Teses em Geofísica (Doutorado) - CPGF/IG
URI Permanente para esta coleçãohttps://repositorio.ufpa.br/handle/2011/2357
O Doutorado Acadêmico pertente a o Programa de Pós-Graduação em Geofísica (CPGF) do Instituto de Geociências (IG) da Universidade Federal do Pará (UFPA).
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Item Acesso aberto (Open Access) Inversão de velocidades por otimização global usando a aproximação superfície de reflexão comum com afastamento finito(Universidade Federal do Pará, 2016-08-25) MESQUITA, Marcelo Jorge Luz; CRUZ, João Carlos Ribeiro; http://lattes.cnpq.br/8498743497664023The recent geophysical literature has shown the building of an accurate initial model is the more appropriate way to reduce the ill-posedness of the Full Waveform Inversion, providing the necessary convergence of the misfit function toward the global minimum. Optimized models are useful as initial guess for more sophisticated velocity inversion and migration methods. I developed an automatic P-wave velocity inversion methodology using pre-stack two-dimensional seismic data. The proposed inversion strategy is fully automatic, based on the semblance measurements and guided by the paraxial traveltime approximation, so-called Finite-Offset Common-Reflection-Surface. It is performed in two steps, at first using image rays and an a priori known initial velocity model we determine the reflector interfaces in depth from time migrated section. The generated depth macro-model is used as input at the second step, where the parametrization of the velocity model is made layer by layer. Each layer is separated from each other by smoothed interfaces. The inversion strategy is based on the scan of semblance measurements in each common-midpoint gather guided by the Finite-Offset Common-Reflection-Surface traveltime paraxial approximations. For beginning the inversion in the second step, the finite-offset common-midpoint central rays is built by ray tracing from the velocity macro-model obtained in the first step. By using the arithmetic mean of total semblance calculated from the whole common-midpoint gathers as objective function, layer after layer, a global optimization method called Very Fast Simulated Annealing algorithm is applied in order to obtain the convergence of the objective function toward the global maximum. By applying to synthetic and real data, I showed the robustness of the inversion algorithm for yielding an optimized P-wave velocity macro-model from pre-stack seismic data.Item Acesso aberto (Open Access) Seismic amplitude analysis and quality factor estimation based on redatuming(Universidade Federal do Pará, 2015-04-25) OLIVEIRA, Francisco de Souza; FIGUEIREDO, José Jadsom Sampaio de; http://lattes.cnpq.br/1610827269025210Amplitude correction is an important task to correct the seismic energy dissipated due the ineslasticity absortion and the geometrical spreading during the acoustic/elastic wave propagation in solids. In this work, we propose a way to improve the estimation of quality factor from seismic reflection data, with a methodology to estimate de quality factor based on the combination of the peak frequency-shift (PFS) method and the redatuming operator. The innovation in this work is in the way we correct travel times when the medium is consisted by many layers. In other words, the correction of traveltime table used in the PFS method is performed using the redatuming operator. This operation, which is performed iteratively, allows to estimate the Q-factor layer by layer in a more accurate way. A redatuming operation is used to simulate the acquisition of data in new levels, avoiding distortions produced by near-surface irregularities related to either geometric or material property heterogeneities. In this work, the application of the true-amplitude Kirchhoff redatuming (TAKR) operator on homogeneous media is compared with conventional Kirchhoff redatuming (KR) operator restricted to the zero-offset case. Our methodology is based on the combination of the peak frequency-shift (PFS) method and the redatuming operator (TAKR with weight equal 1). Application in synthetic and in seismic (Viking Graben) and GPR (Siple Dome) real data demonstrates the feasibility of our analysis.Item Acesso aberto (Open Access) Solução da equação de Archie com algoritmos inteligentes(Universidade Federal do Pará, 2011) SILVA, Carolina Barros da; ANDRADE, André José Neves; http://lattes.cnpq.br/8388930487104926Archie equation is a historical mark of Formation Evaluation establishing a relationship among the physical properties and the petrophysical properties of reservoir rocks, which makes possible the identification and quantification of hydrocarbon in subsurface. Water saturation is the solution of Archie equation obtained from the measure of formation deep resistivity and porosity estimated. However, the solution of Archie equation is no trivial, in the dependence of previous knowledge of formation water resistivity and Archie exponents (cementation and saturation). This thesis introduces a set new intelligent algorithm to solve Archie equation. A modification of competitive neural network, nominated as bicompetitive neural network produces the log zonation. A new genetic algorithm with evolutionary strategy based in the mushrooms reproduction produces estimates for the matrix density, the matrix transit time and the matrix neutron porosity, which associated to a new rock model, produces realistic porosity estimates considering shale effects. A new model of competitive neural network, nominated as angular competitive neural network is able to accomplish the interpretation of Pickett plot, supplying the information about formation water resistivity and cementation exponent. All results of the methodology hereintroduced are presented using synthetic data and actual wireline logs and core analysis results.