Deconvolution of teleseismicp-waves using the SVA and autoregressive techniques
- 出版日期：2007.
- 页数：1 online resource.
- 第一责任说明：Saptarshi Dasgupta.
- 分类号：a631
- ISBN：9780549357506(e-book) :
MARC全文
62h0045997 20131115160740.0 cr an |||||||| 131022s2007 a fsbm |000|0 eng | 3291066 9780549357506(e-book) : CNY371.35 NGL eng NGL a631 Dasgupta, Saptarshi. Deconvolution of teleseismicp-waves using the SVA and autoregressive techniques [electronic resource] / Saptarshi Dasgupta. 2007. 1 online resource. Description based on online resource; title from title page (viewed Oct. 22, 2013) Thesis (Ph.D.)--Purdue University, 2007. Includes bibliographical references. In this study, the deconvolution of three-component teleseismic P-waves is investigated using the autocorrelation of the P to SV scattered waves. By assuming that the P to SV scattering coefficients are random and white, the autocorrelation of the SV component (SVA) provides an estimate of the autocorrelation of the source and distant earth signature. This is similar to using the autocorrelation of a reflection seismogram for deconvolution in exploration seismology where the P to P scattering coefficients are assumed to be random and white. For earthquake data the source signature is generally not minimum phase. However a minimum phase wavelet obtained from the SV autocorrelation can be used to deconvolve the original data that have been processed to be minimum phase. The SVA approach has been tested using synthetic data and then applied to observed teleseismic data from the 1993 Cascadia experiment. Since deconvolution results are often restricted in frequency range, an extrapolation of the deconvolved frequency spectra is next investigated using an autoregressive (AR) approach and an extended time-domain deconvolution approach to obtain better temporal resolution. A prediction error filter is used to perform the autoregressive extrapolation to estimate the unknown spectral values of the deconvolution results. An extended time-domain deconvolution approach is also developed where the deconvolved spectra are enhanced using increased high-cut filters for the time-domain deconvolution. The AR and extended time-domain deconvolution approaches are compared using synthetic data and observed data from the GBA seismic array in India. The deconvolution of vertical component seismic data using the SVA technique is finally applied to selected INDEPTH II and CDSN seismic stations to investigate the P-wave velocity structure in southern Tibet. The deconvolved vertical component seismic data are inverted for P-velocity crustal structure and the resulting Moho depths at each station are compared with the depths obtained by the inversion of receiver functions by Mitra et al. (2005). Seismic prospecting. Electronic dissertations local. aInternet resource. aCN b010001 http://pqdt.bjzhongke.com.cn/Detail.aspx?pid=p9yWMUH6WEQ%3d 010001 Bs2727 rCNY371.35 ; h1 bs1310