ADAPTIVE LEAST SQUARE DECONVOLUTION AND APPLICATION TO SEISMIC PROSPECTING
C Wang · Chinese Journal of Geophysics · 1987
This paper presents an adaptive least square predictive deconvolution method (ALSD). Its basic principle is that successively adjusting desired signals according to filtering outputs makes improved results being adapted to the wavelet phase. In iterative algorithm the method generalizes iterative model of minimum entropy deconvolution. The paper gives some criteria for choosing an adaptive function model which is of significance for algorithm. Numerical examples with synthetic data and natural data show an improvement result and less computational amount. For minimum phase wavelet the result can be compared with that of spike deconvolution and for non-minimum phase wavelet the result is close to that of corresponding minimum phase wavelet.