A new method to production prediction for the shale gas reservoir

doi:10.1080/15567036.2020.1779876

	A new method to production prediction for the shale gas reservoir
	Li, Ting 2,5,6; Tan, Yongsheng 1,3; Ahmad, Faraj A.2; Liu, Haiyan 4
刊名	ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS
	2020-06-18
页码	14
关键词	BP neural-network controlling factors principal component analysis production analysis shale gas
ISSN号	1556-7036
DOI	10.1080/15567036.2020.1779876
英文摘要	It is a common phenomenon that shale gas production differs significantly among wells, and it is difficult to find a relationship between engineering variables and gas rate by utilizing a simple plotting of production data against well and treatment variables. Data such as completion method, flow back, and gas production have been collected for 180 shale gas wells. Firstly, the collected data were standardized, and then related or dependent variables were removed by gray correlation analysis. Finally, principal component analysis and BP Neural-network methods are applied separately to analyze the collected data. It is the first-of-its-kind study that was conducted to define the relationship between gas production and engineering parameters for Fuling shale gas reservoir in China. By use of principal component analysis, it is concluded that the number of stages, the lateral length, the distance between clusters, and the average volume of slick-water are the main factors that impact shale gas production. The results showed that stage numbers account for 42.9% of the total variance, while the horizontal length accounts for about 21.4%; therefore, these two factors account for 64.3% among all of the factors. However, the next important factors are the average distance between clusters and the average volume of slick-water, both account for 24.1% of the total variance. The importance of each variable was also defined by the BP Neural-network method. The number of stages and the horizontal length are still the two major factors, and both account for 52%. The volume of slick-water and the proppant size of 40/70 mesh for both ceramic and sand are considered the second important factor and both account for 37%. This implies that shale gas well configuration and treatment parameters are the dominant factors for gas production in shale reservoirs. Therefore, in order to enhance gas production, it is crucial to increase the number of stages and horizontal length firstly and to raise the volume of slick-water by using 40/70 mesh for both ceramic and sand. However, another driver to accelerate production is to decrease the distance of clusters. These measures will be helpful to improve production in the future shale gas development of Fuling reservoir. This study is believed to be the first-of-its-kind to define the relationship between gas production and engineering parameters for Fuling shale gas reservoir in China.
资助项目	China Scholarship Council[201908420098] ; Major National Science and Technology Projects[2016ZX05060-019] ; Open Fund of State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation (Chengdu University of Technology)[PLC20190703]
WOS研究方向	Energy & Fuels ; Engineering ; Environmental Sciences & Ecology
语种	英语
出版者	TAYLOR & FRANCIS INC
WOS记录号	WOS:000545721400001
内容类型	期刊论文
源URL	[http://119.78.100.198/handle/2S6PX9GI/24495]
专题	中科院武汉岩土力学所
通讯作者	Tan, Yongsheng
作者单位	1.Univ Chinese Acad Sci, Beijing, Peoples R China 2.Colorado Sch Mines, Petr Engn Dept, Golden, CO 80401 USA 3.Chinese Acad Sci, Inst Rock & Soil Mech, State Key Lab Geomech & Geotech Engn, Wuhan, Hubei, Peoples R China 4.Ningbo Fengcheng Adv Energy Mat Res Inst, Ningbo, Peoples R China 5.Yangtze Univ, Petr Engn Coll, Wuhan, Peoples R China 6.Chengdu Univ Technol, State Key Lab Oil & Gas Reservoir Geol & Exploit, Chengdu, Peoples R China
推荐引用方式 GB/T 7714	Li, Ting,Tan, Yongsheng,Ahmad, Faraj A.,et al. A new method to production prediction for the shale gas reservoir[J]. ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS,2020:14.
APA	Li, Ting,Tan, Yongsheng,Ahmad, Faraj A.,&Liu, Haiyan.(2020).A new method to production prediction for the shale gas reservoir.ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS,14.
MLA	Li, Ting,et al."A new method to production prediction for the shale gas reservoir".ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS (2020):14.