基于近邻传播聚类与曲线拟合的断层识别  

Fault recognition based on affinity propagation clustering and curve fitting

作　　者：叶涛[1] 陈雷[2] YE Tao1 , CHEN Lei2(1. College of Computer, Qinghai Nationalities University, Xining 810007, China; 2. Key Laboratory of Petroleum Resources Research, institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, Chin)

机构地区：[1]青海民族大学计算机学院,青海西宁810007 [2]中国科学院地质与地球物理研究所中国科学院油气资源研究重点实验室,北京100029

出　　处：《计算机工程与设计》2018年第8期2510-2514,2637,共6页Computer Engineering and Design

基　　金：教育部"春晖计划"基金项目(Z2016104);青海民族大学网络与信息安全科研创新团队专项基金项目

摘　　要：为快速准确地将断层从地震数据中识别出来,提出一种基于近邻传播聚类与曲线拟合的断层识别方法。通过层位的横向端点确定层位不连续点;采用近邻传播聚类算法对层位不连续点进行聚类,属于同一类的不连续点用于确定一条断层;使用曲线拟合方法对每一类层位不连续点进行拟合,拟合的曲线即为断层。该方法可以准确地识别断层且计算量较小,通过与其它方法在实际地震数据上的实验对比,验证了其有效性。To recognize faults from seismic data quickly and accurately,a fault recognition method based on affinity propagation clustering and curve fitting was proposed.Discontinuous points of horizons were located through the horizontal endpoints of the horizon.The discontinuous points were clustered by the affinity propagation clustering algorithm,and the points of the same cluster were used to determine a fault.The discontinuous points of the same cluster were fitted using the curve fitting method,and the curves were the desired faults.The proposed method can recognize the faults accurately with less computation.By the comparison experiments on the real seismic data with the traditional method,the availability of the presented method is demonstrated.

关 键 词：近邻传播 断层 层位 聚类 拟合 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]