A PROPOSAL FOR REGULARIZED INVERSION FOR AN ILL-CONDITIONED DECONVOLUTION OPERATOR
ABSTRACT From the inverse problem theory aspect, deconvolution can be understood as the linear inversion of an ill-posed and ill-conditioned problem. The ill-conditioned property of the deconvolution operator make the solution of inverse problem sensitive to errors in the data. Tikhonov regularizati...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Instituto Colombiano del Petróleo (ICP) - ECOPETROL S.A.
2013-12-01
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| Series: | CT&F Ciencia, Tecnología & Futuro |
| Subjects: | |
| Online Access: | http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0122-53832013000200003&lng=en&tlng=en |
| _version_ | 1811181097042575360 |
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| author | Herling Gonzalez Sheryl Avendaño German Camacho |
| author_facet | Herling Gonzalez Sheryl Avendaño German Camacho |
| author_sort | Herling Gonzalez |
| collection | DOAJ |
| description | ABSTRACT From the inverse problem theory aspect, deconvolution can be understood as the linear inversion of an ill-posed and ill-conditioned problem. The ill-conditioned property of the deconvolution operator make the solution of inverse problem sensitive to errors in the data. Tikhonov regularization is the most commonly used method for stability and uniqueness of the solution. However, results from Tikhonov method do not provide sufficient quality when the noise in the data is strong. This work uses the conjugate gradient method applied to the Tikhonov deconvolution scheme, including a regularization parameter calculated iteratively and based on the improvement criterion of Morozov discrepancy applied on the objective function. Using seismic synthetic data and real stacked seismic data, we carried out a deconvolution process with regularization and without regularization based on a conjugated gradient algorithm. A comparison of results is also presented. Applying regularized deconvolution on synthetic data shows improved stability on the solution. Additionally, real post-stack seismic data shows a direct application for increasing the vertical resolution even with noisy data. |
| first_indexed | 2024-04-11T09:14:00Z |
| format | Article |
| id | doaj.art-7be5f8545cf54747bec552881372efef |
| institution | Directory Open Access Journal |
| issn | 0122-5383 |
| language | English |
| last_indexed | 2024-04-11T09:14:00Z |
| publishDate | 2013-12-01 |
| publisher | Instituto Colombiano del Petróleo (ICP) - ECOPETROL S.A. |
| record_format | Article |
| series | CT&F Ciencia, Tecnología & Futuro |
| spelling | doaj.art-7be5f8545cf54747bec552881372efef2022-12-22T04:32:25ZengInstituto Colombiano del Petróleo (ICP) - ECOPETROL S.A.CT&F Ciencia, Tecnología & Futuro0122-53832013-12-01534759S0122-53832013000200003A PROPOSAL FOR REGULARIZED INVERSION FOR AN ILL-CONDITIONED DECONVOLUTION OPERATORHerling Gonzalez0Sheryl Avendaño1German Camacho2Ecopetrol S.A. - Instituto Colombiano del Petróleo (ICP)UTP ConsultoriasEcopetrol S.A. - Instituto Colombiano del Petróleo (ICP)ABSTRACT From the inverse problem theory aspect, deconvolution can be understood as the linear inversion of an ill-posed and ill-conditioned problem. The ill-conditioned property of the deconvolution operator make the solution of inverse problem sensitive to errors in the data. Tikhonov regularization is the most commonly used method for stability and uniqueness of the solution. However, results from Tikhonov method do not provide sufficient quality when the noise in the data is strong. This work uses the conjugate gradient method applied to the Tikhonov deconvolution scheme, including a regularization parameter calculated iteratively and based on the improvement criterion of Morozov discrepancy applied on the objective function. Using seismic synthetic data and real stacked seismic data, we carried out a deconvolution process with regularization and without regularization based on a conjugated gradient algorithm. A comparison of results is also presented. Applying regularized deconvolution on synthetic data shows improved stability on the solution. Additionally, real post-stack seismic data shows a direct application for increasing the vertical resolution even with noisy data.http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0122-53832013000200003&lng=en&tlng=enRegularización de TikhonovGradiente conjugadoTeoría de inversiónProcesamiento sísmico |
| spellingShingle | Herling Gonzalez Sheryl Avendaño German Camacho A PROPOSAL FOR REGULARIZED INVERSION FOR AN ILL-CONDITIONED DECONVOLUTION OPERATOR CT&F Ciencia, Tecnología & Futuro Regularización de Tikhonov Gradiente conjugado Teoría de inversión Procesamiento sísmico |
| title | A PROPOSAL FOR REGULARIZED INVERSION FOR AN ILL-CONDITIONED DECONVOLUTION OPERATOR |
| title_full | A PROPOSAL FOR REGULARIZED INVERSION FOR AN ILL-CONDITIONED DECONVOLUTION OPERATOR |
| title_fullStr | A PROPOSAL FOR REGULARIZED INVERSION FOR AN ILL-CONDITIONED DECONVOLUTION OPERATOR |
| title_full_unstemmed | A PROPOSAL FOR REGULARIZED INVERSION FOR AN ILL-CONDITIONED DECONVOLUTION OPERATOR |
| title_short | A PROPOSAL FOR REGULARIZED INVERSION FOR AN ILL-CONDITIONED DECONVOLUTION OPERATOR |
| title_sort | proposal for regularized inversion for an ill conditioned deconvolution operator |
| topic | Regularización de Tikhonov Gradiente conjugado Teoría de inversión Procesamiento sísmico |
| url | http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0122-53832013000200003&lng=en&tlng=en |
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