Seismic multiples attenuating using Radon Transform and principal components

Seismic data is often contaminated with noise that must be attenuated before making reliable seismic interpretations. Seismic noise can be either random noise, which cannot be correlated between seismograms, or coherent noise, which shows patterns in the seismic gathers. Seismic multiples and ground rolls are good examples of coherent noise. My research focuses on optimizing some existing methods for multiples attenuation. My first project focused on optimizing the Radon Transform method to better attenuate seismic multiples. The Radon Transform method entails applying Normal Move Out (NMO) to the seismic Common Depth Point (CDP) gathers using the velocities of the primary signals to remove travel time delay with increasing offset and flatten seismic events. The NMO corrected CDP gathers are transformed to radon domain (intercept time (τ) – curvature (q)), where different seismic multiples and primaries are separated based on their curvatures. In the (τ –q) domain, NMO corrected CDP using primaries velocities depicts near zero curvature for primaries and positive curvatures for multiples. However, using primaries velocities for NMO often results in less distinction between primaries and multiples based on their move out in the (τ –q) domain. Thus, I used the intermediate velocities between primaries and multiples for the NMO correction of the CDP gathers input to the τ-q domain, which resulted in a more significant separation between multiples and primaries and improved multiples removal in the τ-q domain. The results showed better multiples removal as compared to using the conventional velocity radon, where CDP gathers are NMO corrected using the primaries velocities. Although applying multiples velocities seem to render more primaries-multiples move out, testing this method on more synthetic and real seismic gathers showed mixing of the primaries and multiples energy at the near offsets in the radon space. Thus, my second project used coherency as the foundation for attenuating multiples. I used the multiples velocities for NMO correction and the singular value decomposition (SVD) for attenuating multiples in the time domain. Using multiples velocity, the NMO flattened coherent multiples attributed to dominant principal components and can be separated from the unflatten primaries. Principal components attributing to multiples are selected and composed back to seismic traces. The selected multiples are then removed from the original data using simple subtraction. Results of multiples attenuation using Radon Transform and principal components methods were compared. The principal components method seemed to be more effective in multiples attenuation. This may be due to the principal component method improves the separation between flattened multiples and primaries and does not require data transformation to another domain, which often produces artifacts. Both methods opt for an unconventional velocity selection approach, resulting in enhanced performance of the parabolic radon and principal components methods for attenuating seismic multiples

Mechanisms and Models of Seismic Attenuation

Seismic attenuation is a subject of great interest for both industry and academia. In exploration seismology, wave attenuation must be well understood for interpreting seismic data and laboratory experiments with rocks, and improving the quality and resolution of reflection imaging of the subsurface. To achieve such understanding, mechanisms of seismic attenuation and the associated physical models need to be studied in detail. This dissertation focuses on analyzing several attenuation mechanisms and building first-principle mathematical models for them. The effects of seismic attenuation can be broadly subdivided into two groups: 1) caused by inelasticity of the material and 2) caused by small-scale elastic structures of the material or subsurface. From the first of these groups, I study solid viscosity and internal friction due to squirt flows and wave-induced fluid flows (WIFF) at different scales. This approach is based on a new rheological law called the General Linear Solid (GLS) and recently developed to describe macroscopic inelastic effects in multiphase solids. The GLS is a model composed by time/frequency independent parameters and based on Lagrangian continuum mechanics. By utilizing the GLS framework, I extend the well known-model called the Standard Linear Solid (SLS) to include internal inertial forces, which explains the primary wave and reveals additional highly diffusive wave modes. I also use the GLS to model P-waves with squirt flow dissipation by different configurations of the density, moduli, drag and solid viscosity matrices. Seismic wave attenuation may not only be caused by inelastic properties but also by elastic processes such as reflectivity and scattering. I examine two types of such effects of the elastic structure of the material. First, in a laboratory experiment with several rock types, there is a modest influence of sample size on the measured level of attenuation and modulus dispersion. Second, in a field experiment aimed at measuring Q from seismic reflectivity, the effect of elastic layering can be extremely strong and even completely equivalent to that of the Q. An important general observation from this study is that amplitude decays and phase delays measured from reflection seismic data can always be interpreted as either caused by inelasticity or by small-scale elastic structures. An important complementary goal of studying the mechanisms and effects of seismic attenuation consists in correcting for its effects in seismic records and increasing the resolution of seismic images. In this dissertation, I briefly consider attenuation-correction techniques and develop a novel method for such correction by using time-domain deconvolution. Synthetic and field data are used to illustrate and test the performance of this approach

IVGPR: A New Program for Advanced End-To-End GPR Processing

Ground penetrating radar (GPR) processing workflows commonly rely on techniques developed particularly for seismic reflection imaging. Although this practice has produced an abundance of reliable results, it is limited to basic applications. As the popularity of GPR continues to surge, a greater number of complex studies demand the use of routines that take into account the unique properties of GPR signals. Such is the case of surveys that examine the material properties of subsurface scatterers. The nature of these complicated tasks have created a demand for GPR-specific processing packages flexible enough to tackle new applications. Unlike seismic processing programs, however, GPR counterparts often afford only a limited amount of functionalities. This work produced a new GPR-specific processing package, dubbed IVGPR, that offers over 60 fully customizable procedures. This program was built using the modern Fortran programming language in combination with serial and parallel optimization practices that allow it to achieve high levels of performance. Within its many functions, IVGPR provides the rare opportunity to apply a three-dimensional single-component vector migration routine. This could be of great value for advanced workflows designed to develop and test new true-amplitude and inversion algorithms. Numerous examples given through this work demonstrate the effectiveness of key routines in IVGPR. Additionally, three case studies show end-to-end applications of this program to field records that produced satisfactory result well-suited interpretatio

Seismic imaging: a practical approach

In the geophysics of oil exploration and reservoir studies, the surface seismic method is the most commonly used method to obtain a subsurface model in 2 or 3 dimensions. This method plays an increasingly important role in soil investigations for geotechnical, hydrogeological and site characterization studies regarding seismic hazard issues. The goal of this book is to provide a practical guide, using examples from the field, to the application of seismic methods to surface imaging. After reviewing the current state of knowledge in seismic wave propagation, refraction and reflection seismic methods, the book aims to describe how seismic tomography and fullwave form inversion methods can be used to obtain seismic images of the subsurface. Through various synthetic and field examples, the book highlights the benefit of combining different sets of data: refracted waves with reflected waves, and body waves with surface waves. With field data targeting shallow structures, it shows how more accurate geophysical models can be obtained by using the proposed hybrid methods. Finally, it shows how the integration of seismic data (3D survey and VSP), logging data (acoustic logging) and core measurements, combined with a succession of specific and advanced processing techniques, enables the development of a 3D high resolution geological model in depth. In addition to these examples, the authors provide readers with guidelines to carry out these operations, in terms of acquisition, as well as processing and interpretation. In each chapter, the reader will find theoretical concepts, practical rules and, above all, actual application examples. For this reason, the book can be used as a text to accompany course lectures or continuing education seminars. This book aims to promote the exchange of information among geologists, geophysicists, and engineers in geotechnical fields

Nonhyperbolic normal moveout stretch correction with deep learning automation

Normal-moveout (NMO) correction is a fundamental step in seismic data processing. It consists of mapping seismic data from recorded traveltimes to corresponding zero-offset times. This process produces wavelet stretching as an undesired by-product. We have addressed the NMO stretching problem with two methods: (1) an exact stretch-free NMO correction that prevents the stretching of primary reflections and (2) an approximate post-NMO stretch correction. Our stretch-free NMO produces parallel moveout trajectories for primary reflections. Our post-NMO stretch correction calculates the moveout of stretched wavelets as a function of offset. Both methods are based on the generalized moveout approximation and are suitable for application in complex anisotropic or heterogeneous environments. We use new moveout equations, modify the original parameter functions to be a constant over the primary reflections, and then interpolate the seismogram amplitudes at the calculated traveltimes. For fast and automatic modification of the parameter functions, we use deep learning. We design a deep neural network (DNN) using convolutional layers and residual blocks. To train the DNN, we generate a set of 40,000 synthetic NMO-corrected common-midpoint gathers and the corresponding desired outputs of the DNN. The data set is generated using different velocity profiles, wavelets, and offset vectors, and it includes multiples, ground roll, and band-limited random noise. The simplicity of the DNN task - a 1D identification of primary reflections - improves the generalization in practice. We use the trained DNN and find successful applications of our stretch-correction method on synthetic and different real data sets

Full waveform inversion procedures with irregular topography

Full waveform inversion (FWI) is a form of seismic inversion that uses data residual, found as the misfit, between the whole waveform of field acquired and synthesized seismic data, to iteratively update a model estimate until such misfit is sufficiently reduced, indicating synthetic data is generated from a relatively accurate model. The aim of the thesis is to review FWI and provide a simplified explanation of the techniques involved to those who are not familiar with FWI. In FWI the local minima problem causes the misfit to decrease to its nearest minimum and not the global minimum, meaning the model cannot be accurately updated. Numerous objective functions were proposed to tackle different sources of local minima. The ‘joint deconvoluted envelope and phase residual’ misfit function proposed in this thesis aims to combine features of these objective functions for a comprehensive inversion. The adjoint state method is used to generate an updated gradient for the search direction and is followed by a step-length estimation to produce a scalar value that could be applied to the search direction to reduce the misfit more efficiently. Synthetic data are derived from forward modelling involving simulating and recording propagating waves influenced by the mediums’ properties. The ‘generalised viscoelastic wave equation in porous media’ was proposed by the author in sub-chapter 3.2.5 to consider these properties. Boundary layers and conditions are employed to mitigate artificial reflections arising from computational simulations. Linear algebra solvers are an efficient tool that produces wavefield vectors for frequency domain synthetic data. Regions with topography require a grid generation scheme to adjust a mesh of nodes to fit into its non-quadrilateral shaped body. Computational co-ordinate terms are implemented within wave equations throughout topographic models where a single point in the model in physical domain are represented by cartesian nodes in the computational domains. This helps to generate an accurate and appropriate synthetic data, without complex modelling computations. Advanced FWI takes a different approach to conventional FWI, where they relax upon the use of misfit function, however none of their proponents claims the former can supplant the latter but suggest that they can be implemented together to recover the true model.Open Acces

Seismic characterisation based on time-frequency spectral analysis

We present high-resolution time-frequency spectral analysis schemes to better resolve seismic images for the purpose of seismic and petroleum reservoir characterisation. Seismic characterisation is based on the physical properties of the Earth's subsurface media, and these properties are represented implicitly by seismic attributes. Because seismic traces originally presented in the time domain are non-stationary signals, for which the properties vary with time, we characterise those signals by obtaining seismic attributes which are also varying with time. Among the widely used attributes are spectral attributes calculated through time-frequency decomposition. Time-frequency spectral decomposition methods are employed to capture variations of a signal within the time-frequency domain. These decomposition methods generate a frequency vector at each time sample, referred to as the spectral component. The computed spectral component enables us to explore the additional frequency dimension which exists jointly with the original time dimension enabling localisation and characterisation of patterns within the seismic section. Conventional time-frequency decomposition methods include the continuous wavelet transform and the Wigner-Ville distribution. These methods suffer from challenges that hinder accurate interpretation when used for seismic interpretation. Continuous wavelet transform aims to decompose signals on a basis of elementary signals which have to be localised in time and frequency, but this method suffers from resolution and localisation limitations in the time-frequency spectrum. In addition to smearing, it often emerges from ill-localisation. The Wigner-Ville distribution distributes the energy of the signal over the two variables time and frequency and results in highly localised signal components. Yet, the method suffers from spurious cross-term interference due to its quadratic nature. This interference is misleading when the spectrum is used for interpretation purposes. For the specific application on seismic data the interference obscures geological features and distorts geophysical details. This thesis focuses on developing high fidelity and high-resolution time-frequency spectral decomposition methods as an extension to the existing conventional methods. These methods are then adopted as means to resolve seismic images for petroleum reservoirs. These methods are validated in terms of physics, robustness, and accurate energy localisation, using an extensive set of synthetic and real data sets including both carbonate and clastic reservoir settings. The novel contributions achieved in this thesis include developing time-frequency analysis algorithms for seismic data, allowing improved interpretation and accurate characterisation of petroleum reservoirs. The first algorithm established in this thesis is the Wigner-Ville distribution (WVD) with an additional masking filter. The standard WVD spectrum has high resolution but suffers the cross-term interference caused by multiple components in the signal. To suppress the cross-term interference, I designed a masking filter based on the spectrum of the smoothed-pseudo WVD (SP-WVD). The original SP-WVD incorporates smoothing filters in both time and frequency directions to suppress the cross-term interference, which reduces the resolution of the time-frequency spectrum. In order to overcome this side-effect, I used the SP-WVD spectrum as a reference to design a masking filter, and apply it to the standard WVD spectrum. Therefore, the mask-filtered WVD (MF-WVD) can preserve the high-resolution feature of the standard WVD while suppressing the cross-term interference as effectively as the SP-WVD. The second developed algorithm in this thesis is the synchrosqueezing wavelet transform (SWT) equipped with a directional filter. A transformation algorithm such as the continuous wavelet transform (CWT) might cause smearing in the time-frequency spectrum, i.e. the lack of localisation. The SWT attempts to improve the localisation of the time-frequency spectrum generated by the CWT. The real part of the complex SWT spectrum, after directional filtering, is capable to resolve the stratigraphic boundaries of thin layers within target reservoirs. In terms of seismic characterisation, I tested the high-resolution spectral results on a complex clastic reservoir interbedded with coal seams from the Ordos basin, northern China. I used the spectral results generated using the MF-WVD method to facilitate the interpretation of the sand distribution within the dataset. In another implementation I used the SWT spectral data results and the original seismic data together as the input to a deep convolutional neural network (dCNN), to track the horizons within a 3D volume. Using these application-based procedures, I have effectively extracted the spatial variation and the thickness of thinly layered sandstone in a coal-bearing reservoir. I also test the algorithm on a carbonate reservoir from the Tarim basin, western China. I used the spectrum generated by the synchrosqueezing wavelet transform equipped with directional filtering to characterise faults, karsts, and direct hydrocarbon indicators within the reservoir. Finally, I investigated pore-pressure prediction in carbonate layers. Pore-pressure variation generates subtle changes in the P-wave velocity of carbonate rocks. This suggests that existing empirical relations capable of predicting pore-pressure in clastic rocks are unsuitable for the prediction in carbonate rocks. I implemented the prediction based on the P-wave velocity and the wavelet transform multi-resolution analysis (WT-MRA). The WT-MRA method can unfold information within the frequency domain via decomposing the P-wave velocity. This enables us to extract and amplify hidden information embedded in the signal. Using Biot's theory, WT-MRA decomposition results can be divided into contributions from the pore-fluid and the rock framework. Therefore, I proposed a pore-pressure prediction model which is based on the pore-fluid contribution, calculated through WT-MRA, to the P-wave velocity.Open Acces

Métodos de reconstrucción en dominio temporal para tomografía por transmisión de ultrasonidos

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Ciencias Físicas, Departamento de Física Atómica, Molecular y Nuclear, leída el 06-06-2017Breast cancer (BC) is the leading cause of cancer-related death for women in Europe, and the second one after lung cancer in the US [World Cancer Report, 2008]. Early detection is very important for the survival rate of BC, because the smaller the local extension of the neoplasia, the better the output of the surgical treatments employed. Besides, early detection increases the possibility of preserving the breast and decreases the probability of needing more invasive treatments [Secretaría de Salud, 2007, Alteri et al., 2011]. Mammography is currently the standard procedure employed for breast screening programs around the world. Nevertheless, its efficiency has been questioned lately because: (i) it generates many abnormal findings not related to cancer, (ii) it requires irradiating the patient and (iii) it has low specificity with dense breasts [Santen and Mansel, 2005]. Consequently, complementary techniques to mammography are being proposed to improve the detection and characterization of BC. Among these techniques, is the Ultrasound Computed Tomography (USCT), in reflection mode (which provides qualitative maps with the concentration of scatterers in the tissue), and transmission mode (which provides quantitative maps of the sound speed (SS) and the acoustic attenuation (AA) of the tissues). The images provided by the transmission modality have been proposed for BC detection as they can improve the detectability of malignancies in the breast [Mast, 2000, Duric et al., 2009]...El cáncer de mama (CM) es el cáncer más mortal entre las mujeres europeas, y el segundo más común en Estados Unidos [World Cancer Report, 2008]. La detección temprana es un factor que condiciona en gran medida la tasa de supervivencia a esta enfermedad, ya que a menor tamaño de la neoplasia detectada, mejores resultados pueden esperarse para los tratamientos quirúrgicos que se realicen. Además, la detección temprana aumenta la posibilidad de conservar la mama después de la cirugía y disminuye la necesidad de emplear otros tratamientos más invasivos[Secretaría de Salud, 2007, Alteri et al., 2011]. La mamografía es actualmente el procedimiento estándar que se emplea para el cribado del CM. Sin embargo, en los últimas años su eficiencia está siendo muy cuestionada por varios factores: (i) alta tasa de falsos positivos, (ii) requiere la irradiación del paciente y (iii) baja especificidad en mamas densas 2. Debido a lo anterior, para mejorar la detección y caracterización del CM se han propuesto varias técnicas complementarias. Entre ellas está la tomografía ultrasónica (TU), que es una técnica en desarrollo que presenta dos modalidades principales: la reflexión (proporciona mapas cualitativos de la concentración de dispersores en el tejido) y la transmisión (proporciona mapas cuantitativos de la velocidad y atenuación del sonido en el tejido). Los mapas del modo transmisión han sido propuestos como una eficiente alternativa, libre de radiación, para la detección del CM, ya que proporcionan alto contraste y especificidad [Mast, 2000, Duric et al., 2009]...Depto. de Estructura de la Materia, Física Térmica y ElectrónicaFac. de Ciencias FísicasTRUEunpu