Characterization of complex fluvial-deltaic deposits in Northeast India using Poisson impedance inversion and non-parametric statistical technique
Abstract Characterizing complex fluvial-deltaic deposits is a challenging task for finding hydrocarbon discoveries. We described a methodology for predicting the hydrocarbon zones from complex well-log and prestack seismic data. In this current study, data analysis involves an integrated framework b...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2022-10-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-21444-5 |
| _version_ | 1797996153305825280 |
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| author | M. Nagendra Babu Venkatesh Ambati Rajesh R. Nair |
| author_facet | M. Nagendra Babu Venkatesh Ambati Rajesh R. Nair |
| author_sort | M. Nagendra Babu |
| collection | DOAJ |
| description | Abstract Characterizing complex fluvial-deltaic deposits is a challenging task for finding hydrocarbon discoveries. We described a methodology for predicting the hydrocarbon zones from complex well-log and prestack seismic data. In this current study, data analysis involves an integrated framework based on Simultaneous prestack seismic inversion (SPSI), target correlation coefficient analysis (TCCA), Poisson impedance inversion, and non-parametric statistical analysis, and Bayesian classification. First, seismic elastic attributes from prestack seismic data were estimated. They can provide the spatial distribution of petrophysical properties of seismic data. Then target correlation coefficient analysis (TCCA) was estimated roration factor “c” from well-log data. Using the seismic elastic attributes and rotation factor “c”, Poisson impedance inversion was performed to predict the Poisson impedance volume. Finally, Bayesian classification integrated the Poisson impedance volume with non-parametric probabilistic density functions (PDFs) to estimate the spatial distribution of lithofacies. Despite complex characteristics in the elastic properties, the current study successfully delineated the complex fluvial-details deposits. These results were verified with conventional findings through numerical analysis. |
| first_indexed | 2024-04-11T10:12:55Z |
| format | Article |
| id | doaj.art-71bd83e8f2ca45398893d81dabf658f6 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-11T10:12:55Z |
| publishDate | 2022-10-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-71bd83e8f2ca45398893d81dabf658f62022-12-22T04:30:03ZengNature PortfolioScientific Reports2045-23222022-10-0112111310.1038/s41598-022-21444-5Characterization of complex fluvial-deltaic deposits in Northeast India using Poisson impedance inversion and non-parametric statistical techniqueM. Nagendra Babu0Venkatesh Ambati1Rajesh R. Nair2Computational Petroleum Geomechanics Laboratory, Department of Ocean Engineering, Indian Institute of Technology MadrasComputational Petroleum Geomechanics Laboratory, Department of Ocean Engineering, Indian Institute of Technology MadrasComputational Petroleum Geomechanics Laboratory, Department of Ocean Engineering, Indian Institute of Technology MadrasAbstract Characterizing complex fluvial-deltaic deposits is a challenging task for finding hydrocarbon discoveries. We described a methodology for predicting the hydrocarbon zones from complex well-log and prestack seismic data. In this current study, data analysis involves an integrated framework based on Simultaneous prestack seismic inversion (SPSI), target correlation coefficient analysis (TCCA), Poisson impedance inversion, and non-parametric statistical analysis, and Bayesian classification. First, seismic elastic attributes from prestack seismic data were estimated. They can provide the spatial distribution of petrophysical properties of seismic data. Then target correlation coefficient analysis (TCCA) was estimated roration factor “c” from well-log data. Using the seismic elastic attributes and rotation factor “c”, Poisson impedance inversion was performed to predict the Poisson impedance volume. Finally, Bayesian classification integrated the Poisson impedance volume with non-parametric probabilistic density functions (PDFs) to estimate the spatial distribution of lithofacies. Despite complex characteristics in the elastic properties, the current study successfully delineated the complex fluvial-details deposits. These results were verified with conventional findings through numerical analysis.https://doi.org/10.1038/s41598-022-21444-5 |
| spellingShingle | M. Nagendra Babu Venkatesh Ambati Rajesh R. Nair Characterization of complex fluvial-deltaic deposits in Northeast India using Poisson impedance inversion and non-parametric statistical technique Scientific Reports |
| title | Characterization of complex fluvial-deltaic deposits in Northeast India using Poisson impedance inversion and non-parametric statistical technique |
| title_full | Characterization of complex fluvial-deltaic deposits in Northeast India using Poisson impedance inversion and non-parametric statistical technique |
| title_fullStr | Characterization of complex fluvial-deltaic deposits in Northeast India using Poisson impedance inversion and non-parametric statistical technique |
| title_full_unstemmed | Characterization of complex fluvial-deltaic deposits in Northeast India using Poisson impedance inversion and non-parametric statistical technique |
| title_short | Characterization of complex fluvial-deltaic deposits in Northeast India using Poisson impedance inversion and non-parametric statistical technique |
| title_sort | characterization of complex fluvial deltaic deposits in northeast india using poisson impedance inversion and non parametric statistical technique |
| url | https://doi.org/10.1038/s41598-022-21444-5 |
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