Blar i Department of Earth Science på forfatter "Iversen, Einar"
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Higher-order Hamilton–Jacobi perturbation theory for anisotropic heterogeneous media: dynamic ray tracing in Cartesian coordinates
Iversen, Einar; Ursin, Bjørn; Saksala, Teemu; Ilmavirta, Joonas; de Hoop, Maarten (Peer reviewed; Journal article, 2019)With a Hamilton–Jacobi equation in Cartesian coordinates as a starting point, it is common to use a system of ordinary differential equations describing the continuation of first-order derivatives of phase-space perturbations ... -
Higher-order Hamilton–Jacobi perturbation theory for anisotropic heterogeneous media: dynamic ray tracing in ray-centred coordinates
Iversen, Einar; Ursin, Bjørn; Saksala, Teemu; Ilmavirta, Joonas; V. de Hoop, Maarten (Journal article; Peer reviewed, 2021)Dynamic ray tracing is a robust and efficient method for computation of amplitude and phase attributes of the high-frequency Green’s function. A formulation of dynamic ray tracing in Cartesian coordinates was recently ... -
Microseismic wavefield modelling in anisotropic elastic media using integral equation method
Shekhar, Ujjwal; Jakobsen, Morten; Iversen, Einar; Berre, Inga; Radu, Florin Adrian (Journal article; Peer reviewed, 2023)In this paper, we present a frequency-domain volume integral method to model the microseismic wavefield in heterogeneous anisotropic-elastic media. The elastic wave equation is written as an integral equation of the ... -
On the accuracy and spatial sampling of finite-difference modelling in discontinuous models
Tschache, Saskia; Vinje, Vetle; Iversen, Einar (Journal article; Peer reviewed, 2022)Finite-difference modelling estimates the wavefield in the subsurface by solving the elastic or acoustic wave equation numerically in a discrete version of the subsurface. The derivatives in the wave equation are approximated ... -
Source and receiver deghosting by demigration-based supervised learning
Jonge, Thomas de; Vinje, Vetle; Zhao, Peng; Poole, Gordon; Iversen, Einar (Journal article; Peer reviewed, 2022)Deghosting of marine seismic data is an important and challenging step in the seismic processing flow. We describe a novel approach to train a supervised convolutional neural network to perform joint source and receiver ...