Geology and Applied Geophysics Research Group, School of Earth Sciences, Energy and Environment, Yachay Tech University, Hacienda San José, Urcuquí, 100119, Ecuador
Saba Infante
Numerical Analysis and Data Science Research Group, School of Mathematical and Computational Sciences, Hacienda San José, Urcuquí, 100119, Ecuador
Department of Mathematics, FACyT Universidad de Carabobo, Naguanagua, Valencia, 2005, Venezuela
Gabriel Barragan
Numerical Analysis and Data Science Research Group, School of Mathematical and Computational Sciences, Hacienda San José, Urcuquí, 100119, Ecuador
Raul Manzanilla
Numerical Analysis and Data Science Research Group, School of Mathematical and Computational Sciences, Hacienda San José, Urcuquí, 100119, Ecuador
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1,241
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EndNote: 204
Views and downloads (calculated since 21 Oct 2024)
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Total article views: 375 (including HTML, PDF, and XML)
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259
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375
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31
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Total article views: 4,278 (including HTML, PDF, and XML)
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2,645
1,146
487
4,278
82
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HTML: 2,645
PDF: 1,146
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Total: 4,278
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Viewed (geographical distribution)
Total article views: 4,653 (including HTML, PDF, and XML)
Thereof 4,649 with geography defined
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Total article views: 375 (including HTML, PDF, and XML)
Thereof 371 with geography defined
and 4 with unknown origin.
Total article views: 4,278 (including HTML, PDF, and XML)
Thereof 4,278 with geography defined
and 0 with unknown origin.
We explored four methods to improve how underground rock properties are estimated from seismic data. By comparing these methods on both simulated and real-world oilfield data, we found that techniques using gradient information give better accuracy but require more computing time. Our results help guide the choice of method depending on whether speed or precision is more important in subsurface exploration.
We explored four methods to improve how underground rock properties are estimated from seismic...