Research On A Method Of Information Feedback Controlling Seismic Wavelet Estimation Based On Deconvolution

The seismic wavelet estimation quality directly affects high resolution, high signal-to-noise ratio and high fidelity seismic exploration data processing. In the practical seismic data process, the precision of seismic wavelet extraction cannot be judged, and the effects of wavelet estimation technique performances cannot be evaluated. This paper proposed a high precision method of information feedback to control seismic wavelet estimation based on the deconvolution. Under the thorough analysis of deconvoluton method, the synthetic seismic records can be obtained by convolution of the reflection coefficient sequences estimated by the sparse hypothesis mixed phase methods and the seismic wavelet estimated by parametric model method. Then the linchpin attributes can be got by seismic profiles attribute analysis optimization. By comparing and analyzing the linchpin attributes of the synthetic seismic records with the ones of original seismic records to evaluate the extracted wavelet accuracy and the wavelet extraction technology performance. The third step is using the comparison results to fix wavelet and get a high precision seismic wavelet.The accuracy of reflection coefficient sequences by deconvolution methods directly affects the synthetic seismic records. Through the study of classic deconvolution and existing improved deconvolution method,the issue is aimed at various deconvolution methods because different assumed conditions and scope of application resulting the accuracy of extraction reflection coefficient sequences is not high. This paper adopts the mixed phase wavelet deconvolution method based on sparse hypothesis in order to transform the problem of solving reflection coefficient sequences into optimization problem, by establishing objective function and repeate iteration to obtain reflection coefficient sequences. Compare with classic minimum square deconvolution method, theory and data simulation experiment results show the method can get high accuracy reflection coefficient sequences when wavelet is mixed phase, convolution with wavelet can get synthetic seismic records very similar to raw seismic records.Another key problem of the wavelet extraction method based on information feedback is the feedback information and feedback mechanism determination. Feedback information and feedback mechanism are the two keys of seismic wavelet extraction based information feedback. According to the complex and crossed seismic profiles attribute, the feedback information is confirmed from the linchpin attributes (waveform, delay, main-frequency, bandwidth), which reflect the features of seismic profiles through the optimization of seismic profiles attributes. By analyzing all aspects on the key attributes of seismic profiles in the process of synthetic seismograms, the feedback mechanism system was established. According to each key attribute difference wavelet extraction method improvement direction was confirmed to achieve the purpose of wavelet accuracy.In the premise of higher reflection coefficient sequences precision estimated by deconvolution and feedback information accuracy optimized by attributes analysis of seismic profile, the method is used to validate and fix the wavelet estimated by the parameterized modeling method combining of linear (cumulant matrix method) and nonlinear (cumulant fitting method).Under the primitive wavelet known conditions, the theoretical and experimental data simulation results show that the comparison between the second wavelet estimated by synthetic seismic records and the original wavelet can verify the wavelet extraction method combining linear and nonlinear validity. It can also verify that deconvolution can improve the characteristics of seismic records resolution. Under the primitive wavelet unknown conditions, using the comparison result of the seismic profile linchpin attributes can improve wavelet extraction method effects and improve wavelet precision.