石油物探2026，Vol.65Issue(5)：844-854,11.DOI:10.12431/issn.1000-1441.2026.0398
基于时空特征融合的水力裂缝形态代理模型构建与应用
Construction and application of a spatiotemporal feature fusion surrogate model for hydraulic fracture morphology
摘要
Abstract
To address the engineering challenges of difficult hydraulic-fracture network morphology prediction and time-consuming numerical simulation,this study develops an FC-UNet surrogate model for two-dimensional fracture morphology prediction in horizontal wells.The model uses U-Net as the backbone and integrates fast Fourier transform(FFT),parallel convolution(PC),and a channel attention mechanism(CAM)to adaptively fuse pumping time-series signals with spatial geological features,thereby transforming fracture propagation prediction into a pixel-level segmentation task.Based on an unconventional fracture model(UFM)calibrated with field micro-seismic data,310 forward-modeling samples were generated.A joint loss function combining weighted cross-entropy and Dice loss was introduced to alleviate class imbalance caused by sparse fracture pixels.Independent test results show that FC-UNet can accurately characterize main-fracture penetration and fracture deflection features,achieving an intersection over union(IoU)of approximately 0.84 and an F1-score consistently above 0.91.The prediction time for a single case is about 5 s,indicating that the model can serve as a fast surrogate for UFM-based fracture morphology forward modeling under similar geological conditions.关键词
水力压裂/非常规裂缝模型/深度学习/压裂裂缝形态/代理模型Key words
hydraulic fracturing/unconventional fracture model/deep learning/hydraulic fracture morphology/surrogate model分类
能源科技引用本文复制引用
刘春生,高其宇,王猛,方军龄,向东流..基于时空特征融合的水力裂缝形态代理模型构建与应用[J].石油物探,2026,65(5):844-854,11.基金项目
国家重点研发计划项目"地质资源智能预测及勘探开发地质风险评估理论模型与方法"(2022YFF0801202)资助. This research is financially supported by the National Key Research and Development Program of China(Grant No.2022YFF0801202). （2022YFF0801202）
