Application Of Finite Difference Eikonal Solver For Traveltime Computation In Forward Modeling And Migration

Abstract

Traveltime is one of the propagating wave’s components. As the wave propagates further, the traveltime increases. It can be computed by solving wave equation of the ray path or the eikonal wave equation. Accurate method of computing traveltimes will give a significant impact on enhancing the output of seismic forward modeling and migration. In seismic forward modeling, computation of the wave’s traveltime locally by ray tracing method leads to low resolution of the resulting seismic image, especially when the subsurface is having a complex geology. However, computing the wave’s traveltime with a gridding scheme by finite difference methods able to overcomes the problem. This paper aims to discuss the ability of ray tracing and fast marching method of finite difference in obtaining a seismic image that have more similarity with its subsurface model. We illustrated the results of the traveltime computation by both methods in form of ray path projection and wavefront. We employed these methods in forward modeling and compared both resulting seismic images. Seismic migration is executed as a part of quality control (QC). We used a synthetic velocity model which based on a part of Malay Basin geology structure. Our findings shows that the seismic images produced by the application of fast marching finite difference method has better resolution than ray tracing method especially on deeper part of subsurface model.

Multi‐model stacked structure based on particle swarm optimization for random noise attenuation of seismic data

“…To assess the proposed particle swarm optimization (PSO) algorithm in different scenarios, we used three synthetic examples consisting of linear crossings, hyperbolic and complex events obtained through forward modelling software, namely Tesseral (Majdi et al., 2021). First, we create a linear crossing event using a Ricker wavelet with a sampling rate of 2 ms.…”