Nonlinear FAVO Dispersion Quantification Based on the Analytical Solution of the Viscoelastic Wave Equation
Wave-induced fluid flow is the main cause of seismic attenuation and dispersion. So the estimated velocity dispersion information can be used to identify reservoir fluid and effectively reduce the risk of reservoir drilling. Using equivalence of dispersion and attenuation between poroelastic and vis...
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2020-01-01
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Series: | Geofluids |
Online Access: | http://dx.doi.org/10.1155/2020/7616045 |
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doaj-7698e0be31b6435b8ee893493913f37d2020-11-25T03:13:29ZengHindawi-WileyGeofluids1468-81151468-81232020-01-01202010.1155/2020/76160457616045Nonlinear FAVO Dispersion Quantification Based on the Analytical Solution of the Viscoelastic Wave EquationYuanqiang Li0Jingye Li1Xiaohong Chen2Jian Zhang3Chen Zhou4Wei Tang5State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing, ChinaState Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing, ChinaState Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing, ChinaState Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing, ChinaState Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing, ChinaState Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing, ChinaWave-induced fluid flow is the main cause of seismic attenuation and dispersion. So the estimated velocity dispersion information can be used to identify reservoir fluid and effectively reduce the risk of reservoir drilling. Using equivalence of dispersion and attenuation between poroelastic and viscoelastic media, we developed the method of FAVO (frequency-dependent amplitude variation with offset) dispersion quantitative estimation based on the analytical solution of 1D viscoelastic wave equation. Compared with the current single-interface velocity dispersion estimation method, the new nonlinear approach uses the analytical solution of 1D viscoelastic wave equation as the forward modeling engine. This method can conveniently handle the attenuation and generate the full-wave field response of a layered medium. First, the compound matrix method (CMM) was applied to rapidly obtain the analytical solution by vectorization. Further, we analyzed the seismic response characteristics through the model data to clarify the effectiveness of the forward modeling method. Then, the more reliable P-wave velocity, S-wave velocity, and density were recovered based on prestack viscoelastic waveform inversion (PVWI). Combining with the inversion results, the derivative matrix was calculated to perform nonlinear velocity dispersion estimation. Finally, the new estimation method was tested with the model and actual data. The experiments show that the developed method is clearly superior to the single-interface dispersion estimation method in accuracy and resolution. This approach can be used as a new choice reservoir fluid identification.http://dx.doi.org/10.1155/2020/7616045 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yuanqiang Li Jingye Li Xiaohong Chen Jian Zhang Chen Zhou Wei Tang |
spellingShingle |
Yuanqiang Li Jingye Li Xiaohong Chen Jian Zhang Chen Zhou Wei Tang Nonlinear FAVO Dispersion Quantification Based on the Analytical Solution of the Viscoelastic Wave Equation Geofluids |
author_facet |
Yuanqiang Li Jingye Li Xiaohong Chen Jian Zhang Chen Zhou Wei Tang |
author_sort |
Yuanqiang Li |
title |
Nonlinear FAVO Dispersion Quantification Based on the Analytical Solution of the Viscoelastic Wave Equation |
title_short |
Nonlinear FAVO Dispersion Quantification Based on the Analytical Solution of the Viscoelastic Wave Equation |
title_full |
Nonlinear FAVO Dispersion Quantification Based on the Analytical Solution of the Viscoelastic Wave Equation |
title_fullStr |
Nonlinear FAVO Dispersion Quantification Based on the Analytical Solution of the Viscoelastic Wave Equation |
title_full_unstemmed |
Nonlinear FAVO Dispersion Quantification Based on the Analytical Solution of the Viscoelastic Wave Equation |
title_sort |
nonlinear favo dispersion quantification based on the analytical solution of the viscoelastic wave equation |
publisher |
Hindawi-Wiley |
series |
Geofluids |
issn |
1468-8115 1468-8123 |
publishDate |
2020-01-01 |
description |
Wave-induced fluid flow is the main cause of seismic attenuation and dispersion. So the estimated velocity dispersion information can be used to identify reservoir fluid and effectively reduce the risk of reservoir drilling. Using equivalence of dispersion and attenuation between poroelastic and viscoelastic media, we developed the method of FAVO (frequency-dependent amplitude variation with offset) dispersion quantitative estimation based on the analytical solution of 1D viscoelastic wave equation. Compared with the current single-interface velocity dispersion estimation method, the new nonlinear approach uses the analytical solution of 1D viscoelastic wave equation as the forward modeling engine. This method can conveniently handle the attenuation and generate the full-wave field response of a layered medium. First, the compound matrix method (CMM) was applied to rapidly obtain the analytical solution by vectorization. Further, we analyzed the seismic response characteristics through the model data to clarify the effectiveness of the forward modeling method. Then, the more reliable P-wave velocity, S-wave velocity, and density were recovered based on prestack viscoelastic waveform inversion (PVWI). Combining with the inversion results, the derivative matrix was calculated to perform nonlinear velocity dispersion estimation. Finally, the new estimation method was tested with the model and actual data. The experiments show that the developed method is clearly superior to the single-interface dispersion estimation method in accuracy and resolution. This approach can be used as a new choice reservoir fluid identification. |
url |
http://dx.doi.org/10.1155/2020/7616045 |
work_keys_str_mv |
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