geol & Exploita, Chengdu 610500, Peoples R ChinaSouthwest Petr Univ, State Key Lab Oil & Gas Reservoir Geol & Exploita, Chengdu 610500, Peoples R China
机构:
Res Inst Petr Explorat & Dev, Beijing 100083, Peoples R China
Sinopec Star Beijing New Energy Res Inst Co Ltd, Beijing 100083, Peoples R ChinaRes Inst Petr Explorat & Dev, Beijing 100083, Peoples R China
Wang, Qiang
Wan, Jifang
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机构:
Res Inst Petr Explorat & Dev, Beijing 100083, Peoples R China
CNPC Engn Technol R&D Co Ltd, Beijing 102206, Peoples R ChinaRes Inst Petr Explorat & Dev, Beijing 100083, Peoples R China
Wan, Jifang
Mu, Langfeng
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机构:
Missouri Univ Sci & Technol, Rolla, MO 65409 USA
Chinese Acad Geol Sci, Beijing 100037, Peoples R ChinaRes Inst Petr Explorat & Dev, Beijing 100083, Peoples R China
Mu, Langfeng
Shen, Ruichen
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机构:
CNPC Engn Technol R&D Co Ltd, Beijing 102206, Peoples R ChinaRes Inst Petr Explorat & Dev, Beijing 100083, Peoples R China
Shen, Ruichen
Jurado, Maria Jose
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机构:
CSIC, Inst Earth Sci Jaume Almera, E-08028 Barcelona, SpainRes Inst Petr Explorat & Dev, Beijing 100083, Peoples R China
Jurado, Maria Jose
Ye, Yufeng
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机构:
Natl Oil & Gas Explorat & Dev Co Ltd, Beijing 100034, Peoples R ChinaRes Inst Petr Explorat & Dev, Beijing 100083, Peoples R China