Advanced Search
    GUO Xin, YONG Xueshan, GAO Jianhu, LIU Weifang, LI Shengjun. Seismic bandwidth broadening method based on multi-order differential fusion in frequency domainJ. Geophysical Prospecting for Petroleum, 2016, 55(2): 271-279. DOI: 10.3969/j.issn.1000-1441.2016.02.013
    Citation: GUO Xin, YONG Xueshan, GAO Jianhu, LIU Weifang, LI Shengjun. Seismic bandwidth broadening method based on multi-order differential fusion in frequency domainJ. Geophysical Prospecting for Petroleum, 2016, 55(2): 271-279. DOI: 10.3969/j.issn.1000-1441.2016.02.013

    Seismic bandwidth broadening method based on multi-order differential fusion in frequency domain

    • Due to the limited bandwidth of seismic wavelet,the information outside of the wavelet bandwidth is difficult to be distinguished and identified,which leads to the low resolution.To the issue,we present a multi-order differential fusion method in frequency domain to broaden the seismic bandwidth.Differential operators have linear features of increasing monotonically and can improve high frequency and suppress low frequency of signals,namely it has the attribute of frequency spectral decomposition and higher differential order represents higher frequency.We can extract the reflection coefficient from logging data and calculate the low frequency change trend of its amplitude spectrum,which are non-white noise components.Then we add up the differential signal through multiple iterations under the constraint of the non-white noise components.A new broadband seismic record is achieved after back to the time domain from the frequency domain,which has the same trend with the spectrum of reflection coefficient and its high cut-off frequency can be doubled,so it can effectively weaken the influence of the limited bandwidth of the seismic wavelet.It demonstrates that this method can broaden the bandwidth well and improve the resolution of seismic data through the test processing of thin interbedded mathematical model,physical model with pinchout bodies and real seismic data.
    • loading

    Catalog

      Turn off MathJax
      Article Contents

      /

      DownLoad:  Full-Size Img  PowerPoint
      Return
      Return