SEISMIC SPARSE-LAYER REFLECTIVITY INVERSION USING BASIS PURSUIT DECOMPOSITION AND ELASTIC IMPEDANCE FOR DETECTING THIN LAYER OF GAS-SANDSTONE
Basis Pursuit Inversion (BPI) is a new seismic inversion method that based on sparse-layer concept. Seismic trace is assumed as convolution result of wavelet with odd and even dipole reflectivity pair with various thickness that represent sub-surface layer responses. Therefore, inversion problem can...
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| Main Author: | |
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/23951 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | Basis Pursuit Inversion (BPI) is a new seismic inversion method that based on sparse-layer concept. Seismic trace is assumed as convolution result of wavelet with odd and even dipole reflectivity pair with various thickness that represent sub-surface layer responses. Therefore, inversion problem can be formulated as the pursuit of coefficients that represent amplitude from the dipole reflectivity pair, in overcomplete dictionary matrix system. BPI using sparsity norm and regularization parameter in objective function that been optimized to searching the most sparse solution with minimum error. <br />
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In this research, BPI is applied to near, mid, and far pre-stack data to preserve elastic impedance inversion result. Application to real data show that BPI are able to resulting the geometry similarity from three elastic impedance angles and resolve thin layer of gas-sandstone that fit the well data better than Sparse Spike Inversion (SSI). |
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