基于Kendall一致性度量的地震數(shù)據(jù)相干估計(jì)算法(英文)
發(fā)布時(shí)間:2018-03-21 22:03
本文選題:一致性度量 切入點(diǎn):相干估計(jì) 出處:《Applied Geophysics》2016年03期 論文類型:期刊論文
【摘要】:相干體方法常被用于刻畫(huà)地震數(shù)據(jù)的不連續(xù)性和非均質(zhì)性,但相干體方法若使用線性相關(guān)系數(shù)度量?jī)蓚(gè)隨機(jī)變量(即兩個(gè)地震道)之間的關(guān)系,由于隨機(jī)變量的關(guān)系是非線性的,用線性相關(guān)系數(shù)度量描述非線性關(guān)系,根據(jù)數(shù)學(xué)定義,存在一定的局限性。為了能更準(zhǔn)確度量地震道波形之間的相似性),本文提出一種基于Kendall一致性度量算法,克服線性相關(guān)系數(shù)度量存在一定的局限性。本文的重點(diǎn)是研究線性相關(guān)系數(shù)度量和一致性度量對(duì)波形相似性變化的敏感性,我們?cè)O(shè)計(jì)了兩個(gè)數(shù)值模型測(cè)試這兩種度量對(duì)波形相似性變化的敏感性,發(fā)現(xiàn)Kendall一致性度量對(duì)波形的變化比線性相關(guān)系數(shù)度量更敏感,可用于精細(xì)刻畫(huà)波形的變化,并結(jié)合信息散度度量可更精細(xì)刻畫(huà)地層非均質(zhì)性方法,我們將其應(yīng)用處理實(shí)際的地震資料數(shù)據(jù),表明該方法不但有效并具有較高的分辨率。
[Abstract]:Coherent volume method is often used to describe the discontinuity and heterogeneity of seismic data, but the linear correlation coefficient is used to measure the relationship between two random variables (i.e. two seismic traces). Because the relation of random variable is nonlinear, the linear correlation coefficient is used to describe the nonlinear relation, according to the mathematical definition, In order to measure the similarity between seismic trace waveforms more accurately, a consistency measurement algorithm based on Kendall is proposed in this paper. To overcome the limitations of linear correlation coefficient measurement, this paper focuses on the sensitivity of linear correlation coefficient measurement and consistency measure to the variation of waveform similarity. We design two numerical models to test the sensitivity of these two measures to the variation of waveform similarity. It is found that the Kendall consistency measure is more sensitive to the variation of waveform than the measure of linear correlation coefficient, and can be used to describe the variation of waveform in detail. Combined with the information divergence metric, the method of stratigraphic heterogeneity can be described more finely. The method is applied to processing the actual seismic data, which shows that the method is not only effective but also has a high resolution.
【作者單位】: 西安交通大學(xué)電子與信息工程學(xué)院波動(dòng)與信息研究所;海洋石油勘探國(guó)家工程實(shí)驗(yàn)室;中國(guó)石油長(zhǎng)慶油田分公司勘探開(kāi)發(fā)研究院;
【基金】:supported by the Major Programs of National Natural Science Foundation of China(No.41390454) the Major Research Plan of the National Natural Science Foundation of China(No.91330204)
【分類號(hào)】:P631.44
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本文編號(hào):1645740
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