Prediction of sweet spots in shale reservoir based on geophysical well logging and 3D seismic data: A case study of Lower Silurian Longmaxi Formation in W4 block, Sichuan Basin, China
| Autor: | Sheng Chen, Wenzhi Zhao, Yonglin Ouyang, Qingcai Zeng, Qing Yang, Huaxing Hou, Shaohua Gai, Shihai Bao, Xinyu Li |
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| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: | |
| Zdroj: | Energy Exploration & Exploitation, Vol 35 (2017) |
| Druh dokumentu: | article |
| ISSN: | 0144-5987 2048-4054 01445987 |
| DOI: | 10.1177/0144598716679961 |
| Popis: | W4 block of Sichuan Basin is a pioneer in shale gas exploration and development in China. But geophysical prospecting is just at its beginning and thus has not provided enough information about how sweet spots distribute for the deployment of horizontal well. This paper predicted sweet spots based on logging and 3D seismic data. Well logging interpretation method was used to get the key evaluation parameters of shale reservoir and determine the distribution of sweet spots in vertical direction. Rock physics analysis technology was used to define the elastic parameters that were sensitive to the key evaluation parameters, such as TOC and gas content of shale gas reservoir. At the same time the quantitative relationships between them were established. Based on the result of seismic rock physics analysis, prestack inversion was carried out to predict the transverse plane distribution of the key evaluation parameters of shale reservoir. These research results are integrated to determine the distribution of sweet spots. The results show that sweet spots in this area were characterized by high TOC content, high gas content, high GR, high Young’s modulus, low Poisson’s ratio, low density, and low P-wave velocity. Density was the most sensitive elastic parameters to TOC of the reservoir. The optimal combination for predicting the gas content is composed of six parameters include density, Poisson’s ratio, and so on. Sweet spots in this block vertically concentrate within 30 m above the bottom of Longmaxi Formation. Two classes of sweet spots have been predicted in this area, class I sweet spots are recommended to be prioritized for development. This study effectively predicted the spatial distribution of sweet spots, which provide important guidance for the development of the area. |
| Databáze: | Directory of Open Access Journals |
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