Two-dimensional weighted stack determination using signal-to-noise ratios and probability statistics
Abstract To improve the stacking effect in seismic signal processing, we use a weighted stack algorithm that considers the differences in signal-to-noise ratios (SNR) between seismic traces. The statistical properties of the weights in this weighted stack algorithm, such as variance and standard dev...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Zhang, Geng [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2014 |
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| Schlagwörter: |
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| Anmerkung: |
© Akadémiai Kiadó 2014 |
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| Übergeordnetes Werk: |
Enthalten in: Acta geodaetica et geophysica Hungarica - Budapest : Akad. Kiadó, 1997, 49(2014), 4 vom: 25. Okt., Seite 431-440 |
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| Übergeordnetes Werk: |
volume:49 ; year:2014 ; number:4 ; day:25 ; month:10 ; pages:431-440 |
| Links: |
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| DOI / URN: |
10.1007/s40328-014-0073-5 |
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SPR037150723 |
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| 520 | |a Abstract To improve the stacking effect in seismic signal processing, we use a weighted stack algorithm that considers the differences in signal-to-noise ratios (SNR) between seismic traces. The statistical properties of the weights in this weighted stack algorithm, such as variance and standard deviation, are the same as those of the SNR in each trace. We propose using a windowing technique to expand the weight in each seismic trace in “time,” resulting in a two-dimensional weight that varies with both “space” and “time.” A simulation test is conducted under the same conditions. The result shows that the improved two-dimensional weight is more effective. Then, we apply the two-dimensional weight to the multiple detection technique and the multiple coverage technique to determine the optimal condition for the use of such a weighted stack; we find that it is most effective when there are differences in the SNRs or regular noise interference in each seismic trace. It is thus clear that our weighted stack algorithm is more suitable for the multiple coverage techniques. | ||
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10.1007/s40328-014-0073-5 doi (DE-627)SPR037150723 (SPR)s40328-014-0073-5-e DE-627 ger DE-627 rakwb eng Zhang, Geng verfasserin aut Two-dimensional weighted stack determination using signal-to-noise ratios and probability statistics 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Akadémiai Kiadó 2014 Abstract To improve the stacking effect in seismic signal processing, we use a weighted stack algorithm that considers the differences in signal-to-noise ratios (SNR) between seismic traces. The statistical properties of the weights in this weighted stack algorithm, such as variance and standard deviation, are the same as those of the SNR in each trace. We propose using a windowing technique to expand the weight in each seismic trace in “time,” resulting in a two-dimensional weight that varies with both “space” and “time.” A simulation test is conducted under the same conditions. The result shows that the improved two-dimensional weight is more effective. Then, we apply the two-dimensional weight to the multiple detection technique and the multiple coverage technique to determine the optimal condition for the use of such a weighted stack; we find that it is most effective when there are differences in the SNRs or regular noise interference in each seismic trace. It is thus clear that our weighted stack algorithm is more suitable for the multiple coverage techniques. Weighted stack (dpeaa)DE-He213 SNR, Denoising (dpeaa)DE-He213 Two-dimensional weight (dpeaa)DE-He213 Multiple coverage technology (dpeaa)DE-He213 Seismic signal processing (dpeaa)DE-He213 Tuo, Xianguo aut Wang, Kaiyang aut Li, Bin aut Liu, Mingzhe aut Enthalten in Acta geodaetica et geophysica Hungarica Budapest : Akad. Kiadó, 1997 49(2014), 4 vom: 25. Okt., Seite 431-440 (DE-627)364470852 (DE-600)2110468-2 1587-1037 nnns volume:49 year:2014 number:4 day:25 month:10 pages:431-440 https://dx.doi.org/10.1007/s40328-014-0073-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 AR 49 2014 4 25 10 431-440 |
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10.1007/s40328-014-0073-5 doi (DE-627)SPR037150723 (SPR)s40328-014-0073-5-e DE-627 ger DE-627 rakwb eng Zhang, Geng verfasserin aut Two-dimensional weighted stack determination using signal-to-noise ratios and probability statistics 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Akadémiai Kiadó 2014 Abstract To improve the stacking effect in seismic signal processing, we use a weighted stack algorithm that considers the differences in signal-to-noise ratios (SNR) between seismic traces. The statistical properties of the weights in this weighted stack algorithm, such as variance and standard deviation, are the same as those of the SNR in each trace. We propose using a windowing technique to expand the weight in each seismic trace in “time,” resulting in a two-dimensional weight that varies with both “space” and “time.” A simulation test is conducted under the same conditions. The result shows that the improved two-dimensional weight is more effective. Then, we apply the two-dimensional weight to the multiple detection technique and the multiple coverage technique to determine the optimal condition for the use of such a weighted stack; we find that it is most effective when there are differences in the SNRs or regular noise interference in each seismic trace. It is thus clear that our weighted stack algorithm is more suitable for the multiple coverage techniques. Weighted stack (dpeaa)DE-He213 SNR, Denoising (dpeaa)DE-He213 Two-dimensional weight (dpeaa)DE-He213 Multiple coverage technology (dpeaa)DE-He213 Seismic signal processing (dpeaa)DE-He213 Tuo, Xianguo aut Wang, Kaiyang aut Li, Bin aut Liu, Mingzhe aut Enthalten in Acta geodaetica et geophysica Hungarica Budapest : Akad. Kiadó, 1997 49(2014), 4 vom: 25. Okt., Seite 431-440 (DE-627)364470852 (DE-600)2110468-2 1587-1037 nnns volume:49 year:2014 number:4 day:25 month:10 pages:431-440 https://dx.doi.org/10.1007/s40328-014-0073-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 AR 49 2014 4 25 10 431-440 |
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10.1007/s40328-014-0073-5 doi (DE-627)SPR037150723 (SPR)s40328-014-0073-5-e DE-627 ger DE-627 rakwb eng Zhang, Geng verfasserin aut Two-dimensional weighted stack determination using signal-to-noise ratios and probability statistics 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Akadémiai Kiadó 2014 Abstract To improve the stacking effect in seismic signal processing, we use a weighted stack algorithm that considers the differences in signal-to-noise ratios (SNR) between seismic traces. The statistical properties of the weights in this weighted stack algorithm, such as variance and standard deviation, are the same as those of the SNR in each trace. We propose using a windowing technique to expand the weight in each seismic trace in “time,” resulting in a two-dimensional weight that varies with both “space” and “time.” A simulation test is conducted under the same conditions. The result shows that the improved two-dimensional weight is more effective. Then, we apply the two-dimensional weight to the multiple detection technique and the multiple coverage technique to determine the optimal condition for the use of such a weighted stack; we find that it is most effective when there are differences in the SNRs or regular noise interference in each seismic trace. It is thus clear that our weighted stack algorithm is more suitable for the multiple coverage techniques. Weighted stack (dpeaa)DE-He213 SNR, Denoising (dpeaa)DE-He213 Two-dimensional weight (dpeaa)DE-He213 Multiple coverage technology (dpeaa)DE-He213 Seismic signal processing (dpeaa)DE-He213 Tuo, Xianguo aut Wang, Kaiyang aut Li, Bin aut Liu, Mingzhe aut Enthalten in Acta geodaetica et geophysica Hungarica Budapest : Akad. Kiadó, 1997 49(2014), 4 vom: 25. Okt., Seite 431-440 (DE-627)364470852 (DE-600)2110468-2 1587-1037 nnns volume:49 year:2014 number:4 day:25 month:10 pages:431-440 https://dx.doi.org/10.1007/s40328-014-0073-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 AR 49 2014 4 25 10 431-440 |
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10.1007/s40328-014-0073-5 doi (DE-627)SPR037150723 (SPR)s40328-014-0073-5-e DE-627 ger DE-627 rakwb eng Zhang, Geng verfasserin aut Two-dimensional weighted stack determination using signal-to-noise ratios and probability statistics 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Akadémiai Kiadó 2014 Abstract To improve the stacking effect in seismic signal processing, we use a weighted stack algorithm that considers the differences in signal-to-noise ratios (SNR) between seismic traces. The statistical properties of the weights in this weighted stack algorithm, such as variance and standard deviation, are the same as those of the SNR in each trace. We propose using a windowing technique to expand the weight in each seismic trace in “time,” resulting in a two-dimensional weight that varies with both “space” and “time.” A simulation test is conducted under the same conditions. The result shows that the improved two-dimensional weight is more effective. Then, we apply the two-dimensional weight to the multiple detection technique and the multiple coverage technique to determine the optimal condition for the use of such a weighted stack; we find that it is most effective when there are differences in the SNRs or regular noise interference in each seismic trace. It is thus clear that our weighted stack algorithm is more suitable for the multiple coverage techniques. Weighted stack (dpeaa)DE-He213 SNR, Denoising (dpeaa)DE-He213 Two-dimensional weight (dpeaa)DE-He213 Multiple coverage technology (dpeaa)DE-He213 Seismic signal processing (dpeaa)DE-He213 Tuo, Xianguo aut Wang, Kaiyang aut Li, Bin aut Liu, Mingzhe aut Enthalten in Acta geodaetica et geophysica Hungarica Budapest : Akad. Kiadó, 1997 49(2014), 4 vom: 25. Okt., Seite 431-440 (DE-627)364470852 (DE-600)2110468-2 1587-1037 nnns volume:49 year:2014 number:4 day:25 month:10 pages:431-440 https://dx.doi.org/10.1007/s40328-014-0073-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 AR 49 2014 4 25 10 431-440 |
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10.1007/s40328-014-0073-5 doi (DE-627)SPR037150723 (SPR)s40328-014-0073-5-e DE-627 ger DE-627 rakwb eng Zhang, Geng verfasserin aut Two-dimensional weighted stack determination using signal-to-noise ratios and probability statistics 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Akadémiai Kiadó 2014 Abstract To improve the stacking effect in seismic signal processing, we use a weighted stack algorithm that considers the differences in signal-to-noise ratios (SNR) between seismic traces. The statistical properties of the weights in this weighted stack algorithm, such as variance and standard deviation, are the same as those of the SNR in each trace. We propose using a windowing technique to expand the weight in each seismic trace in “time,” resulting in a two-dimensional weight that varies with both “space” and “time.” A simulation test is conducted under the same conditions. The result shows that the improved two-dimensional weight is more effective. Then, we apply the two-dimensional weight to the multiple detection technique and the multiple coverage technique to determine the optimal condition for the use of such a weighted stack; we find that it is most effective when there are differences in the SNRs or regular noise interference in each seismic trace. It is thus clear that our weighted stack algorithm is more suitable for the multiple coverage techniques. Weighted stack (dpeaa)DE-He213 SNR, Denoising (dpeaa)DE-He213 Two-dimensional weight (dpeaa)DE-He213 Multiple coverage technology (dpeaa)DE-He213 Seismic signal processing (dpeaa)DE-He213 Tuo, Xianguo aut Wang, Kaiyang aut Li, Bin aut Liu, Mingzhe aut Enthalten in Acta geodaetica et geophysica Hungarica Budapest : Akad. Kiadó, 1997 49(2014), 4 vom: 25. Okt., Seite 431-440 (DE-627)364470852 (DE-600)2110468-2 1587-1037 nnns volume:49 year:2014 number:4 day:25 month:10 pages:431-440 https://dx.doi.org/10.1007/s40328-014-0073-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 AR 49 2014 4 25 10 431-440 |
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two-dimensional weighted stack determination using signal-to-noise ratios and probability statistics |
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Two-dimensional weighted stack determination using signal-to-noise ratios and probability statistics |
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Abstract To improve the stacking effect in seismic signal processing, we use a weighted stack algorithm that considers the differences in signal-to-noise ratios (SNR) between seismic traces. The statistical properties of the weights in this weighted stack algorithm, such as variance and standard deviation, are the same as those of the SNR in each trace. We propose using a windowing technique to expand the weight in each seismic trace in “time,” resulting in a two-dimensional weight that varies with both “space” and “time.” A simulation test is conducted under the same conditions. The result shows that the improved two-dimensional weight is more effective. Then, we apply the two-dimensional weight to the multiple detection technique and the multiple coverage technique to determine the optimal condition for the use of such a weighted stack; we find that it is most effective when there are differences in the SNRs or regular noise interference in each seismic trace. It is thus clear that our weighted stack algorithm is more suitable for the multiple coverage techniques. © Akadémiai Kiadó 2014 |
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Abstract To improve the stacking effect in seismic signal processing, we use a weighted stack algorithm that considers the differences in signal-to-noise ratios (SNR) between seismic traces. The statistical properties of the weights in this weighted stack algorithm, such as variance and standard deviation, are the same as those of the SNR in each trace. We propose using a windowing technique to expand the weight in each seismic trace in “time,” resulting in a two-dimensional weight that varies with both “space” and “time.” A simulation test is conducted under the same conditions. The result shows that the improved two-dimensional weight is more effective. Then, we apply the two-dimensional weight to the multiple detection technique and the multiple coverage technique to determine the optimal condition for the use of such a weighted stack; we find that it is most effective when there are differences in the SNRs or regular noise interference in each seismic trace. It is thus clear that our weighted stack algorithm is more suitable for the multiple coverage techniques. © Akadémiai Kiadó 2014 |
| abstract_unstemmed |
Abstract To improve the stacking effect in seismic signal processing, we use a weighted stack algorithm that considers the differences in signal-to-noise ratios (SNR) between seismic traces. The statistical properties of the weights in this weighted stack algorithm, such as variance and standard deviation, are the same as those of the SNR in each trace. We propose using a windowing technique to expand the weight in each seismic trace in “time,” resulting in a two-dimensional weight that varies with both “space” and “time.” A simulation test is conducted under the same conditions. The result shows that the improved two-dimensional weight is more effective. Then, we apply the two-dimensional weight to the multiple detection technique and the multiple coverage technique to determine the optimal condition for the use of such a weighted stack; we find that it is most effective when there are differences in the SNRs or regular noise interference in each seismic trace. It is thus clear that our weighted stack algorithm is more suitable for the multiple coverage techniques. © Akadémiai Kiadó 2014 |
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