Oil & Gas Science and Technology (Jan 2021)

Well log data super-resolution based on locally linear embedding

  • Han Jian,
  • Gao Pan,
  • Cao Zhimin,
  • Li Jing,
  • Wang Sijie,
  • Yang Can

DOI
https://doi.org/10.2516/ogst/2021042
Journal volume & issue
Vol. 76
p. 63

Abstract

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Unconventional remaining oil and gas resources such as tight oil, shale oil, and coalbed gas are currently the focus of the exploration and development of major oil fields all over the world. Therefore, to make best understand of target reservoirs, enhancing the vertical resolution of well log data is crucial important. However, in the face of the continuous low-level fluctuations of international oil price, large scale use of expensive high resolution well logging hardware tools has always been unaffordable and unacceptable. In another aspect, traditional well log interpolation methods can always not realize high reliable information enhancement for crucial high frequency components. In this paper, in order to improve the well log data super-resolution performance, we propose for the first time to employ Locally Linear Embedding (LLE) technique to reveal the nonlinear mapping relationship between 2-times-scale-difference well log data. Several super resolution experiments with well log data from a given area of Daqing Oil field, China, were conducted. Experimental results illustrated that the proposed LLE-based method can efficiently achieve more reliable super-resolution results than other state-of-the-art methods.