Produção Científica



Artigo em Revista
07/11/2018

Effects of torque produced by wake on the maneuverability of a flatfish autonomous underwater vehicle
Autonomous underwater vehicles (AUV) are important resources to be used in the oil exploration industry in deep waters as well as a platform for scanning devices used in open sea regions of difficult human access. This work aims to analyze through computer simulations the influence of marine currents on the maneuverability of a flatfish shaped AUV. The 3D realistic scale simulations were performed on the Yemoja supercomputer located at SENAI-CIMATEC and describe the temporal evolution of the torques in the three rotational degrees of freedom - roll,yaw and pitch. The torques were calculated for two different inlet velocities and three angles (yaw) of attack showing a significant
gain in the amplitude of these with increasing velocity and pitch being the component with the greatest amplitude of oscillation.
Artigo em Revista
07/11/2018

Cross-correlation in a turbulent flow: Analysis of the velocity field using the pDCCA coefficient
The stochastic process of a turbulent flow in a pipeline provides a time series of the velocity field at any point of the domain by solving numerically the Navier-Stokes equation. The turbulent flow was produced by obstacles near the inlet, injecting eddies into the current. Moving downstream, these eddies evolve to a fully turbulent flow. Many length and time scales are involved in this process. We explore the cross-correlations of the velocity field time series at different points and also at different time scales using the detrended cross-correlation coefficient, pDCCA, designed to analyze the cross-correlations in non-stationary time series. Thus, the results with DCCA allow interpreting how these eddies propagate downstream, and also quantify how
adherent the velocity fields are with respect to the pipeline position.
Artigo em Revista
07/11/2018

Detection of the persistency of the blockages symmetry influence on the multi-scale cross-correlations of the velocity fields in internal turbulent flows in pipelines
In this paper we analyze the influence of obstacles symmetry on the development of the turbulent flow of a fluid through a pipeline. The analysis is based on the numerical solutions of the Navier–Stokes equations for the velocity field. The influence of the obstacle symmetry on the turbulence is detected by changing their shape while keeping the blockage ratio constant and calculating velocity field cross-correlations on the time series resulting from the simulation. The Detrended Cross-Correlation coefficient (ρDCCA) is applied to obtain two-point correlations located at different regions of the channel: at mid-channel and near the walls (above and below). With this cross-correlation coefficient we quantify how far from the obstructions these coefficients become independent on the obstructions shape, establishing a scale for the obstruction symmetry memory loss.
Artigo em Revista
17/10/2018

A numerical viscoelastic model of ground response assimilating pore-water pressure measurements
We consider a simple one-dimensional, viscoelastic model for shear-wave propagation on liquefiable soils. The soil is modelled as a layered medium parametrized by shear modulus and viscosity, which in turn depend on the excess pore-water pressure ratio. We numer ically solve the resulting wave propagation model with the spectral element method, and employ simulated annealing and weighted Gauss-Newton inversion algorithms to minimize the misfit of surface displacement, velocity, and acceleration. This procedure is validated us ing recorded ground motion and pore-water pressure data from the Imperial Valley Wildlife and the Garner Valley downhole arrays. Parameter inversion is also carried out with linear models with constant shear modulus
and viscosity, and the proposed model provides better fitness in the presence of strong motion, especially in the 1987 Superstition Hills earthquake.

Key words: viscoelastic wave equation, liquefaction, spectral element method, site response.
Artigo em Revista
11/10/2018

Complex Autoregressive Time–Frequency Analysis - Estimation of time-varying periodic signal components
Time–frequency representations of nonstationary signals have a wide range of geophysical applications, including seismics, seismology, volcanology, and astrophysics. In this article, we estimate a complex autoregressive (AR) model from a short time window of the analytic signal. The local power spectrum is the inverse of the spectrum of this AR model. Since the coefficients are complex, the time window can be shorter than for the real AR model, which requires more coefficients. This results in higher time–frequency resolution, as seen in a synthetic data examples with different signal components. The new technique also gives good results when computing the instantaneous average frequency (IAF) of marine seismic data. Applied to digitized and downloaded data from the Laser Interferometer Gravitational-Wave Observatory (LIGO) in Hanford, Washington, the result clearly shows the linear chirp associated with the merger of two black holes.
Artigo em Revista
11/10/2018

APPLICATION OF TIME-FREQUENCY DECOMPOSITION METHOD IN THE STUDY OF GAS RESERVOIR IN THE SERGIPE-ALAGOAS BASIN
The sedimentary basin of Sergipe-Alagoas, located on the Brazilian east bank, presents one of the most complete stratigraphic sections of the Brazilian
continental margin. Hydrocarbon exploration activities began more than 50 years ago. The recent discoveries of hydrocarbons (gas and oil of high API grade) in turbiditic reservoirs of deep waters have further awakened the exploratory interest of the basin. Problems related to the processing and interpretation of seismic data have always received great attention from the scientific community. Currently, the use of time-frequency decomposition methods of the seismic signal is of great interest. Spectral decomposition has been widely used in reservoir characterization, such as determination of layer thickness, stratigraphic visualization with seismic attributes
and identification of low frequency anomalies associated with the presence of gas. The mechanism causing these anomalies is not yet well known, but they are often attributed to the high attenuation of gas filled reservoirs. The approach used for spectral decomposition combines the maximum entropy method and the Wigner-Ville distribution, based on the idea of the Burg method that uses the prediction error operator to extend the Wigner-Ville kernel sequences by applying the Fourier transform to each extended sequence, thus allowing to obtain the Wigner-Ville distribution of maximum entropy.

Keywords: Sergipe-Alagoas Basin,Wigner-Ville distribution, maximum entropy, spectral decomposition, seismic attributes, low frequency anomaly.
Artigo em Revista
04/10/2018

Processing of large offset data: experimental seismic line from Tenerife Field, Colombia
Exploration seismology provides the main source of information about the Earth’s subsurface, which in many cases can be presented as a simple model of horizontal or near-horizontal layers. After the seismic acquisition step, conventional seismic processing of reflection data provides an image of the subsurface by using information about the reflections of these layers. The traveltime from a source to different receivers is adjusted using a hyperbolic function. This expression is used in the case involving an isotropic medium, which is a simplification of nature, whereas geologically complex media are generally anisotropic. A subsurface model that more closely resembles reality is the vertical transverse isotropy, which defines two parameters that are required to correct the traveltimes: the NMO velocity and the anellipticity parameter. In this paper, we reviewed the literature and methodology for velocity analysis of seismic data acquired from anisotropic media. A model with horizontal layers and anisotropic behavior was developed and evaluated. The anisotropic velocity was compared to the isotropic velocity, and the results were analyzed. Finally, the methodology was applied to real seismic data, i.e. an experimental landline from Tenerife Field, Colombia. The results show the importance of the anellipticity parameter in models with anisotropic layers.
Artigo em Revista
01/10/2018

Filtering and frequency interpretations of Singular Spectrum Analysis
New filtering and spectral interpretations of Singular Spectrum Analysis(SSA)are provided. It is shown that the variables reconstructed fromd iagonal averaging of reduced-rank approximations to the trajec-tory matrix can be obtained from a noncausal convolution filte rwith zero-phase characteristics. There-constructed variables are readily constructed using a two-pass filtering algorithm that is well known in the signal processing literature. When the number of rows in the trajectory matrix is much larger than number of columns, many results reported in the signal processing literature can be used to derive the properties of the resulting filters and their spectra. New features of there constructed series are revealed using these results. Two examples are used to illustrate the results derived in this paper.
Artigo em Revista
18/07/2018

Otimização global para resolver problemas inversos em eletrorresistividade com flexibilidade na escolha dos vínculos
Inversion in DC-resistivity is an ill-posed inverse problem because different realizations of the same model might satisfy approximately the same data fitting criterium. It is therefore necessary to use constraints to obtain unique and / or stable solutions to small perturbations in the measurements. However, in general, the introduction of constraints has been restricted to cases of differentiable constraints, which can be treated with local optimization algorithms. 1D and 2D modeling in DC-resistivity is computationally inexpensive, allowing the use of global optimization methods (GOMs) to solve 1.5D and 2D inverse problems with flexibility in constraint incorporation. Changes in the cost function, either in the constraints or data fitting criteria, can be easily performed, since each term of the cost function is properly normalized to allow the approximate invariance of the
Lagrange multipliers. GOMs have the potential to support a computational environment suitable for quantitative interpretation in which the comparison of solutions incorporating different constraints is one way of inferring characteristics of the actual distribution of the underground resistivity. In this work, we developed: (i) comparison of the performances of the Simulated Annealing (SA), Genetic Algorithm (GA) and Particle Swarm optimization (PSO) methods to solve the 1.5D inverse problem in DC resistivity using synthetic and field data; (ii) an inversion approach based on particle swarm optimization (PSO) to solve the 2D DC-resistivity inverse problem; (iii) exploration of several constraints in the variation of log-resistivity, including spatial continuity in both L1 andL2 norms, total variation and sparsity constraints using discrete cosine and Daubechies bases. In addition, we explore the minimum inertia constraint, including the case of using the Earth’s surface as the target axis, to impose the concentration of resistive or conductive materials along target axes. The main results of the comparison for the 1.5D case are: a) all methods reproduce quite well the resistivity distribution of synthetic models, b) PSO and GA are very robust to changes in the cost function and SA is comparatively much more sensitive, c) PSO first and GA second present the best computational performances, requiring smaller number of forwarding modeling than SA, and d) GA shows the best performance with respect to the final attained value of the cost function and its standard deviation, whilst
SA has the worst performance in this aspect. Equally important for both 1.5 and 2D cases, from the stopping criteria of the PSO algorithm results not only the best solution but also a cluster of suboptimal quasi-solutions from which uncertainty analyses can be performed. As a result, the interpreter has freedom to perform a quantitative interpretation process based on a feedback trial-and-error inversion approach, in a similar manner he/she has when using a friendly forward
Artigo em Revista
18/07/2018

Evaluation of model performances in reproducing measures of thermal conductivity of crystalline rocks
We evaluate the performances of the Krischer-Esdorn (KE), Hashin-Shtrikman (HS), classic Maxwell (CM), Maxwell-Wiener (MW), and geometric mean (GM) models in reproducing 1,105 measurements of thermal conductivity of crystalline rocks collected in Borborema Province (NE-Brazil). Percent volumes of quartz, K-feldspar, plagioclase, andmafic minerals were also measured. Rock samples were divided into the IOG (igneous and ortho-derived) and MET (metasedimentary) groups. IOG-group (939 samples) covered most the lithologies of the Streckeisen diagram and MET-group (166 samples) covered low-to-medium metamorphic grade lithologies. Reproducing rock conductivities was treated as an inverse problem, where conductivity measurements and constituent mineral volumes are the known quantities while the constituent mineral effective conductivities and model parameters are the unknowns. To identify the model better reproducing the measurements, model performances were compared by using the percentage of number of samples whose estimated conductivities are close to the measured conductivities within the tolerance level of 15%. For all models, the performances are relatively inferior for the MET-group. In the IOG-group, the KE- and HS-model performances are relatively superior. In the MET-group, model performances are very contrasting but the KE-model is again superior. The KE-model thus presents the best performance in reproducing thermal conductivities of crystalline rocks.
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