Regular Article
Identification of reservoir fractures on FMI image logs using Canny and Sobel edge detection algorithms
School of Mining, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, Iran
* Corresponding author: kamkar@shahroodut.ac.ir
Received:
30
December
2019
Accepted:
30
October
2020
Because of the significant impact of fractures on production in hydrocarbon reservoirs, identification of these phenomena is a very important issue. Image logs are one of the best tools for revealing and studying fractures in reservoir and researcher can get lots of information about geological features in wells, by studying and analyzing these logs. In this research, two approaches have been used to determine the fractures in two wells A and B located in one of the oil fields in southwest of Iran. In the first approach, using Geolog software (version-7), after processing and correction of raw image log data, the number, position, dip, extension, layering, density and expansion of fractures have been identified. In the second approach, considering that the fractures in FMI images have edges, the Canny and Sobel filters as edge detection operators in image processing have been used to detect fractures in these images.
© M. Shafiabadi et al., published by IFP Energies nouvelles, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
