Produção Científica
Artigo em Revista
| EVOLUTIONARY PROBLEMS OF NONLINEAR MAGNETOELASTICITY We consider mixed problems for nonlinear equations of magnetoelasticity. Our main result in the three-dimensional case is the proof of an existence and uniqueness theorem; uniqueness is established under some extra restrictions on the smoothness of solutions. We also manage to prove the existence and uniqueness of a weak solution to the problem in the two-dimensional case; uniqueness is established without any additional a priori assumptions on the smoothness of solutions. |
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Artigo em Revista
| Petrofacies classification using machine learning algorithms Carbonate reservoirs represent a large portion of the world’s oil and gas reserves, exhibiting specific characteristics that pose complex challenges to the reservoirs’ characterization, production, and management. Therefore, the evaluation of the relationships between the key parameters, such as porosity,permeability, water saturation, and pore size distribution, is a complex task considering only well-log data, due to the geologic heterogeneity. Hence, the petrophysical parameters are the key to assess the original composition and postsedimentological aspects of the carbonate reservoirs. The concept of reservoir petrofacies was proposed as a tool for the characterization and prediction of the reservoir quality as it combines primary textural analysis with laboratory measurements of porosity, permeability, capillary pressure, photomicrograph descriptions, and other techniques, which contributes to understanding the postdiagenetic events. We have adopted a workflow to petrofacies classification of a carbonate reservoir from the Campos Basin in southeastern Brazil, using the following machine learning methods: decision tree, random forest, gradient boosting, K-nearest neighbors, and naïve Bayes. The data set comprised1477 wireline data from two wells (A3 and A10) that had petrofacies classes already assigned based on core descriptions. It was divided into two subsets, one for training and one for testing the capability of the trained models to assign petrofacies. The supervised-learning models have used labeled training data to learn the relationships between the input measurements and the petrofacies to be assigned. Additionally, we have developed a comparison of the models’ performance using the testing set according to accuracy, precision, recall, and F1-score evaluation metrics. Our approach has proved to be a valuable ally in petrofacies classification, especially for analyzing a well-logging database with no prior petrophysical information. |
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Artigo em Revista
| Mathematical Model of Water Alternated Polymer Injection Chemical enhanced oil recovery (EOR) methods include the injection of aqueous polymer solutions slugs driven by water. Polymer solutions increase water viscosity, decreasing the water phase mobility and improving oil recovery through better sweep efciency. In this paper, we present the water alternated polymer EOR technique, which is based on the injection of successive polymer slugs alternated by water slugs. The mathematical problem is composed by two conservation equations: one of them is related to the water volume and the other one to the polymer mass. We assume that the polymer may be adsorbed by the rock, and the relation between the concentration in the aqueous solution and the solid is governed by a Langmuir type adsorption isotherm. The water viscosity is a function of the polymer concentration in water. The 2×2 system of hyperbolic equations was decoupled by introducing a potential function instead of time as an independent variable. The water alternated polymer injection is represented by a varying boundary condition. The analytical solution presents interactions between waves of diferent families. It is shown that the polymer slugs always catch up each other along the porous media generating a single slug. As a consequence, the water slugs will disappear. This solution is new and was compared to numerical results with close agreement. It also can be used for the selection of the most suitable enhanced oil recovery technique for a particular oil field. |
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Artigo em Revista
| The effectiveness of spectral decomposition-based layer thickness estimation: A seismic physical modeling example We have constructed a channel complex model at a scale of 1:10,000 by stacking 3D-printed polylactide layers with negative relief meandering channels. This model was subjected to an ultrasonic common-offset acquisition in a water tank (with the water filling the channels), and the result was treated as a zero-offset 3D acoustic reflection seismogram, receiving a deterministic deconvolution and a poststack migration as data treatment. We then developed an algorithm to yield volumes of estimated two-way time layer thickness from multiple-frequency volumes obtained through the short-time Fourier transform. The estimated thicknesses were compared with the measurements of the physical model obtained through X-ray computed tomography. Despite the strong signal attenuation and imaging issues, the results were rather satisfactory, increasing the confidence in using spectral decomposition for quantitative seismic analysis. |
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Artigo em Revista
| Core plug and 2D/3D-image integrated analysis for improving permeability estimation based on the differences between micro- and macroporosity in Middle East carbonate rocks Carbonate rocks are porous systems, with pores and pore throats of varying morphologies that result from depositional and diagenetic processes. Such heterogeneity produces a complex arrangement between the grains and pores that affects the petrophysical properties while limiting the utility of measurement techniques. Petrophysical properties are generally acquired by conventional laboratory methods, although to provide accurate results, core plugs need to be recovered intact. Two-dimensional digital image analysis (2D DIA) enables the processing of any core cut and requires minimal data manipulation and computation when compared to threedimensional approaches. In DIA, permeability is calculated using models described in the literature that often do not provide good predictions for carbonate rocks. Often, the permeability, which is controlled by the size and shape of the pores and pore throats, is related to porosity values; however, the porosity of a rock varies from the micro to macro level, resulting in enormous uncertainty in estimating permeability. In this article, we present a new strategy to improve the prediction of permeability by using pore-shape parameters from 2D DIA, which provides data related to the macropores resulting from the optical resolution. This gas technique measures the absolute permeability, which is used as a calibration parameter, and the total porosity, which is used to calculate the microporosity. The test samples used are from Oman outcrops of the Huqf Supergroup and Salalah Formation, which are analogous to the carbonates of the giant reservoirs in the Middle East. Microporosity was characteristic of all the samples due to the calcite mud matrix, recrystallized calcite cement, microcracks and the crystalline texture caused by dolomitization. The pore-shape parameters from the 2D DIA improved the permeability prediction and were found to relate to the pore types that make up the rock, whereas the 3D technique did not provide a good result. The R2 of the 2D data was 0.96, demonstrating the efficiency of the procedures applied in mitigating the uncertainties of the models for the set of samples studied. |
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Artigo em Revista
| Dynamics of the nonequilibrium flow in a duct with obstruction This work aims to numerically simulate the dynamics of a channel flow with an obstruction since the moment we inject a fluid with an homogeneous velocity profile. The simulations uses the open source tools of the OpenFOAM platform, the pisoFoam and the LES turbulence model, describing in detail the velocity profiles of laminar and turbulent flows. We also perform a boundary layer mapping in the presence of an obstacle. We used three different domains to follow the evolution of the velocity profile while the fluid progresses downstream and passes the obstruction. The results reproduce the well-known results of laminar flow in a channel, as well as the average velocity profile in the turbulent regime and the occurrence of attachments by the obstruction. These preliminary results are used to validate the solvers and the mesh used. Next,an analysis of the velocity profile dynamics resulted in determining an exponential decay of the root mean square deviations of the homogeneous to the parabolic, and to the turbulent regime in the channel. |
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Artigo em Revista
| A wavefield domain dynamic approach: Application in reverse time migration This paper proposes a novel technique to handle the wavefield domain involved in the procedures of seismic modeling, reverse-time migration (RTM), and full-waveform inversion (FWI). This method considers that the size of the wavefield domain varies with time, in other words, that it expands concomitantly to the propagation. However, in the geophysical literature, this dynamism has always been neglected as the wavefield domain is constantly considered to be fixed, thus, representing what we call a static approach (SA). This assumption may incurunnecessary use of available computational resources, thereby compromising application performance. Herein, we create a so-called dynamic approach (DA), capable of obtaining truly significant gains in terms of memory consumption and computational time. This new methodology is based on the application of an empirical filter that delimits the wavefront. This filter functions as a window and it is applied at each timestep until the wavefront reaches the model's boundaries, selecting the area where the seismic wavefield exists. This approach tries to approximate the computational domain to the propagation domain in order to obtain valuable computational gains, by eliminating unnecessary work, thus reducing the amount of work needed to perform forward and backward propagation. We compare both approaches using the Pluto model. The seismic data generated from the Pluto model is very large and it was not possible to use the static approach with it relying only on the randomaccess memory (RAM) of the used hardware. In order to perform the conventional RTM, we implement and compare the effective boundary technique for wavefield reconstruction with the RTM using the proposed dynamic approach. With the dynamic approach, it was possible to perform RTM of a 2D seismic data obtained from the Pluto model using only the RAM of the computational nodes and without the need of reconstruction techniques. |
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Artigo em Revista
| Multiphase flow mobility impact on oil reservoir recovery: An open-source simulation This work uses Computational Fluid Dynamics (CFD) to simulate the two-phase flow (oil and water) through a reservoir represented by a sandbox model. We investigated the influence in the flows of water having higher and lower mobilities than oil. To accomplish this, we also developed a dedicated solver, with the appropriated equations and representative models implemented in the open-source CFD OpenFOAM platform. In this solver, the black-oil model represented the oil. The results show that the Buckley–Leverett water-flood equation is a good approach for the three-dimensional flow. We observe that the water wall front is mixed to some extent with the oil and evolves obeying an exponential law. Water with mobility lower than oil is not common. However, in this case, the oil recovery is improved and the amount of injected water is reduced. The results comparing different mobilities show that a careful economic assessment should be performed before the field development. We have shown that the low water mobility can increase, as in this studied example, the water front saturation from 0.57 to 0.73, giving a substantial improvement in the oil recovery. The reservoir simulation can provide all process information needed to perform an economical assessment in an oil field exploration. |
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Artigo em Revista
| Cloud-computing approach for an environmental, social, and corporate governance focus in universities and businesses There is an increasing demand for high-performance computing on geophysical exploration applications, which implies more carbon emissions due to higher energy consumption. Furthermore, increasing the concern about the environmental and social impact that this can generate. We show how cloud computing can handle these challenges simultaneously and thereby assist business leaders in their decision-making. Cloud computing is a paradigm in which users rent computing capacity from providers on a pay-as-you-go basis, thereby reducing the carbon footprint by up to 88%. It can run software for years uninterrupted using the same capital required to acquire and run on-premises infrastructure, even if such infrastructure has over a thousand graphics processing units. However, the managers must consider that challenges arise from using the cloud, such as trusting their data in a third-party server and expenses throughout the years, especially with storage. |
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Artigo em Revista
| Faster and cheaper: How graphics processing units on spot-market instances minimize turnaround time and budget Cloud computing is enabling users to instantiate and access high-performance computing clusters quickly. However, without proper knowledge of the type of application and the nature of the instances, it can become quite expensive. Our objective is to indicate that adequately choosing the instances provides a fast execution, which, in turn, leads to a low execution price, using the pay-as-you-go model on cloud computing. We have used graphics processing unit instances on the spot market to execute a seismic-data set interpolation job and compared their performance with regular on-demand central processing unit (CPU) instances. Furthermore, we explored how scaling could also improve the execution times at small price differences. The experiments have shown that, by using an instance with eight accelerators on the spot market, we obtain up to a 300 times speedup compared with the on-demand CPU options, while being 100 times cheaper. Finally, our results have shown that seismic-imaging processing can be sped up by an order of magnitude with a low budget, resulting in faster and cheaper processing turnaround time and enabling new possible imaging techniques. |
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