| 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)
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| Source Publication | INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
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| 2020-11-06 | |
| Volume | 45Issue:55Pages:30244-30253 |
| ISSN | 0360-3199 |
| Abstract | Saturation 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. |
| Keyword | Oil reservoir RANDOM FOREST Saturation pressure HETEROGENEITY Random forest Decision tree ANN Empirical formula |
| DOI | 10.1016/j.ijhydene.2020.08.042 |
| Indexed By | SCI ; EI |
| Language | 英语 |
| WOS ID | WOS:000582322100027 |
| WOS Research Area | Chemistry ; Electrochemistry ; Energy & Fuels |
| WOS Subject | Chemistry, Physical ; Electrochemistry ; Energy & Fuels |
| Funding Organization | Major Project of China National Petroleum Corporation [2016D-4402} |
| Classification | 二类 |
| Ranking | 5+ |
| Contributor | Xu, F |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://dspace.imech.ac.cn/handle/311007/85425 |
| Collection | 非线性力学国家重点实验室 |
| Affiliation | 1.{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.Rp_Au:Xu, F |
| 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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| Jp2020383.pdf（1920KB） | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | View Download | |
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