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Geoscience ›› 2018, Vol. 32 ›› Issue (02): 406-414.DOI: 10.19657/j.geoscience.1000-8527.2018.02.20

• Geophysics • Previous Articles    

Inversion Method Based on High-resolution Waveform and Its Application on Predicting Sweet Spots: An Example from Shale Gas Reservoirs in Jiaoshiba Area of Sichuan Basin

GUO Peng1,2(), YUAN Yijun1, LIU Xiwu3,4,5, ZHANG Yuanyin3,4,5, WU Xuemin1,6, LI Hong1,7   

  1. 1. School of Geophysics and Information Technology, China University of Geosciences, Beijing 100083, China
    2. Geophysical Prospecting Center, Beijing Engineering Corporation Limited of Power China, Beijing 100024,China
    3. Petroleum Exploration and Production Research Institute, SINOPEC, Beijing 100083, China
    4. Key Laboratory of Shale Oil/Gas Exploration and Production Technology, SINOPEC, Beijing 100083,China
    5. National Energy R & D Center of Shale Oil, Beijing 100083, China
    6. Guangzhou Marine Geological Survey,Guangzhou,Guangdong 510075,China
    7. Tianjin Municipal Engineering Design & Research Institute,Tianjin 300392,China
  • Received:2016-03-07 Revised:2017-01-22 Online:2018-04-10 Published:2018-05-07

Abstract:

The resolution of the conventional post-stack sparse pulse inversion method is low, and the traditional geostatistical inversion method also lacks the lateral geological significance. For these limitations, this paper proposed an inversion method based on high-resolution waveforms. This inversion method was employed to portray the distribution profile of wave impedance of the thin shale reservoir on Longmaxi Formation in Jiaoshiba area of Sichuan Basin, and to describe the plane distribution profile of thickness of high quality shale reservoirs in time domain. In the performance for random-well detection on the distribution profile of wave impedance in target reservoirs, the accuracy of this method had doubled comparing with the conventional post-stack sparse pulse inversion method. This inversion method was further applied to simulate the distribution profile of TOC in the target reservoir, and the results laid a foundation for the later ‘sweet spots’ evaluation and fine evaluation of shale reservoirs.

Key words: high-resolution, reservoir prediction, acoustic impedance, total organic carbon (TOC) content

CLC Number: