Title | ||
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A Born-WKBJ Pre-Stack Seismic Inversion Based on a 3-D Structural-Geology Model Building |
Abstract | ||
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Estimation of subsurface properties by using the scattering integral equation is a method that finds increasing use in near-surface and shallow oil/gas exploration, based on seismic, low-frequency electromagnetic, and surface-radar surveys. The method can accurately simulate physical realizations induced by small-scale perturbations, but its accuracy depends on a suitable low-frequency property model. We propose a 3-D geological-structure-guided model building to provide a reliable low-frequency model and combine it with the Born-Wentzel-Kramers-Brillouin-Jeffreys (WKBJ)-approximation-based inversion algorithm. Instead of the traditional approach based on artificially interpreted horizons, we use 3-D seismic-slope attributes as lateral constraints, which contain more geological information. Plane-wave destruction (PWD) in 3-D is exploited to extract the 2-D slopes along the inline and crossline directions, which are the key factors in computing 3-D slopes. Then, by introducing the shaping regularization, we build low-frequency models by solving the inverse problem. Numerical analysis indicates that an appropriate background model is essential for seismic modeling with the Born-WKBJ approximation. The methodology is applied to synthetic and 3-D field data, and the examples show that it provides reliable background models and improves the inversion performance. |
Year | DOI | Venue |
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2022 | 10.1109/TGRS.2021.3103430 | IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING |
Keywords | DocType | Volume |
Mathematical model, Computational modeling, Buildings, Solid modeling, Geology, Analytical models, Numerical models, 3-D structure constraints, Born-Wentzel-Kramers-Brillouin-Jeffreys (WKBJ) approximation, model building, pre-stack seismic inversion | Journal | 60 |
ISSN | Citations | PageRank |
0196-2892 | 0 | 0.34 |
References | Authors | |
0 | 4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Cong Luo | 1 | 0 | 3.38 |
Jing Ba | 2 | 0 | 1.35 |
Guangtan Huang | 3 | 1 | 3.08 |
Jose M. Carcione | 4 | 0 | 0.68 |