Approximation of seismic velocities from the spectrum of weighted graphs

Abstract Extracting seismic velocities from recorded seismic data requires converting the shot gathers to mid-point gathers, calculating the velocity spectrum, and picking the velocity values. In this paper, we propose to use graph theory to extract the seismic velocity values directly from the mid-...
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Autor*in:	Alfuraidan, Monther Rashed [verfasserIn] Al-Shuhail, Abdullatif Hanafy, Sherif M. Sarumi, Ibrahim O.

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Seismic velocity Seismic migration Weighted graph Graph spectral radius

Anmerkung:	© The Author(s) 2023

Übergeordnetes Werk:	Enthalten in: GEM - Berlin : Springer, 2010, 14(2023), 1 vom: 13. März
Übergeordnetes Werk:	volume:14 ; year:2023 ; number:1 ; day:13 ; month:03

Links:	Volltext

DOI / URN:	10.1007/s13137-023-00214-z

Katalog-ID:	SPR049675591

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520			\|a Abstract Extracting seismic velocities from recorded seismic data requires converting the shot gathers to mid-point gathers, calculating the velocity spectrum, and picking the velocity values. In this paper, we propose to use graph theory to extract the seismic velocity values directly from the mid-point gathers. We use spectral data of a weighted graph model for approximating the seismic velocity. We develop a regression model to predict the seismic velocity from the largest eigenvalue of the graph representing the physical system. The approach is tested on a synthetic seismic data that represent a typical near-surface geological situation. The method was able to predict the seismic velocity of the second layer with 99.4% accuracy.
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allfields	10.1007/s13137-023-00214-z doi (DE-627)SPR049675591 (SPR)s13137-023-00214-z-e DE-627 ger DE-627 rakwb eng Alfuraidan, Monther Rashed verfasserin (orcid)0000-0002-3641-290X aut Approximation of seismic velocities from the spectrum of weighted graphs 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract Extracting seismic velocities from recorded seismic data requires converting the shot gathers to mid-point gathers, calculating the velocity spectrum, and picking the velocity values. In this paper, we propose to use graph theory to extract the seismic velocity values directly from the mid-point gathers. We use spectral data of a weighted graph model for approximating the seismic velocity. We develop a regression model to predict the seismic velocity from the largest eigenvalue of the graph representing the physical system. The approach is tested on a synthetic seismic data that represent a typical near-surface geological situation. The method was able to predict the seismic velocity of the second layer with 99.4% accuracy. Seismic velocity (dpeaa)DE-He213 Seismic migration (dpeaa)DE-He213 Weighted graph (dpeaa)DE-He213 Graph spectral radius (dpeaa)DE-He213 Al-Shuhail, Abdullatif aut Hanafy, Sherif M. aut Sarumi, Ibrahim O. (orcid)0000-0001-8202-4708 aut Enthalten in GEM Berlin : Springer, 2010 14(2023), 1 vom: 13. März (DE-627)631499296 (DE-600)2564274-1 1869-2680 nnns volume:14 year:2023 number:1 day:13 month:03 https://dx.doi.org/10.1007/s13137-023-00214-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 14 2023 1 13 03
spelling	10.1007/s13137-023-00214-z doi (DE-627)SPR049675591 (SPR)s13137-023-00214-z-e DE-627 ger DE-627 rakwb eng Alfuraidan, Monther Rashed verfasserin (orcid)0000-0002-3641-290X aut Approximation of seismic velocities from the spectrum of weighted graphs 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract Extracting seismic velocities from recorded seismic data requires converting the shot gathers to mid-point gathers, calculating the velocity spectrum, and picking the velocity values. In this paper, we propose to use graph theory to extract the seismic velocity values directly from the mid-point gathers. We use spectral data of a weighted graph model for approximating the seismic velocity. We develop a regression model to predict the seismic velocity from the largest eigenvalue of the graph representing the physical system. The approach is tested on a synthetic seismic data that represent a typical near-surface geological situation. The method was able to predict the seismic velocity of the second layer with 99.4% accuracy. Seismic velocity (dpeaa)DE-He213 Seismic migration (dpeaa)DE-He213 Weighted graph (dpeaa)DE-He213 Graph spectral radius (dpeaa)DE-He213 Al-Shuhail, Abdullatif aut Hanafy, Sherif M. aut Sarumi, Ibrahim O. (orcid)0000-0001-8202-4708 aut Enthalten in GEM Berlin : Springer, 2010 14(2023), 1 vom: 13. März (DE-627)631499296 (DE-600)2564274-1 1869-2680 nnns volume:14 year:2023 number:1 day:13 month:03 https://dx.doi.org/10.1007/s13137-023-00214-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 14 2023 1 13 03
allfields_unstemmed	10.1007/s13137-023-00214-z doi (DE-627)SPR049675591 (SPR)s13137-023-00214-z-e DE-627 ger DE-627 rakwb eng Alfuraidan, Monther Rashed verfasserin (orcid)0000-0002-3641-290X aut Approximation of seismic velocities from the spectrum of weighted graphs 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract Extracting seismic velocities from recorded seismic data requires converting the shot gathers to mid-point gathers, calculating the velocity spectrum, and picking the velocity values. In this paper, we propose to use graph theory to extract the seismic velocity values directly from the mid-point gathers. We use spectral data of a weighted graph model for approximating the seismic velocity. We develop a regression model to predict the seismic velocity from the largest eigenvalue of the graph representing the physical system. The approach is tested on a synthetic seismic data that represent a typical near-surface geological situation. The method was able to predict the seismic velocity of the second layer with 99.4% accuracy. Seismic velocity (dpeaa)DE-He213 Seismic migration (dpeaa)DE-He213 Weighted graph (dpeaa)DE-He213 Graph spectral radius (dpeaa)DE-He213 Al-Shuhail, Abdullatif aut Hanafy, Sherif M. aut Sarumi, Ibrahim O. (orcid)0000-0001-8202-4708 aut Enthalten in GEM Berlin : Springer, 2010 14(2023), 1 vom: 13. März (DE-627)631499296 (DE-600)2564274-1 1869-2680 nnns volume:14 year:2023 number:1 day:13 month:03 https://dx.doi.org/10.1007/s13137-023-00214-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 14 2023 1 13 03
allfieldsGer	10.1007/s13137-023-00214-z doi (DE-627)SPR049675591 (SPR)s13137-023-00214-z-e DE-627 ger DE-627 rakwb eng Alfuraidan, Monther Rashed verfasserin (orcid)0000-0002-3641-290X aut Approximation of seismic velocities from the spectrum of weighted graphs 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract Extracting seismic velocities from recorded seismic data requires converting the shot gathers to mid-point gathers, calculating the velocity spectrum, and picking the velocity values. In this paper, we propose to use graph theory to extract the seismic velocity values directly from the mid-point gathers. We use spectral data of a weighted graph model for approximating the seismic velocity. We develop a regression model to predict the seismic velocity from the largest eigenvalue of the graph representing the physical system. The approach is tested on a synthetic seismic data that represent a typical near-surface geological situation. The method was able to predict the seismic velocity of the second layer with 99.4% accuracy. Seismic velocity (dpeaa)DE-He213 Seismic migration (dpeaa)DE-He213 Weighted graph (dpeaa)DE-He213 Graph spectral radius (dpeaa)DE-He213 Al-Shuhail, Abdullatif aut Hanafy, Sherif M. aut Sarumi, Ibrahim O. (orcid)0000-0001-8202-4708 aut Enthalten in GEM Berlin : Springer, 2010 14(2023), 1 vom: 13. März (DE-627)631499296 (DE-600)2564274-1 1869-2680 nnns volume:14 year:2023 number:1 day:13 month:03 https://dx.doi.org/10.1007/s13137-023-00214-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 14 2023 1 13 03
allfieldsSound	10.1007/s13137-023-00214-z doi (DE-627)SPR049675591 (SPR)s13137-023-00214-z-e DE-627 ger DE-627 rakwb eng Alfuraidan, Monther Rashed verfasserin (orcid)0000-0002-3641-290X aut Approximation of seismic velocities from the spectrum of weighted graphs 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract Extracting seismic velocities from recorded seismic data requires converting the shot gathers to mid-point gathers, calculating the velocity spectrum, and picking the velocity values. In this paper, we propose to use graph theory to extract the seismic velocity values directly from the mid-point gathers. We use spectral data of a weighted graph model for approximating the seismic velocity. We develop a regression model to predict the seismic velocity from the largest eigenvalue of the graph representing the physical system. The approach is tested on a synthetic seismic data that represent a typical near-surface geological situation. The method was able to predict the seismic velocity of the second layer with 99.4% accuracy. Seismic velocity (dpeaa)DE-He213 Seismic migration (dpeaa)DE-He213 Weighted graph (dpeaa)DE-He213 Graph spectral radius (dpeaa)DE-He213 Al-Shuhail, Abdullatif aut Hanafy, Sherif M. aut Sarumi, Ibrahim O. (orcid)0000-0001-8202-4708 aut Enthalten in GEM Berlin : Springer, 2010 14(2023), 1 vom: 13. März (DE-627)631499296 (DE-600)2564274-1 1869-2680 nnns volume:14 year:2023 number:1 day:13 month:03 https://dx.doi.org/10.1007/s13137-023-00214-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 14 2023 1 13 03
language	English
source	Enthalten in GEM 14(2023), 1 vom: 13. März volume:14 year:2023 number:1 day:13 month:03
sourceStr	Enthalten in GEM 14(2023), 1 vom: 13. März volume:14 year:2023 number:1 day:13 month:03
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Seismic velocity Seismic migration Weighted graph Graph spectral radius
isfreeaccess_bool	true
container_title	GEM
authorswithroles_txt_mv	Alfuraidan, Monther Rashed @@aut@@ Al-Shuhail, Abdullatif @@aut@@ Hanafy, Sherif M. @@aut@@ Sarumi, Ibrahim O. @@aut@@
publishDateDaySort_date	2023-03-13T00:00:00Z
hierarchy_top_id	631499296
id	SPR049675591
language_de	englisch
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author	Alfuraidan, Monther Rashed
spellingShingle	Alfuraidan, Monther Rashed misc Seismic velocity misc Seismic migration misc Weighted graph misc Graph spectral radius Approximation of seismic velocities from the spectrum of weighted graphs
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topic_title	Approximation of seismic velocities from the spectrum of weighted graphs Seismic velocity (dpeaa)DE-He213 Seismic migration (dpeaa)DE-He213 Weighted graph (dpeaa)DE-He213 Graph spectral radius (dpeaa)DE-He213
topic	misc Seismic velocity misc Seismic migration misc Weighted graph misc Graph spectral radius
topic_unstemmed	misc Seismic velocity misc Seismic migration misc Weighted graph misc Graph spectral radius
topic_browse	misc Seismic velocity misc Seismic migration misc Weighted graph misc Graph spectral radius
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title	Approximation of seismic velocities from the spectrum of weighted graphs
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title_full	Approximation of seismic velocities from the spectrum of weighted graphs
author_sort	Alfuraidan, Monther Rashed
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author_browse	Alfuraidan, Monther Rashed Al-Shuhail, Abdullatif Hanafy, Sherif M. Sarumi, Ibrahim O.
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author-letter	Alfuraidan, Monther Rashed
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title_sort	approximation of seismic velocities from the spectrum of weighted graphs
title_auth	Approximation of seismic velocities from the spectrum of weighted graphs
abstract	Abstract Extracting seismic velocities from recorded seismic data requires converting the shot gathers to mid-point gathers, calculating the velocity spectrum, and picking the velocity values. In this paper, we propose to use graph theory to extract the seismic velocity values directly from the mid-point gathers. We use spectral data of a weighted graph model for approximating the seismic velocity. We develop a regression model to predict the seismic velocity from the largest eigenvalue of the graph representing the physical system. The approach is tested on a synthetic seismic data that represent a typical near-surface geological situation. The method was able to predict the seismic velocity of the second layer with 99.4% accuracy. © The Author(s) 2023
abstractGer	Abstract Extracting seismic velocities from recorded seismic data requires converting the shot gathers to mid-point gathers, calculating the velocity spectrum, and picking the velocity values. In this paper, we propose to use graph theory to extract the seismic velocity values directly from the mid-point gathers. We use spectral data of a weighted graph model for approximating the seismic velocity. We develop a regression model to predict the seismic velocity from the largest eigenvalue of the graph representing the physical system. The approach is tested on a synthetic seismic data that represent a typical near-surface geological situation. The method was able to predict the seismic velocity of the second layer with 99.4% accuracy. © The Author(s) 2023
abstract_unstemmed	Abstract Extracting seismic velocities from recorded seismic data requires converting the shot gathers to mid-point gathers, calculating the velocity spectrum, and picking the velocity values. In this paper, we propose to use graph theory to extract the seismic velocity values directly from the mid-point gathers. We use spectral data of a weighted graph model for approximating the seismic velocity. We develop a regression model to predict the seismic velocity from the largest eigenvalue of the graph representing the physical system. The approach is tested on a synthetic seismic data that represent a typical near-surface geological situation. The method was able to predict the seismic velocity of the second layer with 99.4% accuracy. © The Author(s) 2023
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title_short	Approximation of seismic velocities from the spectrum of weighted graphs
url	https://dx.doi.org/10.1007/s13137-023-00214-z
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author2	Al-Shuhail, Abdullatif Hanafy, Sherif M. Sarumi, Ibrahim O.
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doi_str	10.1007/s13137-023-00214-z
up_date	2024-07-04T01:49:18.063Z
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Approximation of seismic velocities from the spectrum of weighted graphs

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