Common reflection surface stack: A new parameter search strategy by global optimization

Garabito, German; Pavlov, João C.; Hubral, Peter; Costa, Jessé C.

doi:10.1190/1.1816536

Cited by 41 publications

(14 citation statements)

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“…) from multi‐coverage seismic data and for optimising the zero‐offset CRS kinematic attributes from prestack seismic data (Garabito et al . ; Minato et al . ).…”

Section: Parameter Estimation By Very Fast Simulated Annealingmentioning

confidence: 99%

Finite‐offset common reflection surface stack using global optimisation for parameter estimation: a land data example

Garabito

Cruz

Söllner

2016

Geophysical Prospecting

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In recent years, several research works dealing with velocity model independent seismic imaging have been published. These methods are capable of simulating arbitrary offset seismic sections by stacking a set of measured prestack seismic data along paraxial travel‐time surfaces. Hyperbolic common‐reflection‐surface travel‐time approximation is one of the most robust descriptions, which simulates not only zero‐offset but also finite‐offset sections with high accuracy from noisy multi‐coverage seismic data. In order to reconstruct seismic reflection events in common‐offset sections, the common‐reflection‐surface travel‐time approximation depends on five kinematic attributes (or parameters) for each selected point of the common‐offset seismic section. The main challenge of this method is to provide a computationally efficient data‐driven strategy for accurately determining the best set of parameters. Here, we introduce an approach for simultaneously estimating the five parameters from prestack seismic data by a very fast simulated annealing optimisation algorithm. For each sample point of the common‐offset section to be simulated, we determine only one set of common reflection surface attributes corresponding to the global maximum or the event with highest coherency. We applied our method of simultaneous global optimisation on synthetic and real data examples and showed the potential of the proposed strategy to enhance the reflection events in noisy data, even with very low signal‐to‐noise ratio. Finally, we demonstrate the regularisation capability of our method in a land seismic data example with missing traces for near, middle, and far offsets. In order to better appreciate the field data results, we present the time‐migrated sections with and without application of the proposed regularisation strategy.

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“…) from multi‐coverage seismic data and for optimising the zero‐offset CRS kinematic attributes from prestack seismic data (Garabito et al . ; Minato et al . ).…”

Section: Parameter Estimation By Very Fast Simulated Annealingmentioning

confidence: 99%

Finite‐offset common reflection surface stack using global optimisation for parameter estimation: a land data example

Garabito

Cruz

Söllner

2016

Geophysical Prospecting

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“…Following Garabito et al (2001) the three optimal CRS parameters (β * 0 , R N I P , R N ) are searched by three steps. At the first step we use formula (4) to determine β * 0 and R N I P .…”

Section: Theorymentioning

confidence: 99%

“…Optimization strategies to estimate these parameters are found in the literature (e.g. Müller (1999); Birgin et al (1999); Garabito et al (2001)). …”

Section: -D Zo Crs Stackmentioning

confidence: 99%

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2-D ZO CRS stack by considering an acquisition line with smooth topography

Chira-Oliva¹,

Cruz²,

Garabito³

et al. 2005

Rev. Bras. Geof.

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ABSTRACT. The land seismic data suffers from effects due to the near surface irregularities and the existence of topography. For obtaining a high resolution seismic image, these effects should be corrected by using seismic processing techniques, e.g. field and residual static corrections. The Common-Reflection-Surface (CRS) stack method is a new processing technique to simulate zero-offset (ZO) seismic sections from multi-coverage seismic data. It is based on a second-order hyperbolic paraxial traveltime approximation referred to a central normal ray. By considering a planar measurement surface, the CRS stacking operator is defined by means of three parameters, namely the emergence angle of the normal ray, the curvature of the normal incidence point (NIP) wave, and the curvature of the normal (N) wave. In this paper the 2-D ZO CRS stack method is modified in order to consider effects due to the smooth topography. By means of this new CRS formalism, we obtain a high resolution ZO seismic section, without applying static corrections. As by-products the 2-D ZO CRS stack method we estimate at each point of the ZO seismic section the three relevant parameters associated to the CRS stack process.Keywords: CRS stack, smooth topography, measurement surface curvature, near-surface irregularities. RESUMO.Os dados sísmicos terrestres são afetados pela existência de irregularidades na superfície de medição, e.g. a topografia. Neste sentido, para obter uma imagem sísmica de alta resolução, faz-se necessário corrigir estas irregularidades usando técnicas de processamento sísmico, e.g. correições estáticas residuais e de campo. O método de empilhamento Superfície de Reflexão Comum, CRS ("Common-Reflection-Surface", em inglês)é uma nova técnica de processamento para simular seções sísmicas com afastamento-nulo, ZO ("Zero-Offset", em inglês) a partir de dados sísmicos de cobertura múltipla. Este método baseia-se na aproximação hiperbólica de tempos de trânsito paraxiais de segunda ordem referido ao raio (central) normal. O operador de empilhamento CRS para uma superfície de medição planar depende de três parâmetros, denominados oângulo de emergência do raio normal, a curvatura da onda Ponto de Incidência Normal, NIP ("Normal Incidence Point", em inglês) e a curvatura da onda Normal, N. Neste artigo o método de empilhamento CRS ZO 2-Dé modificado com a finalidade de considerar uma superfície de medição com topografia suave também dependente desses parâmetros. Com este novo formalismo CRS, obtemos uma seção sísmica ZO de alta resolução, sem aplicar as correições estáticas, onde em cada ponto desta seção são estimados os três parâmetros relevantes do processo de empilhamento CRS.Palavras-chave: empilhamento CRS, topografia suave, curvatura da superfície de medição, irregularidades próximas da superfície.

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“…In the stacked section, a search for the emergence angle is conducted, followed by a search for the curvature. Garabito et al (2001) suggest the hybrid search as an extension of the pragmatic search. In this approach, the emergence angle and velocity are searched for simultaneously from prestack data.…”

Section: Introductionmentioning

confidence: 99%

Fast and robust common-reflection-surface parameter estimation

et al. 2018

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The common-reflection-surface (CRS) method offers a stack with higher signal-to-noise ratio at the cost of a timeconsuming semblance search to obtain the stacking parameters. We have developed a fast method for extracting the CRS parameters using local slope and curvature. We estimate the slope and curvature with the gradient structure tensor and quadratic structure tensor on stacked data. This is done under the assumption that a stacking velocity is already available. Our method was compared with an existing slopebased method, in which the slope is extracted from prestack data. An experiment on synthetic data shows that our method has increased robustness against noise compared with the existing method. When applied to two real data sets, our method achieves accuracy comparable with the pragmatic and full semblance searches. Our method has the advantage of being approximately two and four orders of magnitude faster than the semblance searches.

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Common reflection surface stack: A new parameter search strategy by global optimization

Cited by 41 publications

References 0 publications

Finite‐offset common reflection surface stack using global optimisation for parameter estimation: a land data example

Finite‐offset common reflection surface stack using global optimisation for parameter estimation: a land data example

2-D ZO CRS stack by considering an acquisition line with smooth topography

Fast and robust common-reflection-surface parameter estimation

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