页岩裂缝智能提取与缝网复杂度定量表征

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中图分类号：P631 文献标识码：A DOI：10.13810/j.cnki.issn.1000-7210.20240438

Abstract： Shale gas has become an important strategic alternative field for China’s oil and gas resources. Shale is characterized by low porosity and low permeability，and only after going through large-scale volume fracturing can industrial production capacitybe obtained. The fine characterization and quantitative characterization of fracture parameters after shale fracturing are the key to fracturing effect evaluation and development parameter optimization. By taking the three-dimensional CT images of shale cores after fracturing as the research object， this paper conducts inteligent fracture extraction based on the deep learning semantic segmentation model. Firstly，a U-Net deep learning model integrating the pyramid convolution and atention mechanism is built to alleviate the influence of image category imbalance and improve fracture extraction accuracy. Secondly，a digital core model is built based on the semantic segmentation results，and quantitative characterization of the spatial distribution of fractures is realized by combining parameters such as the porosity and tilt index.Finally，the complexity of the fracture network is characterized by the peak and width of the multi-fractal spectrum.The research results show that compared with the traditional image segmentation model，the sensitivity of the improved model is increased by 6.69% ，and the intersection over union grows by 0.48% . This study systematically characterizes the three-dimensional fracture features by image segmentation algorithm optimization，digital core modeling，and multi-fractal analysis，which is applicable to the characterization of fracture networks in unconventional reservoirs such as shale and can provide a reference for the evaluation of reservoir stimulation effects after hydraulic fracturing.

Keywords： CT image，fracture segmentation，U-Net，digital core，multi-fractal dimension王飞，黄露逸，边会媛，等，页岩裂缝智能提取与缝网复杂度定量表征[J].石油地球物理勘探，2025，60（4）：828-839.

WANG Fei，HUANG Luyi，BIAN Huiyuan，et al. Intellgent extraction of shale fractures and quantitative characterizationoffracture network complexity[J].Oil Geophysical Prospecting，2025，60（4）：828-839.

0 引言

页岩气作为清洁的非常规能源逐步成为勘探开发的热点领域以及油气资源的重要接替领域，研究页岩气藏的储集机理与高效开采方法具有重大战略意义[。（剩余17164字）