github.com/xinwucwp/faultSeg 1.概述 从地震图像中判定出断层是地震构造解释、油藏描述和井位布置的关键步骤。地震图像处理通常涉及提取和增强地震构造特征以解释地下。在常规方法中,断层被认为是地震反射的不连续面,并通过计算估计反射连续性或不连续面的属性来检测。在本文中,认为断层检测是一种二值图像分割...
文件结构 -faultSeg-master(训练及验证部分) ├check1 # 用于存储检查点的模型和最后生成的模型 ├data #数据部分 ├─train ├──fault ├──seis ├─validation ├──fault ├──seis ├──predict ├train.py ├utils.py ├unet3.py -faultSeg-master(测试部分) ├model ├─prediction_model.hdf5...
As described inFaultSeg: using synthetic datasets to train an end-to-end convolutional neural network for 3D fault segmentationbyXinming Wu1,Luming Liang2,Yunzhi Shi1andSergey Fomel1.1BEG, UT Austin;2Uber. Getting Started with Example Model for fault prediction ...
Structural interpretation tasks require the step of fault segmentation, which is mostly performed manually, in seismic samples. Recent approaches represent seismic samples as 3D images and utilize a variety of methods, including Deep Learning. In this re
FaultSeg3D: using synthetic datasets to train an end-to-end convolutional neural network for 3D seismic fault segmentation 来自 Semantic Scholar 喜欢 0 阅读量: 1668 作者:X Wu,L Liang,Y Shi,S Fomel 摘要: (codes and data are available here: https://github.com/xinwucwp) Delineating faults ...
FaultSeg3D: using synthetic datasets to train an end-to-end convolutional neural network for 3D seismic fault segmentation This is a Keras version of FaultSeg implemented by Xinming Wu for 3D fault segmentation As described in FaultSeg: using synthetic datasets to train an end-to-end convolutiona...