FZC: An Unsupervised Method for 3D Fracture Representation and Recognition in Well Logging.

IEEE International Geoscience and Remote Sensing Symposium (IGARSS)(2022)

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摘要
The recognition and representation of natural fractures are essential since oil and gas can gather and flow through naturally fractured zones in the stratum. This paper aims to give an intuitive and precise fracture representation by three-dimensional (3D) models of borehole walls and proposes an unsupervised method to segment fracture zones in the 3D borehole wall models. First, the 3D point cloud of the borehole walls, obtained by an ultrasonic imaging logging system, is built to reveal the actual oil wells' structures intuitively. Subsequently, the fractured zones clustering (FZC) method is proposed to implement fracture recognition using the density-based spatial clustering, an unsupervised approach to deal with the shortage of annotated labels. Experiments on the well logging data of an actual production well demonstrate that the proposed method can identify the point cloud corresponding to fracture zones effectively and accurately.
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关键词
ultrasonic logging,fracture recognition,point cloud,DBSCAN clustering
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