Detection of reservoir fractures in imaging logs using directional filtering
Every rock, which has pores connected together, can be considered as a reservoir rock. Existing fractures in the reservoir rock are the most effective factors, which increase the production and harvesting of the well. Detection of reservoir rock fractures is a very complicated process, due to factors such as poor contrast, fracture variable thickness, noise, discontinuities in the curve of a fracture, and the existence of some phenomenon like fracture bedding. In the well-log images, some sinusoidal curves are fractures. The directions of fractures are shown as some special curves. According to this concept, in this paper, fractures are extracted based on an optimized algorithm using directional filters. The first order derivative of the imaging log is calculated for each pixel. Then, the direction filters are designed based on a different direction of each pixel, and applied to the original imaging log. Finally, using the Hough transform, some parameters of each fracture are obtained, and are displayed on a real imaging log.
Automatic Detection of Fractures Based on Optimal Path Search in Well Logging Images
Reservoir fractures are essential locations to gather oil and gas. Recently, imaging logging technology has become a mainstream method for obtaining stratigraphic information. This paper proposed a combined optimal path search strategy to effectively identify and extract the fracture information in well logging images. Specifically, the threshold segmentation of logging images is used to obtain the binary image. In addition, the identification of connected fractures in the logging image is transformed into the optimal path search, and the identification and extraction of reservoir fractures are realized by constructing the optimal path between the two ends of fractures. Finally, an improved ant colony algorithm is applied to filter irrelevant information and extract fractures automatically by recording all the ants’ exploration trajectories in the ant colony. Compared with previous approaches, the proposed method can eliminate irrelevant background features and merely reserve pixels corresponding to fractures. Simultaneously, relative to the conventional strategy, the time consumption is reduced by more than 98%. The findings of this study can help for better extracting fractures automatically and reducing manual workload.
Multiple paths extraction in images using a constrained expanded trellis
Single shortest path extraction algorithms have been used in a number of areas such as network flow and image analysis. In image analysis, shortest path techniques can be used for object boundary detection, crack detection, or stereo disparity estimation. Sometimes one needs to find multiple paths as opposed to a single path in a network or an image where the paths must satisfy certain constraints. In this paper, we propose a new algorithm to extract multiple paths simultaneously within an image using a constrained expanded trellis (CET) for feature extraction and object segmentation. We also give a number of application examples for our multiple paths extraction algorithm.