Rock Physics Model Constrained Viscoacoustic Full Waveform Inversion for Saturation and Porosity Estimation

Saturation and porosity are important indicators for the quantitative assessment of reservoir fluids. With the progress of seismic inversion methods, reconstructing saturation and porosity from seismic elastic parameters has become one of the most effective approaches. Theoretically, full waveform inversion (FWI) is the highest resolution method to reconstruct elastic parameters, and selecting appropriate parameters can enhance the accuracy of fluid monitoring. For partially saturated rocks, both P-wave velocity (Vp) and attenuation are sensitive to variations in fluid saturation and porosity. As a result, we can estimate the fluid state by inverting Vp, quality factor (Q), fluid saturation, and porosity. We propose a rock physics model constrained viscoacoustic FWI (RP-QFWI) method to estimate the fluid saturation and porosity directly from seismic records. Specifically, we use the extended Gassmann equation to constrain viscoacoustic FWI (QFWI). We evaluate the performance of RP-QFWI using the classic Frio-II CO2 injection model, a CO2 injection model based on an oil field, as well as a field seismic data. The results indicate that, for elastic parameters, the rock physics prior constraints improved the inversion accuracy and stabilized the inversion of weak parameters Q. For reservoir parameters, combining the two-step process into a single inversion method fully exploits the information in the seismic data, leading to more accurate inversion results.

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Publication Details

Journal
IEEE Transactions on Geoscience and Remote Sensing
Published
2025-01-01
DOI
https://doi.org/10.1109/tgrs.2025.3597976
Primary Topic
Seismic Imaging and Inversion Techniques
Type
article
Field-Weighted Citation Impact
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article

Rock Physics Model Constrained Viscoacoustic Full Waveform Inversion for Saturation and Porosity Estimation

Chao Huang, Luanxiao Zhao, Yuzhu Liu, Liangguo Dong et al.
IEEE Transactions on Geoscience and Remote Sensing
Seismic Imaging and Inversion Techniques
article

Rock Physics Model Constrained Viscoacoustic Full Waveform Inversion for Saturation and Porosity Estimation

Chao Huang, Luanxiao Zhao, Yuzhu Liu, Liangguo Dong, Yifan Zheng
article en

Abstract

Saturation and porosity are important indicators for the quantitative assessment of reservoir fluids. With the progress of seismic inversion methods, reconstructing saturation and porosity from seismic elastic parameters has become one of the most effective approaches. Theoretically, full waveform inversion (FWI) is the highest resolution method to reconstruct elastic parameters, and selecting appropriate parameters can enhance the accuracy of fluid monitoring. For partially saturated rocks, both P-wave velocity (Vp) and attenuation are sensitive to variations in fluid saturation and porosity. As a result, we can estimate the fluid state by inverting Vp, quality factor (Q), fluid saturation, and porosity. We propose a rock physics model constrained viscoacoustic FWI (RP-QFWI) method to estimate the fluid saturation and porosity directly from seismic records. Specifically, we use the extended Gassmann equation to constrain viscoacoustic FWI (QFWI). We evaluate the performance of RP-QFWI using the classic Frio-II CO2 injection model, a CO2 injection model based on an oil field, as well as a field seismic data. The results indicate that, for elastic parameters, the rock physics prior constraints improved the inversion accuracy and stabilized the inversion of weak parameters Q. For reservoir parameters, combining the two-step process into a single inversion method fully exploits the information in the seismic data, leading to more accurate inversion results.

IEEE Transactions on Geoscience and Remote SensingVol. 63
Tongji University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China, Fundamental Research Funds for the Central Universities
Climate action
Openalex Percentile: Top 78%
Seismic Imaging and Inversion Techniques
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