摘要
针对非线性高维地震属性参数降维的难题,在综合分析研究工区地震属性参数数据实际特征的基础上,引入非线性降维Isomap算法,并基于MATLAB平台进行了算法的程序编制,进一步将Isomap降维的结果与线性的MDS降维结果通过小波神经网络进行检验,从算法原理的角度讨论了Isomap算法在地震属性参数降维处理中的可适性,表明Isomap具有更强的降维能力和发现数据本质结构的能力,从另一个角度提供了解决地质数据处理问题的方法。
In view of difficulty in reduction dimension of nonlinear high dimensional seismic attribution parameter and based on comprehensive analysis of the exact character of seismic attribution parameter in the study area, a method of nonlinear Isomap algorithm is introduced. The algorithm program is achieved on the base of MATLAB. Further, the result from Isomap and that from linear MDS are examined by wavelet neural net. Whether Isomap is applicable for reduction dimension of seismic attribution parameter or not is discussed from the angle of algorithm theory. It is shown that Isomap has stronger ability in reduction dimension and finding data's essential structure. It provides a solution to analyze geological data from another angle.
出处
《天然气工业》
EI
CAS
CSCD
北大核心
2008年第5期38-40,140,共3页
Natural Gas Industry
基金
国家自然科学基金重点项目“南方中上扬子区叠合盆地沉积充填过程与物质分布规律”(编号:40739901)的资助
关键词
地震数据处理
参数
算法分析
模糊数学
seismic attribution analysis, parameter, algorithm, fuzzy mathematics
