Multiparametric traveltime inversion

In conventional seismic processing, the classical algorithm of Hubral and Krey is routinely applied to extract at? initial macrovelocity model that consists of a stack of homogeneous layers bounded by curved interfaces. Input for the algorithm are identified primary, reflections together with normal moveout (NMO) velocities, as derived from a previous velocity analysis conducted on common midpoint (CMP) data. This work presents a modified version of the Hubral and Krey algorithm that is designed to extend the original version in two ways, namely (a) it makes an advantageous use of previously obtained common-reflection-surface (CRS) attributes as its input and (b) it also allows for gradient layer velocities in depth. A new strategy to recover interfaces as optimized cubic splines is also proposed. Some synthetic examples are provided to illustrate and explain the implementation of the method.In conventional seismic processing, the classical algorithm of Hubral and Krey is routinely applied to extract at? initial macrovelocity model that consists of a stack of homogeneous layers bounded by curved interfaces. Input for the algorithm are identif462177192FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO97/12125-8SEM INFORMAÇÃ

Tempos de transito multiparametricos : estimação e inversão

Orientadores : Martin Tygel, Lucio Tunes dos SantosTese (doutorado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação CientificaResumo: Nesta tese, desenvolvemos um método, baseado no Algoritmo de Dix, para a estimação de um modelo de velocidade em profundidade. O método de Dix é capaz de construir um modelo com várias camadas homogêneas, separadas por interfaces curvas. Nosso método também gera modelos com essa estrutura. Porém, a velocidade em cada camada é uma função afim da profundidade. Desta forma, permitimos a presença de heterogeneidades, possibilitando um ajuste muito melhor dos dados. Além disso, utilizamos, como dados de entrada, os vários parâmetros cinemáticos, obtidos de maneira automática, pela técnica conhecida como Common Reflection Surface (CRS). Essa técnica é capaz de lidar diretamente com dados de multicobertura, fazendo um uso consistente de toda a informação disponível no levantamento sísmico. As estratégias convencionais usam quantidades cuja obtenção já se mostra um problema em si. Dado o maior grau de liberdade dos dados usados pelo método CRS, o tempo de trânsito depende de vários parâmetros. Estudamos também o problema de como estimar os parâmetros cinemáticos do tempo de trânsito que seriam usados para posterior inversão. Para tanto, foi aplicado um recente algoritmo de otimização, conhecido com Gradiente Espectral Projetado. Resultados promissores indicam o potencial de tal abordagem. Além disso, apresentamos uma aplicação para o modelo de velocidade construído. Desenvolvemos uma técnica para a obtenção de curvas de amplitude por afastamento (AVO) e amplitude por ângulo (AVA). Estas curvas são usadas pela indústria do petróleo para a caracterização de reservatórios. Sua obtenção implica um elevado custo computacional. O método proposto consiste em estimar o fator de espalhamento geométrico através de traçamento de raios no modelo invertido. Com isso, obtém-se as curvas AVO e A VA, para pontos de interesse em profundidade, a baixos custos computacionais. Os resultados para modelos sintéticos mostraram-se muito promissoresAbstract: For a fixed, central ray in an isotropic elastic or acoustic media, traveltime moveouts of rays in its vicinity can be described in terms of a certain number of parameters that refer to the central ray only. The determination of these parameters out of multicoverage data leads to very powerful algorithms that can be used for several imaging and inversion processes. Assuming two-dimensional propagation, the travei time expressions depend on three parameters directly related to the geometry of the unknown model in the vicinity of the central ray. We present a new method to extract these parameters out of coherency analysis applied directly to the data. Application of the method on a synthetic example shows an excellent performance of the algorithm both in accuracy and efficiency. The results obtained so far indicate that the algorithm may be a feasible option to solve the corresponding, harder, full three-dimensional problem, in which eight parameters, instead of three, are required. In conventional processing, the classical algorithm of Hubral and Krey is routinely applied to extract an initial macro-velocity model that consists of a stack of homogeneous layers bounded by curved interfaces. Input for the algorithm are identified primary reflections together with NMO velocities derived from a previous velocity analysis conducted on CMP data. We presents a modified version of the Hubral and Krey algorithm that is adapted to advantageously use the above described parameters (the CRS attributes) as its input. Moreover, each velocity layer is no longer restricted to be a constant, being now a affine function on depth. Finally, we present a method to obtain a true-amplitude migration and amplitude-versusangle (AVA) at selected points using the attributes generated by the CRS attributes. Our approach combines the CRS stackjinversion process applied to multicoverage data, together with the use of a kinematic Kirchhoff migration, to achieve true-amplitudes (TA) at assigned depth points of the migrated images. Our method is designed to aggregate amplitude information on selected points of a reflector, after a purely kinematic image (migration) has been obtained. The method is tested on a synthetic inhomogeneous layered model with good resultsDoutoradoDoutor em Matemática Aplicad

A frequency criterion for optimal node selection in smoothing with cubic splines

When smoothing a function with high-frequency noise by means of optimal cubic splines, it is often not clear how to choose the number of nodes. The more nodes are used, the closer the smoothed function will follow the noisy one. In this work, we show that more nodes mean a better approximation of Fourier coefficients for higher frequencies. Thus, the number of nodes can be determined by specifying a frequency up to which all Fourier coefficients must be preserved and increasing the number of nodes until this criterion is met. A comparison of the corresponding smoothing results with those obtained by filtering using moving average and moving median filters of corresponding length and a low pass with corresponding high-cut frequency shows that optimal cubic splines yield better results as they preserve not only the desired low-frequency band but also important high-frequency characteristics.When smoothing a function with high-frequency noise by means of optimal cubic splines, it is often not clear how to choose the number of nodes. The more nodes are used, the closer the smoothed function will follow the noisy one. In this work, we show that562229237CNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOFAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOSEM INFORMAÇÃOSEM INFORMAÇÃ

Dip correction for coherence-based time migration velocity analysis

Migration velocity analysis (MVA) is a seismic processing step that aims to translate residual moveout in an image gather after migration with an erroneous velocity model into velocity updates. An analysis of the position of a reflection event in an image gather after migration with an incorrect velocity allows us to extend the original coherence-based MVA approach to dipping reflectors. The extended MVA technique includes the reflector dip which is treated as an additional search parameter that is to be detected together with the velocity updating factor. Both parameters are searched for simultaneously by the application of two-parameter search techniques. The search consists of determining trial curves as a function of the search parameters and stacking the migrated data along these curves. The highest coherence determines the best-fitting curve and thus the optimal parameter pair. A numerical example demonstrates that the additional search parameter improves the quality of the velocity updates, thus requiring less iterations in the MVA.Migration velocity analysis (MVA) is a seismic processing step that aims to translate residual moveout in an image gather after migration with an erroneous velocity model into velocity updates. An analysis of the position of a reflection event in an image721S41S48CNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOFAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOSEM INFORMAÇÃOSEM INFORMAÇÃ

A statistics-based descriptor for automatic classification of scatterers in seismic sections

Discontinuities and small structures induce diffractions on seismic or ground-penetrating radar (GPR) acquisitions. Therefore, diffraction images can be used as a tool to access valuable information concerning subsurface scattering features, such as pinch outs, fractures, and edges. Usually, diffraction-imaging methods operate on diffraction events previously detected. Pattern-recognition methods are efficient to detect, image, and characterize diffractions. The use of this kind of approach, though, requires a numerical description of image points on a seismic section or radargram. We have investigated a new descriptor for seismic/GPR data that distinguishes diffractions from reflections. The descriptor consists of a set of statistical measures from diffraction operators sensitive to kinematic and dynamic aspects of an event. We develop experiments in which the proposed descriptor was incorporated into a pattern-recognition routine for diffraction imaging. The obtained method is useful for performing the automatic classification of image points using supervised and unsupervised algorithms, as a complementary step to Kirchhoff imaging. We also develop a new type of filtering, designed to address anomalies on the diffraction operators caused by interfering events. We evaluate the method using synthetic seismic data and real GPR data. Our results indicate that the descriptor correctly discriminates diffractions and shows promising results for low signal-to-noise-ratio situations8551SOZ2

A statistics-based descriptor for automatic classification of scatterers in seismic sections

Discontinuities and small structures induce diffractions on seismic or ground-penetrating radar (GPR) acquisitions. Therefore, diffraction images can be used as a tool to access valuable information concerning subsurface scattering features, such as pinch outs, fractures, and edges. Usually, diffraction-imaging methods operate on diffraction events previously detected. Pattern-recognition methods are efficient to detect, image, and characterize diffractions. The use of this kind of approach, though, requires a numerical description of image points on a seismic section or radargram. We have investigated a new descriptor for seismic/GPR data that distinguishes diffractions from reflections. The descriptor consists of a set of statistical measures from diffraction operators sensitive to kinematic and dynamic aspects of an event. We develop experiments in which the proposed descriptor was incorporated into a pattern-recognition routine for diffraction imaging. The obtained method is useful for performing the automatic classification of image points using supervised and unsupervised algorithms, as a complementary step to Kirchhoff imaging. We also develop a new type of filtering, designed to address anomalies on the diffraction operators caused by interfering events. We evaluate the method using synthetic seismic data and real GPR data. Our results indicate that the descriptor correctly discriminates diffractions and shows promising results for low signal-to-noise-ratio situations

Restricted optimization: a clue to a fast and accurate implementation of the Common Reflection Surface Stack method

For a fixed, central ray in an isotropic elastic or acoustic media, traveltime moveouts of rays in its vicinity can be described in terms of a certain number of parameters that refer to the central ray only. The determination of these parameters out of multicoverage data leads to very powerful algorithms that can be used for several imaging and inversion processes. Assuming two-dimensional propagation, the traveltime expressions depend on three parameters directly related to the geometry of the unknown model in the vicinity of the central ray. We present a new method to extract these parameters out of coherency analysis applied directly to the data. It uses (a) fast one-parameter searches on different sections extracted from the multi-coverage data to derive initial values of the sections parameters, and (b) the application of a recently introduced Spectral Projected Gradient optimization algorithm for the final parameter estimation. Application of the method on a synthetic example shows an excellent performance of the algorithm both in accuracy and efficiency. The results obtained so far indicate that the algorithm may be a feasible option to solve the corresponding, harder, full three-dimensional problem, in which eight parameters, instead of three, are required