Supressão do ruído de rolamento superficial utilizando a transformada Curvelet

Among the many types of noise observed in seismic land acquisition there is one produced by surface waves called Ground Roll that is a particular type of Rayleigh wave which characteristics are high amplitude, low frequency and low velocity (generating a cone with high dip). Ground roll contaminates the relevant signals and can mask the relevant information, carried by waves scattered in deeper regions of the geological layers. In this thesis, we will present a method that attenuates the ground roll. The technique consists in to decompose the seismogram in a basis of curvelet functions that are localized in time, in frequency, and also, incorporate an angular orientation. These characteristics allow to construct a curvelet filter that takes in consideration the localization of denoise in scales, times and angles in the seismogram. The method was tested with real data and the results were very good

Análise sísmica usando transformada de Curvelet

Oil prospecting is one of most complex and important features of oil industry Direct prospecting methods like drilling well logs are very expensive, in consequence indirect methods are preferred. Among the indirect prospecting techniques the seismic imaging is a relevant method. Seismic method is based on artificial seismic waves that are generated, go through the geologic medium suffering diffraction and reflexion and return to the surface where they are recorded and analyzed to construct seismograms. However, the seismogram contains not only actual geologic information, but also noise, and one of the main components of the noise is the ground roll. Noise attenuation is essential for a good geologic interpretation of the seismogram. It is common to study seismograms by using time-frequency transformations that map the seismic signal into a frequency space where it is easier to remove or attenuate noise. After that, data is reconstructed in the original space in such a way that geologic structures are shown in more detail. In addition, the curvelet transform is a new and effective spectral transformation that have been used in the analysis of complex data. In this work, we employ the curvelet transform to represent geologic data using basis functions that are directional in space. This particular basis can represent more effectively two dimensional objects with contours and lines. The curvelet analysis maps real space into frequencies scales and angular sectors in such way that we can distinguish in detail the sub-spaces where is the noise and remove the coefficients corresponding to the undesired data. In this work we develop and apply the denoising analysis to remove the ground roll of seismograms. We apply this technique to a artificial seismogram and to a real one. In both cases we obtain a good noise attenuation

Supressão do ruído de rolamento superficial utilizando a transformada Curvelet

Among the many types of noise observed in seismic land acquisition there is one produced by surface waves called Ground Roll that is a particular type of Rayleigh wave which characteristics are high amplitude, low frequency and low velocity (generating a cone with high dip). Ground roll contaminates the relevant signals and can mask the relevant information, carried by waves scattered in deeper regions of the geological layers. In this thesis, we will present a method that attenuates the ground roll. The technique consists in to decompose the seismogram in a basis of curvelet functions that are localized in time, in frequency, and also, incorporate an angular orientation. These characteristics allow to construct a curvelet filter that takes in consideration the localization of denoise in scales, times and angles in the seismogram. The method was tested with real data and the results were very good

Representações espectrais de sistemas complexos: aplicações à síntese de superfícies brownianas fracionárias anisotrópicas, filtragem de sinais e identificação de correlações

In this thesis, we study the application of spectral representations to the solution of problems in seismic exploration, the synthesis of fractal surfaces and the identification of correlations between one-dimensional signals. We apply a new approach, called Wavelet Coherency, to the study of stratigraphic correlation in well log signals, as an attempt to identify layers from the same geological formation, showing that the representation in wavelet space, with introduction of scale domain, can facilitate the process of comparing patterns in geophysical signals. We have introduced a new model for the generation of anisotropic fractional brownian surfaces based on curvelet transform, a new multiscale tool which can be seen as a generalization of the wavelet transform to include the direction component in multidimensional spaces. We have tested our model with a modified version of the Directional Average Method (DAM) to evaluate the anisotropy of fractional brownian surfaces. We also used the directional behavior of the curvelets to attack an important problem in seismic exploration: the atenuation of the ground roll, present in seismograms as a result of surface Rayleigh waves. The techniques employed are effective, leading to sparse representation of the signals, and, consequently, to good resolutions