A Novel Continuous Fracture Network Model: Formation Mechanism, Numerical Simulation, and Field Application
After a shale gas reservoir is fractured, hydraulic fractures interweave with natural fractures to form a fracture network. Numerical simulation based on the continuous fracture network model is a relatively economical and convenient method to predict fracture network morphology and size in the fiel...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
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| Series: | Geofluids |
| Online Access: | http://dx.doi.org/10.1155/2022/4026200 |
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| _version_ | 1832553591199498240 |
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| author | Zixi Guo Jinzhou Zhao Xinhao Sun Chengwang Wang Dali Guo Haoran Hu Hongna Wang Qinggang Zeng |
| author_facet | Zixi Guo Jinzhou Zhao Xinhao Sun Chengwang Wang Dali Guo Haoran Hu Hongna Wang Qinggang Zeng |
| author_sort | Zixi Guo |
| collection | DOAJ |
| description | After a shale gas reservoir is fractured, hydraulic fractures interweave with natural fractures to form a fracture network. Numerical simulation based on the continuous fracture network model is a relatively economical and convenient method to predict fracture network morphology and size in the field application. However, some important factors, such as fracture height variation and filtration loss, have not been considered in the past continuous fracture network models. Therefore, this paper is aimed at establishing a novel continuous fracture network model to improve simulation accuracy. Firstly, this paper established a method to judge whether natural fractures develop or not. Then, a novel continuous fracture network model considering fracture height variation and asymmetry, filtration loss, fluid flow, and other key factors was established, and the forward algorithm and inverse algorithm of the model were proposed. At last, this model was applied in a field case to verify accuracy, and the average accuracy is more than 90%. Compared with the traditional Meyer software, the average error of prediction was reduced by 7.86%. |
| format | Article |
| id | doaj-art-1ec45ada09134e4fb4ae444a455c7334 |
| institution | Kabale University |
| issn | 1468-8123 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Geofluids |
| spelling | doaj-art-1ec45ada09134e4fb4ae444a455c73342025-02-03T05:53:40ZengWileyGeofluids1468-81232022-01-01202210.1155/2022/4026200A Novel Continuous Fracture Network Model: Formation Mechanism, Numerical Simulation, and Field ApplicationZixi Guo0Jinzhou Zhao1Xinhao Sun2Chengwang Wang3Dali Guo4Haoran Hu5Hongna Wang6Qinggang Zeng7State Key Laboratory of Oil and Gas Reservoir Geology and ExploitationState Key Laboratory of Oil and Gas Reservoir Geology and ExploitationCNPC Western Drilling Engineering Company LimitedPetroChina Coalbed Methane Company LimitedState Key Laboratory of Oil and Gas Reservoir Geology and ExploitationPetroChina Southwest Oil & Gas Field CompanyCNPC Exploration Software Company LimitedSichuan Kehong Oil & Gas Engineering Company LimitedAfter a shale gas reservoir is fractured, hydraulic fractures interweave with natural fractures to form a fracture network. Numerical simulation based on the continuous fracture network model is a relatively economical and convenient method to predict fracture network morphology and size in the field application. However, some important factors, such as fracture height variation and filtration loss, have not been considered in the past continuous fracture network models. Therefore, this paper is aimed at establishing a novel continuous fracture network model to improve simulation accuracy. Firstly, this paper established a method to judge whether natural fractures develop or not. Then, a novel continuous fracture network model considering fracture height variation and asymmetry, filtration loss, fluid flow, and other key factors was established, and the forward algorithm and inverse algorithm of the model were proposed. At last, this model was applied in a field case to verify accuracy, and the average accuracy is more than 90%. Compared with the traditional Meyer software, the average error of prediction was reduced by 7.86%.http://dx.doi.org/10.1155/2022/4026200 |
| spellingShingle | Zixi Guo Jinzhou Zhao Xinhao Sun Chengwang Wang Dali Guo Haoran Hu Hongna Wang Qinggang Zeng A Novel Continuous Fracture Network Model: Formation Mechanism, Numerical Simulation, and Field Application Geofluids |
| title | A Novel Continuous Fracture Network Model: Formation Mechanism, Numerical Simulation, and Field Application |
| title_full | A Novel Continuous Fracture Network Model: Formation Mechanism, Numerical Simulation, and Field Application |
| title_fullStr | A Novel Continuous Fracture Network Model: Formation Mechanism, Numerical Simulation, and Field Application |
| title_full_unstemmed | A Novel Continuous Fracture Network Model: Formation Mechanism, Numerical Simulation, and Field Application |
| title_short | A Novel Continuous Fracture Network Model: Formation Mechanism, Numerical Simulation, and Field Application |
| title_sort | novel continuous fracture network model formation mechanism numerical simulation and field application |
| url | http://dx.doi.org/10.1155/2022/4026200 |
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