Maximizing of the coverage and quality in micro resistivity image log by applying minimum weighted norm interpolation and anisotropic diffusion filter
Author(s):
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
The micro-resistivity imaging log is a crucial tool for measuring the heterogeneous features of a formation. It objectively and quantitatively describes various reservoir characteristics, including fine structures, thin strata, fissures, and sedimentary facies. In these imaging tools, measurements from button arrays create an electrical image of the wellbore. However, gaps between tool pads limit coverage, and damaged buttons may compromise image quality.In this study, we examine image log data for factors impacting data acquisition, followed by processing for basic correction, image enhancement, and static and dynamic image log creation. To achieve 100% coverage, the Minimum Weighted Norm Interpolation (MWNI) algorithm fills gaps between tool pads. Finally, the Anisotropic Diffusion Filter (ADF) reduces noise and enhances image log quality in MATLAB, providing a comprehensive image from logging tools. As image logs play a crucial role in illustrating the wellbore and reservoir, this study suggests a new workflow to successfully tackle the challenges linked with acquiring comprehensive image log coverage.
Keywords:
Language:
English
Published:
International Journal of Mining & Geo-Engineering, Volume:58 Issue: 2, Spring 2024
Pages:
221 to 227
https://www.magiran.com/p2736283
سامانه نویسندگان
مقالات دیگری از این نویسنده (گان)
-
Hydrocarbon reservoir potential mapping through Permeability estimation by a CUDNNLSTM Deep Learning Algorithm
Behnia Azizzadeh Mehmandoust Olya, Reza Mohebian *
International Journal of Mining & Geo-Engineering, Autumn 2023