Application of Inverse Deconvolution Algorithm. Eastern Siberia Case Study

Nowadays the algorithm of “robust” surface-consistent deconvolution is widely used. Many seismic data processing companies practice the implementation of fairly aggressive noise attenuation workflows while evaluating trace spectra for subsequent decomposition. However, aggressive noise reduction is often performed in a quick mode without extensive testing and for these reasons is worse than the final version of production noise attenuation workflow. One possible way to solve this problem is to derive and re-calculate deconvolution operators after noise attenuation procedures. The convolution is a linear transformation, which allows us to declare its complete reversibility, and, consequently, the reversibility of the entire procedure of surface-consistent deconvolution. Due to data analysis of a clean dataset without noise interference allowed us to noticeably improve the amplitude-frequency characteristics especially in the low-frequency zone. Another advantage of this approach is the ability to significantly improve the performance of processing large volumes that involve new data acquisition during project fulfillment. In this paper, we consider examples using the reversibility of the deconvolution procedure in a data processing graph.