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- W2092209396 abstract "Ray‐Based Stochastic Inversion (RBSI) was introduced in Verdel et al. (2004) as a new seismic inversion method for reservoir parameter estimation claimed to be more accurate than conventional Stochastic Inversion (SI) in laterally heterogeneous subsurfaces. In this paper, an RBSI‐variant is presented which utilises a 1D convolutional forward‐modeling kernel as found in common inversion software, offering great practical benefits. Synthetic datatests demonstrate the superiority of this variant, in its proper application regime, over SI in resolving reservoir‐layer‐ P‐velocities and thicknesses in strongly dipping subsurface structures. SI, under those circumstances, is severely affected by wavelet distortion due to migration." @default.
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- W2092209396 date "2005-01-01" @default.
- W2092209396 modified "2023-10-16" @default.
- W2092209396 title "Ray‐based stochastic inversion for reservoir parameters using 1D convolutional forward modeling" @default.
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- W2092209396 doi "https://doi.org/10.1190/1.2147960" @default.
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