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Fast and objective detection and analysis of structures in downhole images

Downhole acoustic and optical televiewer images, and formation microimager (FMI) logs are important datasets for structural and geotechnical analyses for the mineral and petroleum industries. Within these data, dipping planar structures appear as sinusoids, often in incomplete form and in abundance....

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Bibliographic Details
Published in:Journal of applied geophysics 2017-09, Vol.144, p.157-172
Main Authors: Wedge, Daniel, Holden, Eun-Jung, Dentith, Mike, Spadaccini, Nick
Format: Article
Language:English
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Summary:Downhole acoustic and optical televiewer images, and formation microimager (FMI) logs are important datasets for structural and geotechnical analyses for the mineral and petroleum industries. Within these data, dipping planar structures appear as sinusoids, often in incomplete form and in abundance. Their detection is a labour intensive and hence expensive task and as such is a significant bottleneck in data processing as companies may have hundreds of kilometres of logs to process each year. We present an image analysis system that harnesses the power of automated image analysis and provides an interactive user interface to support the analysis of televiewer images by users with different objectives. Our algorithm rapidly produces repeatable, objective results. We have embedded it in an interactive workflow to complement geologists' intuition and experience in interpreting data to improve efficiency and assist, rather than replace the geologist. The main contributions include a new image quality assessment technique for highlighting image areas most suited to automated structure detection and for detecting boundaries of geological zones, and a novel sinusoid detection algorithm for detecting and selecting sinusoids with given confidence levels. Further tools are provided to perform rapid analysis of and further detection of structures e.g. as limited to specific orientations. •A system for rapidly detecting dipping planar structures in borehole images is presented, harnessing computational power with geologists’ input, experience, and goals.•A novel algorithm detects planar structures imaged as sinusoids in downhole images, handling variations in contrast, aperture and shape.•We introduce a workflow and tools for using the algorithm to rapidly analyse and select structures within a borehole.
ISSN:0926-9851
1879-1859
DOI:10.1016/j.jappgeo.2017.07.004