2013
DOI: 10.1111/1365-2478.12065
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3D elastic full‐waveform inversion of small‐scale heterogeneities in transmission geometry

Abstract: Three‐dimensional elastic full‐waveform inversion aims to reconstruct elastic material properties of 3D structures in the subsurface with high resolution. Here we present an implementation of 3D elastic full‐waveform inversion based on the adjoint‐state method. The code is optimized regarding runtime and storage costs by using a time‐frequency approach. The gradient is computed from monochromatic frequency‐domain particle‐velocity wavefields calculated with a time‐domain velocity‐stress finite‐difference schem… Show more

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Cited by 48 publications
(18 citation statements)
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References 49 publications
(97 reference statements)
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“…In most applications to field data, scattering of surface waves due to near-surface 3D structure might be significant. Unfortunately, 3D elastic FWI is still computationally too expensive for frequent repeat runs (Butzer et al, 2013) in a development environment. In this respect, we start with a 2D FWI that allows us to develop appropriate algorithms in an efficient way until sufficient computational power for routine full 3D FWI is available to all of us.…”
Section: Introductionmentioning
confidence: 99%
“…In most applications to field data, scattering of surface waves due to near-surface 3D structure might be significant. Unfortunately, 3D elastic FWI is still computationally too expensive for frequent repeat runs (Butzer et al, 2013) in a development environment. In this respect, we start with a 2D FWI that allows us to develop appropriate algorithms in an efficient way until sufficient computational power for routine full 3D FWI is available to all of us.…”
Section: Introductionmentioning
confidence: 99%
“…Previous studies have already presented results of 3D elastic full waveform inversion: [6,10,17,18,34,42,43,46]. In order to validate our approach in 3D, the SEG/EAGE Overhrust model is used.…”
Section: Application To 3d Elastic Full Waveform Inversionmentioning
confidence: 99%
“…Метод сопряженных гра-диентов [Hestenes, Stiefel, 1952] существенно со-кращает число необходимых направленных спусков. В приложениях чаще всего применяется либо нели-нейная версия метода сопряженных градиентов [Polak, Ribiere, 1969;Butzer et al, 2013], либо алгоритм Брой-дена-Флетчера-Гольдфарба-Шанно с ограничен-ной памятью (в англоязычной литературе -метод L-BFGS) [Nocedal, 1980;Brossier et al, 2009].…”
Section: построение итерационного процесса оптимизацииunclassified