Oil & Gas Geology ›› 2021, Vol. 42 ›› Issue (5): 1202-1209.doi: 10.11743/ogg20210517

• Methods and Technologies • Previous Articles     Next Articles

Super-resolution imaging of thin sections for lacustrine shale reservoirs

Chao Guo1,2(), Qianping Zhao1,2,*(), Gang Liu1,2, Shiyan Hao1,2, Chao Gao1,2, Jianbo Sun1,2, Chao Liu1,2, Yiyi Chen1,2   

  1. 1. Research Institute, Shaanxi Yanchang Petroleum (Group) Co., Ltd., Xi'an, Shaanxi 710065, China
    2. Shaanxi Key Laboratory of Lacustrine Shale Gas Accumulation and Exploitation, Xi'an, Shaanxi 710065, China
  • Received:2021-03-02 Online:2021-10-28 Published:2021-10-26
  • Contact: Qianping Zhao E-mail:232003659@qq.com;zhaoqp@yeah.net

Abstract:

Despite a great progress made in the exploration and development of shale gas and oil in recent years, the study on the pores, organic matter and mineral composition of shale reservoirs at a microscopic scale is still a challenge with thin section analysis for conventional reservoirs. In order to solve this problem, this study introduces a super-resolution technology to improve thin section image quality for revealing micro-characteristics of shale reservoirs. A set of super-resolution models are established based on generative adversarial networks and corresponding content loss functions are also set up for thin-section images. Application of the technology to the processing of actual data from lacustrine shale gas reservoirs in the Yanchang Formation in Ordos Basin has yielded positive results, demonstrating quantitatively and qualitatively its applicability, accuracy and reliability for unconventional reservoir assessment.

Key words: microscopic physical property, super-resolution, data enhancement, thin section, shale reservoir, Ordos Basin

CLC Number: