IMECH-IR  > 非线性力学国家重点实验室
A new method of predicting the saturation pressure of oil reservoir and its application
Yu GY; Xu F; Cui YZ; Li XL; Kang CJ; Lu C; Li SY; Bai L; Du SH(杜书恒)
Source PublicationINTERNATIONAL JOURNAL OF HYDROGEN ENERGY
2020-11-06
Volume45Issue:55Pages:30244-30253
ISSN0360-3199
AbstractSaturation pressure is a vital parameter of oil reservoir which can reflect the oilfield characteristics and determine the oilfield development process, and it is determined by experiments in the laboratory in general. However, there was only one well with saturation pressure test in this target reservoir, and it is necessary to determine whether this parameter is right or not. In this work, we present a new method for quickly determining saturation pressure using machine learning algorithms, including random forest regressor (RF), support vector machine (SVM), decision trees (DT), and artificial neural network (ANN or NN). Using these approaches, saturation pressure was obtained by using the initial solution gas-oil ratio (GOR), temperature, API gravity and other reservoir-fluid data available in the oilfields. Compared with the empirical formula for saturation pressure calculation, the calculated result shows that the accuracy given from machine learning is higher than that from other formulas at home and abroad, and has a good match with the lab test. On the basis of the calculated saturation pressure, it can determine whether the reservoir enters into the stage of dissolved gas drive or not, which also provides the basis for maintaining the reservoir pressure by water injection in advance, rational development decision-making and work over measures. This approach above can provide technical guidance for predicting the saturation pressure in the development of different kinds of reservoirs, including the sandstone reservoirs and carbonate reservoirs. (C) 2020 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
KeywordOil reservoir RANDOM FOREST Saturation pressure HETEROGENEITY Random forest Decision tree ANN Empirical formula
DOI10.1016/j.ijhydene.2020.08.042
Indexed BySCI ; EI
Language英语
WOS IDWOS:000582322100027
WOS Research AreaChemistry ; Electrochemistry ; Energy & Fuels
WOS SubjectChemistry, Physical ; Electrochemistry ; Energy & Fuels
Funding OrganizationMajor Project of China National Petroleum Corporation [2016D-4402}
Classification二类
Ranking5+
ContributorXu, F
Citation statistics
Cited Times:10[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://dspace.imech.ac.cn/handle/311007/85425
Collection非线性力学国家重点实验室
Affiliation1.{Yu Guoyi, Xu Feng, Lu Cheng, Bai Lin} China Natl Oil & Gas Explorat & Dev Co Ltd CNODC Beijing 100034 Peoples R China
2.{Xu Feng, Li Xiangling, Kang Chujuan} CNPC Res Inst Petr Explorat & Dev Co Ltd RIPED Beijing 100083 Peoples R China
3.{Cui Yingzhi} Univ New South Wales Sch Mineral Energy & Resource Engn Sydney NSW 2052 Australia
4.{Li Siyu} China Petr Technol & Dev Corp Beijing 100028 Peoples R China
5.{Du Shuheng} Chinese Acad Sci Inst Mech State Key Lab Nonlinear Mech Beijing 100190 Peoples R China
Recommended Citation
GB/T 7714
Yu GY,Xu F,Cui YZ,et al. A new method of predicting the saturation pressure of oil reservoir and its application[J]. INTERNATIONAL JOURNAL OF HYDROGEN ENERGY,2020,45,55,:30244-30253.
APA Yu GY.,Xu F.,Cui YZ.,Li XL.,Kang CJ.,...&杜书恒.(2020).A new method of predicting the saturation pressure of oil reservoir and its application.INTERNATIONAL JOURNAL OF HYDROGEN ENERGY,45(55),30244-30253.
MLA Yu GY,et al."A new method of predicting the saturation pressure of oil reservoir and its application".INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 45.55(2020):30244-30253.
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