SUMMARY

Subbasalt seismic processing commonly faces challenges from severe scattering losses by impedance contrasts and rugose surfaces, geometrical spreading, strong multiples and velocity heterogeneity. As a result, conventional methods fail to reveal enough information about the subbasalt structures, and...

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Other Authors: The Pennsylvania State University CiteSeerX Archives
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Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.620.3739
http://setur.fo/uploads/tx_userpubrep/ngyuen_2008_04.pdf
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spelling ftciteseerx:oai:CiteSeerX.psu:10.1.1.620.3739 2023-05-15T16:10:51+02:00 SUMMARY The Pennsylvania State University CiteSeerX Archives application/pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.620.3739 http://setur.fo/uploads/tx_userpubrep/ngyuen_2008_04.pdf en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.620.3739 http://setur.fo/uploads/tx_userpubrep/ngyuen_2008_04.pdf Metadata may be used without restrictions as long as the oai identifier remains attached to it. http://setur.fo/uploads/tx_userpubrep/ngyuen_2008_04.pdf text ftciteseerx 2016-01-08T14:58:50Z Subbasalt seismic processing commonly faces challenges from severe scattering losses by impedance contrasts and rugose surfaces, geometrical spreading, strong multiples and velocity heterogeneity. As a result, conventional methods fail to reveal enough information about the subbasalt structures, and velocity models derived from reflection data are equally suspect, with multiples interfering with primaries. The fundamental problem is that for most cases the real data are unconstrained – we do not know what the correct answer is and therefore we cannot identify the optimal image. Thus we have to make decisions driven by need rather than knowledge. One way to address this problem is to generate synthetic data for which the correct result is known, and then process these data as a test of our strategy. By demonstrating that we can recover the correct result and gain confidence in handling of the real data. In this paper, we present this workflow and propose a processing strategy for the GlyVeST seismic data acquired in the Faroe Islands. The synthetic data, produced by an elastic finite-difference (FD) modeling scheme, offer excellent possibilities for detailed studies of how a seismic wave interact with heterogeneous basalt flows, as well as detailed understanding of the multiple problem. Text Faroe Islands Unknown Faroe Islands
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description Subbasalt seismic processing commonly faces challenges from severe scattering losses by impedance contrasts and rugose surfaces, geometrical spreading, strong multiples and velocity heterogeneity. As a result, conventional methods fail to reveal enough information about the subbasalt structures, and velocity models derived from reflection data are equally suspect, with multiples interfering with primaries. The fundamental problem is that for most cases the real data are unconstrained – we do not know what the correct answer is and therefore we cannot identify the optimal image. Thus we have to make decisions driven by need rather than knowledge. One way to address this problem is to generate synthetic data for which the correct result is known, and then process these data as a test of our strategy. By demonstrating that we can recover the correct result and gain confidence in handling of the real data. In this paper, we present this workflow and propose a processing strategy for the GlyVeST seismic data acquired in the Faroe Islands. The synthetic data, produced by an elastic finite-difference (FD) modeling scheme, offer excellent possibilities for detailed studies of how a seismic wave interact with heterogeneous basalt flows, as well as detailed understanding of the multiple problem.
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url http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.620.3739
http://setur.fo/uploads/tx_userpubrep/ngyuen_2008_04.pdf
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