Quantitative tools for seismic stratigraphy and lithology characterization
Seismological images represent maps of the earth's structure. Apparent bandwidth limitation of seismic data prevents successful estimation of transition sharpness by the multiscale wavelet transform. We discuss the application of two recently developed techniques for (non-linear) singularity an...
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| Format: | Technical Report |
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Massachusetts Institute of Technology. Earth Resources Laboratory
2012
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| Online Access: | http://hdl.handle.net/1721.1/68607 |
| _version_ | 1811072689771642880 |
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| author | Herrmann, Felix |
| author2 | Massachusetts Institute of Technology. Earth Resources Laboratory |
| author_facet | Massachusetts Institute of Technology. Earth Resources Laboratory Herrmann, Felix |
| author_sort | Herrmann, Felix |
| collection | MIT |
| description | Seismological images represent maps of the earth's structure. Apparent bandwidth limitation of seismic data prevents successful estimation of transition sharpness by the multiscale wavelet transform. We discuss the application of two recently developed techniques for (non-linear) singularity analysis designed for bandwidth limited data, such as imaged seismic reflectivity.
The first method is a generalization of Mallat's modulus maxima approach to a method capable of estimating coarse-grained local scaling/sharpness/Hölder regularity of edges/transitions from data residing at essentially one single scale. The method is based on a non-linear criterion predicting the (dis)appearance of local maxima as a function of the data's fractional integrations/differentiations.
The second method is an extension of an atomic decomposition technique based on the greedy Matching Pursuit Algorithm. Instead of the ordinary Spline Wavelet Packet Basis, our method uses multiple Fractional Spline Wavelet Packet Bases, especially designed for seismic reflectivity data. The first method excels in pinpointing the location of the singularities (the stratigraphy). The second method improves the singularity characterization by providing information on the transition's location, magnitude, scale, order and direction (anti-/causal/symmetric). Moreover, the atomic decomposition entails data compression, denoising and deconvolution.
The output of both methods produces a map of the earth's singularity structure. These maps can be overlayed with seismic data, thus providing us with a means to more precisely characterize the seismic reflectivity's litho-stratigraphical information content. |
| first_indexed | 2024-09-23T09:10:17Z |
| format | Technical Report |
| id | mit-1721.1/68607 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T09:10:17Z |
| publishDate | 2012 |
| publisher | Massachusetts Institute of Technology. Earth Resources Laboratory |
| record_format | dspace |
| spelling | mit-1721.1/686072019-04-10T21:08:47Z Quantitative tools for seismic stratigraphy and lithology characterization Herrmann, Felix Massachusetts Institute of Technology. Earth Resources Laboratory Herrmann, Felix Seismological images represent maps of the earth's structure. Apparent bandwidth limitation of seismic data prevents successful estimation of transition sharpness by the multiscale wavelet transform. We discuss the application of two recently developed techniques for (non-linear) singularity analysis designed for bandwidth limited data, such as imaged seismic reflectivity. The first method is a generalization of Mallat's modulus maxima approach to a method capable of estimating coarse-grained local scaling/sharpness/Hölder regularity of edges/transitions from data residing at essentially one single scale. The method is based on a non-linear criterion predicting the (dis)appearance of local maxima as a function of the data's fractional integrations/differentiations. The second method is an extension of an atomic decomposition technique based on the greedy Matching Pursuit Algorithm. Instead of the ordinary Spline Wavelet Packet Basis, our method uses multiple Fractional Spline Wavelet Packet Bases, especially designed for seismic reflectivity data. The first method excels in pinpointing the location of the singularities (the stratigraphy). The second method improves the singularity characterization by providing information on the transition's location, magnitude, scale, order and direction (anti-/causal/symmetric). Moreover, the atomic decomposition entails data compression, denoising and deconvolution. The output of both methods produces a map of the earth's singularity structure. These maps can be overlayed with seismic data, thus providing us with a means to more precisely characterize the seismic reflectivity's litho-stratigraphical information content. Massachusetts Institute of Technology. Industry Consortia 2012-01-17T18:45:33Z 2012-01-17T18:45:33Z 2001 Technical Report http://hdl.handle.net/1721.1/68607 Earth Resources Laboratory Industry Consortia Annual Report;2001-02 application/pdf Massachusetts Institute of Technology. Earth Resources Laboratory |
| spellingShingle | Herrmann, Felix Quantitative tools for seismic stratigraphy and lithology characterization |
| title | Quantitative tools for seismic stratigraphy and lithology characterization |
| title_full | Quantitative tools for seismic stratigraphy and lithology characterization |
| title_fullStr | Quantitative tools for seismic stratigraphy and lithology characterization |
| title_full_unstemmed | Quantitative tools for seismic stratigraphy and lithology characterization |
| title_short | Quantitative tools for seismic stratigraphy and lithology characterization |
| title_sort | quantitative tools for seismic stratigraphy and lithology characterization |
| url | http://hdl.handle.net/1721.1/68607 |
| work_keys_str_mv | AT herrmannfelix quantitativetoolsforseismicstratigraphyandlithologycharacterization |