基于迭代再加权最小二乘的地震资料稀疏反演方法

ABSTRACTABSTRACTThe basic goal impedance inversion is to recover the layered structure of thesurface as a function of depth from observed seismic data,which usually expressed asseries of reflection coefficients.Such a goal could be achieved when the effects ofseismic wavelet is eliminated in an effective way.However,it is hard to get highresolution reflection coefficients series because of the bandlimited effect of seismicdata with the resulting loss of low and high frequency information about subsurfacestructure.The unavoidable noise reduced the resolution,too.The purpose of this dissertation is to invert a high resolution reflectioncoefficients series from seismic data using iterative reweighted technique.Thistechnique transform the sparse optimization into a series of wighted linear function,speeds up the computing while keep signal-to-noise rate high.In order to stabilize andaccelerate the solving,pre-conditioning according to the linear function is used andshrink operator is introduced in computing the weighing.Through lots of numericalexperimentations,the range of parameters is settled,and the practicability isconformed together with the real data processing.KEYWORDS:impedance inversion,iterative reweighted,Gauss-Siedel iteration,conjugate gradientmethod,pre-conditioning,shrinkV