Geostatistical Filtering of Noisy Seismic Data Using Stochastic Partial Differential Equations (SPDE)
M. Pereira, C. Magneron and N. Desassis
Event name: Petroleum Geostatistics 2019
Session: Seismic Reservoir Characterization I
Publication date: 02 September 2019
Info: Extended abstract, PDF ( 697.93Kb )
Price: € 20
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.