High permeability flowing channel prediction upon production data mining

Runfei Bai; Shuiqing Hu; Jue Wang

doi:10.1117/12.3021582

19 February 2024 High permeability flowing channel prediction upon production data mining

Runfei Bai, Shuiqing Hu, Jue Wang

Proceedings Volume 13063, Fourth International Conference on Computer Vision and Data Mining (ICCVDM 2023); 130631B (2024) https://doi.org/10.1117/12.3021582
Event: Fourth International Conference on Computer Vision and Data Mining (ICCVDM 2023), 2023, Changchun, China

Abstract

Due to long term development by waterflooding in the unconsolidated sandstone oilfields, high permeability flowing channels or “large pore paths” are likely to form between some injection and production wells, resulting in the channeling of injected water as well as the worsening of waterflooding effectiveness. Therefore, how to quickly and accurately identify and predict the direction of high permeability flowing channels is very significant for tapping the remaining oil and designing the scheme of profile control and water plugging. According to the deficiencies in some testing methods which are commonly used in field to discriminate high permeability flowing channels, a convenient, efficient and economic approach to predict the distribution direction of high permeability flowing channels is put forward in the paper, which base on system analysis theory can fully dig out implicit information behind the dynamic data. Moreover, the validity of this method has been verified by using theoretical model and actual production data.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Runfei Bai, Shuiqing Hu, and Jue Wang "High permeability flowing channel prediction upon production data mining", Proc. SPIE 13063, Fourth International Conference on Computer Vision and Data Mining (ICCVDM 2023), 130631B (19 February 2024); https://doi.org/10.1117/12.3021582

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