The use of Laguerre-Gauss transform in 2D reverse time migration imaging

Paniagua, Juan Guillermo

doi:10.1190/sbgf2017-250

Cited by 3 publications

(3 citation statements)

References 13 publications

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“…In horizontal profile, the intensity of the line profile was increased in all frequency values. These modifications are evidenced in the strong changes in the shape of the line profiles from the Fourier spectrum of the Laplacian image respect to the Fourier spectrum of cross-correlation image (Paniagua & Quintero, 2017a).…”

Section: Two-layer Modelmentioning

confidence: 99%

“…Third, we compare the images obtained by zero-lag cross-correlation imaging condition, Laplacian filtering, and the Laguerre Gauss filtering applied to three synthetic datasets, to present evidences from the effectiveness of our imaging implementation to reduce the low-frequency spatial noise. Then, we compare and analyze the Fourier spectra obtained by the 2D spatial fast Fourier transform of the images obtained by zero-lag cross-correlation imaging condition (ZL-CC-IC), zero-lag cross-correlation imaging condition plus Laplacian filtering (ZL-CC-IC-LP) and zero-lag cross-correlation imaging condition plus Laguerre-Gauss filtering (ZL-CC-IC-LG) in order to establish quantitative measurements of the spatial spectral features looking for the first step to determine the accuracy and enhancement capability of the method to reach better subsurface structures (Paniagua & Quintero, 2017a). Finally, by comparison we carefully demonstrate that despite the smoothed velocity models the Laguerre-Gauss filtering preserves well the reflections with their true locations and significantly attenuates the low-frequency noise in the image (Paniagua & Quintero, 2017b).…”

Section: Introductionmentioning

confidence: 99%

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Laguerre-Gauss Filters in Reverse Time Migration Image Reconstruction

2018

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ABSTRACT. Reverse time migration (RTM) solves the acoustic or elastic wave equation by means of the extrapolation from source and receiver wavefield in time. A migrated image is obtained by applying a criteria known as imaging condition. The cross-correlation between source and receiver wavefields is the commonly used imaging condition. However, this imaging condition produces spatial low-frequency noise, called artifacts, due to the unwanted correlation of the diving, head and backscattered waves. Several techniques have been proposed to reduce the artifacts occurrence. Derivative operators as Laplacian are the most frequently used. In this work, we propose a technique based on a spiral phase filter ranging from 0 to 2π, and a toroidal amplitude bandpass filter, known as Laguerre-Gauss transform. Through numerical experiments we present the application of this particular filter on three synthetic data sets. In addition, we present a comparative spectral study of images obtained by the zero-lag cross-correlation imaging condition, the Laplacian filtering and the Laguerre-Gauss filtering, showing their frequency features. We also present evidences not only with simulated noisy velocity fields but also by comparison with the model velocity field gradients that this method improves the RTM images by reducing the artifacts and notably enhance the reflective events. Keywords: Laguerre-Gauss transform, zero-lag cross-correlation, seismic migration, imaging condition. RESUMO. A migração reversa no tempo (RTM) resolve a equação de onda acústica ou elástica por meio da extrapolação a partir do campo de onda da fonte e do receptor no tempo. Uma imagem migrada é obtida aplicando um critério conhecido como condição de imagem. A correlação cruzada entre campos de onda de fonte e receptor é a condição de imagem comumente usada. No entanto, esta condição de imagem produz ruído espacial de baixa frequência, chamados artefatos, devido à correlação indesejada das ondas de mergulho, cabeça e retrodifusão. Várias técnicas têm sido propostas para reduzir a ocorrência de artefatos. Operadores derivados como Laplaciano são os mais utilizados. Neste trabalho, propomos uma técnica baseada em um filtro de fase espiral que varia de 0 a 2π, e um filtro passabanda de amplitude toroidal, conhecido como transformada de Laguerre-Gauss. Através de experimentos numéricos, apresentamos a aplicação deste filtro particular em três conjuntos de dados sintéticos. Além disso, apresentamos um estudo comparativo espectral de imagens obtidas pela condição de imagem de correlação cruzada atraso zero, a filtragem de Laplaciano e a filtragem Laguerre-Gauss, mostrando suas características de frequência. Apresentamos evidências não somente com campos simulados de velocidade ruidosa, mas também por comparação com os gradientes de campo de velocidade do modelo que este método melhora as imagens RTM, reduzindo os artefatos e aumentando notavelmente os eventos reflexivos. Palavras-chave: Transformação de Laguerre-Gauss, correlação cruzada atraso zero, migração sísmica, condição de imagem.

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Section: Two-layer Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Laguerre-Gauss Filters in Reverse Time Migration Image Reconstruction

2018

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“…Although the results obtained are promising, we apply the postprocessing technique proposed by Paniagua, Sierra-Sosa, & Quintero [22], Paniagua & Quintero [24] and Paniagua & Sierra-Sosa [25] on seismic migrated models obtained by the proposed method which were shown in Figure 8b and Figure 10b).…”

Section: (B)mentioning

confidence: 99%

Application of the continuous wavelet transform in the extraction of directional data on RTM imaging condition wavefields

Castrillón

Montoya

2018

CT&F Cienc. Tecnol. Futuro

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Low-frequency artifacts in reverse time migration result from unwanted cross-correlation of the source and receiver wavefields at non-reflecting points along ray-paths. These artifacts can hide important details in migrated models and increase poor interpretation risk. Some methods have been proposed to avoid or reduce the number of these artifacts, preserving reflections, and improving model quality, implementing other strategies such as modification of the wave equation, proposing other imaging conditions, and using image filtering techniques. One of these methods uses wavefield decomposition, correlating components of the wavefields that propagate in opposite directions. We propose a method for extracting directional information from the RTM imaging condition wavefields to obtain characteristics allowing for better, more refined imaging. The method works by separating directional information about the wavefields based on the continuous wavelet transform (CWT), and the analysis of the main changes on the frequency content revealed within the scalogram obtained by a Gaussian wavelet family. Through numerical applications, we demonstrate that this method can effectively remove undesired artifacts in migrated images. In addition, we use the Laguerre-Gauss filtering to improve the results obtained with the proposed method.

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From Artificial Intelligence to Deep Learning in Bio-medical Applications

Montoya

Paniagua

2020

Intelligent Systems Reference Library

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The use of Laguerre-Gauss transform in 2D reverse time migration imaging

Cited by 3 publications

References 13 publications

Laguerre-Gauss Filters in Reverse Time Migration Image Reconstruction

Laguerre-Gauss Filters in Reverse Time Migration Image Reconstruction

Application of the continuous wavelet transform in the extraction of directional data on RTM imaging condition wavefields

From Artificial Intelligence to Deep Learning in Bio-medical Applications

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