Future gas field development and prospect assessment depend on accurate reservoir parameter characterization. The understanding of the tight sand distribution of the Shanxi and Taiyuan Formations within the Hangjinqi area is ambiguous due to the presence of coal and mudstone lithofacies, high heterogeneity, and poor resolution of the seismic data. Thus, it is difficult to determine the reservoir’s thickness. To cope with this challenge, we have employed the advanced method of constrained sparse spike inversion (CSSI) utilizing 3D seismic and nine wells for the distinction of tight sandstone facies from the coal and mudstone facies. Results of petrophysical analysis of studied well J54 show that the coal and mudstone facies are dominant towards the T9c horizon, whereas tight sandstone facies are present towards the T9d horizon. The obtained findings show that the CSSI accurately identified the spatial distribution of sand-ratio in the zone of interest (ZOI) that lies between the T9c and T9d horizons. The acoustic impedance (AI) of coal shows the lowest AI values, whereas the tight sandstone shows the highest AI values. The tight sandstone facies shows moderate values of AI in the range of 8.5 × 106 kg/m2s to 1.20 × 107 kg/m2s. The impedance map of T9c suggested the presence of coal and mud facies, whereas the T9d impedance map suggest the presence of maximum tight sandstone facies. The sand-ratio map of T9d showed maximum reservoir thickness that ranges from 0.65-0-95, whereas the sand-ratio value mostly ranges from 0 to 0.5 on the T9c map. The maximum sand-ratio values on T9d show that the lower Shanxi Formation has good reservoir characteristics. Whereas, due to the presence of coal and mudstone in the Taiyuan Formation, the T9c map shows low values of sand-ratio. The maximum sand-ratio regions within the targeted T9c-T9d layers should be exploited for future gas explorations.
|Original language||English (US)|
|Journal||Frontiers in Earth Science|
|State||Published - Sep 23 2022|
Bibliographical noteKAUST Repository Item: Exported on 2022-10-31
Acknowledgements: This research was supported by the National Natural Science Foundation of China (Grant Nos 4162134 and 41820104008), the National Key R and D program of China (2017YFE0106300), the 13th Five year Plan of the Ministry of Science and Technology of China (2016ZX05034-002003), the Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) (CUGCJ1712), and the Open Fund of the Key Laboratory of Tectonics and Petroleum Resources (China University of Geosciences in Wuhan) (TPR-2018-18), and Yunnan Provincial Government Leading Scientist Program, No. 2015HA024. AA is grateful to my former supervisor Prof. Shi Wanzhong for providing the necessary data, guidance, support, software, and technical help to accomplish this research. I am also thankful for my labmates at the China University of Geosciences. I also acknowledge the China University of Geosciences, Wuhan, and Yunnan University for funding this project.