Denoising and Storage in Seismic Reverse Time Migration

Abstract

Pre‐stack reverse time migration (RTM) is a very useful tool for seismic imaging. It has, however, some problems such as highly intensive computation cost, low‐frequency imaging noise and massy memory demand. The problem of time consuming for calculation can be solved by GPU/CPU collaborative computation. This paper focuses on suppressing noise and data storage. First, we analyze the generation mechanism of low‐frequency imaging noise and suggest that the phase and frequency spectra of seismic data are modified before migration and a Laplacian filter is used to remove the low wavenumber noise efficiently. Aiming at the problem of massy memory demand, we adopt the random boundary condition which sacrifices the computation cost but reduces the memory demand. The implementation can be performed on GPU and the communication between CPU and GPU can be saved to reduce the computation cost in another way. The tests on synthetic data examples illustrate that the difference between the migration result from the method of random boundary condition and that from the traditional method of saving the footprint of the wavefield can be overlooked.

Study on the Relation between Thermal Oxidation Kinetics of Raw Constant Viscosity Natural Rubber and Ageing Characteristics of Its Vulcanizate

“…The CVNR with medium Mooney viscosity can be obtained through adding aniline (0.03 phr) or semicarbazide hydrochloride. CVNR with high Mooney viscosity can be obtained through adding aniline (0.05 phr) or hydrazine hydrate [5].…”