Heuristic-based approaches for fracture detection in borehole images. (2nd March 2023)

• Record Type: Journal Article
• Authors: Moran, Maira B.H.; Vasconcellos, Eduardo C.; Cuno, Jordan J.S.; Biondi, Mauro; Riveaux, José M.; Correia, Maury D.; Clua, Esteban W. Gonzalez; Conci, Aura
• Is Part Of: International journal of innovative computing and applications. Volume 14:Number 1/2(2023)
• Page Start: 78
• Page End: 90
• Publication Date: 2023-03-02
• Subjects: oil drilling -- ultrasonic borehole image -- UBI -- fractures -- sinusoidal curves -- heuristics -- variable neighbourhood descendent -- iterated local search -- detection -- Hough transform; Evolutionary computation -- Periodicals; Neural networks (Computer science) -- Periodicals; Genetic programming (Computer science) -- Periodicals; Biologically-inspired computing -- Periodicals; Swarm intelligence -- Periodicals; Quantum computers -- Periodicals; 006.3
• Languages: English
• ISSNs: 1751-648X

Abstract

The success of an oil well drilling process depends, among other factors, on the borehole stability, which is closely related to fractures. Borehole imaging tools are commonly used to identify this kind of feature. Visually, fractures can be identified as sinusoidal curves in the 2D data obtained by the ultrasonic borehole imager (UBI). Their automatic detection is not trivial. Previous works in literature proposed solutions for this problem. Most of them are based on extensive curve searches with a high computational cost. A recent work uses a more efficient method based on a heuristic algorithm. However, it results in many false fractures. In this work, we propose a set of 11 new heuristics-based innovative methods, composed of two different algorithms and three pre-processings, to identify the sinusoidal curves related to fractures in UBI data. Moreover, we include a post-processing step to reduce the number of incorrect fractures. We perform an evaluation of these proposed methods in real data, comparing them to the only heuristic-based method previously presented in the literature. Our achieved results are very promising, with the best methods presenting fewer false curves and a higher rate of correctly detected fractures.