Geostatistical Filtering of Noisy Seismic Data Using Stochastic Partial Differential Equations (SPDE)

Abstract

Summary An innovative geostatistical filtering approach is presented in this paper. It is based on Stochastic Partial Differential Equations (SPDE) and the idea is to solve kriging equations with the finite element method which requires the subdivision of a whole domain into simpler parts. This approach enables to deal with local variographic parameters while using a unique neighborhood even on large datasets. It opens the door to the operational processing of the most complex noise issues on seismic data. Post-stack and pre-stack. The methodology is described in details and two case studies are presented.