A Comprehensive Model for Estimating Stimulated Reservoir Volume Based on Flowback Data in Shale Gas Reservoirs
Stimulated reservoir volume (SRV) which is generated by horizontal drilling with multistage hydraulic fracturing governs the production in the shale gas reservoirs. Although microseismic data has been used to estimate the SRV, it is high-priced and sometimes overestimated. Additionally, the effect o...
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Geofluids |
| Online Access: | http://dx.doi.org/10.1155/2020/8886988 |
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| author | Qi Chen Shaojun Wang Dan Zhu Guoxuan Ren Yuan Zhang Jinghong Hu |
| author_facet | Qi Chen Shaojun Wang Dan Zhu Guoxuan Ren Yuan Zhang Jinghong Hu |
| author_sort | Qi Chen |
| collection | DOAJ |
| description | Stimulated reservoir volume (SRV) which is generated by horizontal drilling with multistage hydraulic fracturing governs the production in the shale gas reservoirs. Although microseismic data has been used to estimate the SRV, it is high-priced and sometimes overestimated. Additionally, the effect of stress sensitivity on SRV is not considered in abnormal overpressure areas. Thus, the objective of this work is to characterize subsurface fracture networks with stress sensitivity of permeability through the shale gas well production data of the early flowback stage. The flowback regions are first identified with the flowback data of two shale gas wells in South China. Then, we measured the permeability stress sensitivity of the core after fracturing, coupled to the dynamic relative permeability (DRP) calculation to obtain an accurate and simple DRP curve. After that, a comprehensive model is built considering dynamic two-phase relative permeability function and stress sensitivity. Finally, we compared the calculated results with the microseismic data. The results show that the proposed model could reasonably predict the SRV using the flowback data after fracturing. Additionally, compared with the microseismic data, the stress sensitivity should be included, especially in the abnormal overpressure block. It is believed that this mathematical model is accurate and useful. The work provides an efficient approach to estimate stimulated reservoir volume in the shale gas reservoirs. |
| format | Article |
| id | doaj-art-3bd85aafb87c413eb9ef9204ff038c27 |
| institution | OA Journals |
| issn | 1468-8115 1468-8123 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Geofluids |
| spelling | doaj-art-3bd85aafb87c413eb9ef9204ff038c272025-08-20T02:08:16ZengWileyGeofluids1468-81151468-81232020-01-01202010.1155/2020/88869888886988A Comprehensive Model for Estimating Stimulated Reservoir Volume Based on Flowback Data in Shale Gas ReservoirsQi Chen0Shaojun Wang1Dan Zhu2Guoxuan Ren3Yuan Zhang4Jinghong Hu5Beijing Key Laboratory of Unconventional Natural Gas Geology Evaluation and Development Engineering, China University of Geosciences, Beijing 100083, ChinaResearch Institute of Petroleum Exploration & Development, Beijing 100083, ChinaThe 5th Oil Production Plant, Changqing Oilfield, Xi’an 710021, ChinaLeewen-Cobra International Energy (Beijing) Technology, Co., Ltd., 100084, ChinaBeijing Key Laboratory of Unconventional Natural Gas Geology Evaluation and Development Engineering, China University of Geosciences, Beijing 100083, ChinaBeijing Key Laboratory of Unconventional Natural Gas Geology Evaluation and Development Engineering, China University of Geosciences, Beijing 100083, ChinaStimulated reservoir volume (SRV) which is generated by horizontal drilling with multistage hydraulic fracturing governs the production in the shale gas reservoirs. Although microseismic data has been used to estimate the SRV, it is high-priced and sometimes overestimated. Additionally, the effect of stress sensitivity on SRV is not considered in abnormal overpressure areas. Thus, the objective of this work is to characterize subsurface fracture networks with stress sensitivity of permeability through the shale gas well production data of the early flowback stage. The flowback regions are first identified with the flowback data of two shale gas wells in South China. Then, we measured the permeability stress sensitivity of the core after fracturing, coupled to the dynamic relative permeability (DRP) calculation to obtain an accurate and simple DRP curve. After that, a comprehensive model is built considering dynamic two-phase relative permeability function and stress sensitivity. Finally, we compared the calculated results with the microseismic data. The results show that the proposed model could reasonably predict the SRV using the flowback data after fracturing. Additionally, compared with the microseismic data, the stress sensitivity should be included, especially in the abnormal overpressure block. It is believed that this mathematical model is accurate and useful. The work provides an efficient approach to estimate stimulated reservoir volume in the shale gas reservoirs.http://dx.doi.org/10.1155/2020/8886988 |
| spellingShingle | Qi Chen Shaojun Wang Dan Zhu Guoxuan Ren Yuan Zhang Jinghong Hu A Comprehensive Model for Estimating Stimulated Reservoir Volume Based on Flowback Data in Shale Gas Reservoirs Geofluids |
| title | A Comprehensive Model for Estimating Stimulated Reservoir Volume Based on Flowback Data in Shale Gas Reservoirs |
| title_full | A Comprehensive Model for Estimating Stimulated Reservoir Volume Based on Flowback Data in Shale Gas Reservoirs |
| title_fullStr | A Comprehensive Model for Estimating Stimulated Reservoir Volume Based on Flowback Data in Shale Gas Reservoirs |
| title_full_unstemmed | A Comprehensive Model for Estimating Stimulated Reservoir Volume Based on Flowback Data in Shale Gas Reservoirs |
| title_short | A Comprehensive Model for Estimating Stimulated Reservoir Volume Based on Flowback Data in Shale Gas Reservoirs |
| title_sort | comprehensive model for estimating stimulated reservoir volume based on flowback data in shale gas reservoirs |
| url | http://dx.doi.org/10.1155/2020/8886988 |
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