4.4 Article

Channel identification using 3D seismic attributes and well logging in lower Shihezi Formation of Hangjinqi area, northern Ordos Basin, China

Journal

JOURNAL OF APPLIED GEOPHYSICS
Volume 163, Issue -, Pages 139-150

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.jappgeo.2019.02.015

Keywords

3D seismic attributes; Hangjinqi; Northern Ordos Basin; Shihezi Formation; Spectral decomposition

Funding

  1. China University of Geosciences, Wuhan
  2. National Natural Science Foundation of China [4162134]
  3. National Key R&D program of China [2017YFE0106300]
  4. 13th Five year Plan of the Ministry of Science and Technology of China [2016ZX05034-002003]
  5. Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) [CUGCJ1712]
  6. Key Laboratory of Tectonics and Petrolum Resources (China University of Geosciences in Wuhan) [TPR-2018-18]

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Channel identification in oil and gas exploration is a vital task due to the importance of fluvial reservoirs. The fluvial sandstone of Lower Shihezi Formation of Ordos Basin is the primary target layer of gas exploration and development which has the maximum potential of producing tight gas sand reservoir in China. Fluvial paleo-channels can be identified easily by core, outcrop and logs data, but due to development of the several faults and limited seismic resolution in the study area, it is difficult to identify them by conventional seismic methods. The study was conducted in Hangjinqi area on the regional level of about 4537.87 km(2). The radical objective of this research is to recognize the horizontal distribution and geometry of the multiple channels. Based on the study of integrated analyses of geological cores, geophysical well-logs, and seismic attributes it is confirmed that multiple, braided channels are present in the study area. Channel distribution based on seismic attributes and its overlapping on the paleogeographic map showed that the channels are coming from the North and are merging towards South direction. (C) 2019 Elsevier B.V. All rights reserved.

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