ORIGINAL RESEARCH article
Front. Earth Sci.
Sec. Economic Geology
Volume 13 - 2025 | doi: 10.3389/feart.2025.1640215
This article is part of the Research TopicAdvances in Accumulation Conditions of Unconventional Oil and Gas Resources in Complicated Structure AreasView all 5 articles
Automatic detection and classification of igneous rock fractures from imaging logging using K-mean algorithm and DNN
Provisionally accepted
- China Oilfield Services Ltd, Beijing, China
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Accurately identifying fracture zones and their types in strata is of great significance for enhancing oil and gas recovery efficiency. Due to its complicated geological structure and long-term weathering and erosion, the buried hill reservoir in Huizhou Oilfield has developed a complicated reservoir structure. This structure is characterized by great burial depth, strong heterogeneity, diverse lithological types, and high degrees of weathering. These factors collectively result in significant spatial
Keywords: DNN, K-means, Buried hill reservoirs, Imaging logging, image segmentation, Classification of fractures
Received: 03 Jun 2025; Accepted: 28 Jul 2025.
Copyright: © 2025 Wang, Zhou, Yin and Dong. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Lu Yin, China Oilfield Services Ltd, Beijing, China
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