Produção Científica
Artigo em Revista
Characterization of subaerial lava flows of the presalt strata in the Santos Basin based on basic well logs It is hard to identify volcanic morphologies using well logs to support technical decisions during well drilling and the acquisition of geological information. Therefore, this study was carried out on the volcanic sequence present in the Presalt interval of the Santos Basin, Brazil, which is referred to as the CamboriÃº Formation. This section was described in a previous study using image well logs as a succession of subaerial lava flows formed mainly by compound pahoehoes, sheet pahoehoes and rubbly pahoehoes. Based on sidewall core samples and petrophysical, geochemical and mineralogical reports, we identified five electrofacies from gamma ray, resistivity, sonic, density and neutron logs, representing patterns for identifying lava flows in subaerial sequences. In addition, we applied a porosity quantification method that resulted in a method for obtaining information from the matrix and presented coherent values in facies that did not present amygdalae or breccias and inferring altered zones from variations in resistivity and density logs or from crossplots. Patterns of well log responses were defined for each type of lava flow present in the studied well, as was the inference about the most favorable facies for reservoirs. This methodology, which uses basic well logs from basalts, is unprecedented in the Presalt sequence and can be easily used to evaluate this exploratory frontier because of its close association with subaerial volcanism. 

Artigo em Revista
Cycleconsistent convolutional neural network for seismic impedance inversion: An application for highresolution characterization of turbidites reservoirs. Acoustic impedance is a subsurface layer parameter crucial for reservoir characterization due to its relationship with petrophysical properties. Seismic impedance inversion is the routine conventionally used to calculate the acoustic impedance in 3D seismic datasets. Deep learningbased seismic inversion has recently gained attention due to its capacity to establish nonlinear relationships between observed data and model parameters, producing robust acoustic impedance estimates. We employed a 1D cycleconsistent convolutional neural network (CNN) to perform the highresolution seismic impedance inversion in the turbidite reservoirs of the Jubarte Field, Campos Basin, Brazil. The neural network was trained using geostatisticsbased pseudowells with high pattern variability. Before applying the trained CNN, we performed the seismic data preconditioning to remove high and lowfrequency noises affecting the data amplitudes, making the dataset more suitable for seismic impedance inversion. Our results show that the deep learningbased inversion produced a highresolution estimate, allowing an accurate internal characterization of turbidite lobes. Quantitatively, the estimated average correlation coefficient in the eight wells evaluated in this study was 0.78. We observed that the preconditioning step was important for this application since the 1D architecture utilized could not deal properly with the noise as it disregards lateral connections. 2D and 3D networks may address this issue. Compared to the openloop CNN and the traditional modelbased inversion, the cycleconsistent network produced the best estimate, with good lateral continuity, vertical resolution, and correlation. We support that modern deeplearning architectures like the one presented can be efficiently integrated into reservoir characterization workflows for enhancing subsurface assessment. 

Artigo em Revista
Magnetopolariton: Strong tilted magnetic field applied on confined electron gas in a wide Ga(1x)Al(x)As quantum well The coupling of an electron gas confined by a harmonic potential and submitted to a strong magnetic field tilted in relation to the confining direction creates an excitation called here magnetopolariton. This work describes the origin of this excitation and calculates the energy eigenvalues for different tilted angles. It presents the reasons leading to the crossings and repulsions of the energy bands, the degeneracy of the states, the way the Fermi levels change with the magnetic field, the influence of an external electric field, and how the Hall resistance plateaus change with the change in the tilted angle. 

Artigo em Revista
An integrated 3D digital model of stratigraphy, petrophysics and karstified fracture network for the Cristal Cave, NEBrazil. Digital Outcrop Models (DOMs) are virtual representations of geological features. Although DOMs are widely used tools in geosciences, their integration with other datasets remains relatively underexplored. We combined a DOM, derived from a photogrammetric survey of a carbonate sequence, with lithostratigraphic, petrophysical (porosity, permeability and uniaxial compressive strength), fracture distribution, and karst dissolution information to compose a single integrated threedimensional digital model. The study site is one of the entrances of the Cristal Cave (Sao Francisco Craton, Northeastern Brazil), which has been used as a structural and diagenetic outcrop analog for the Brazilian presalt carbonate reservoirs. Data from fracture distributions, measured on the exposed surfaces of the cave, were used to build a Discrete Fracture Network, based on the solution of the stereology inverse problem. Fracture apertures were then modified to generate different scenarios of karstification, thus composing Discrete Fracture and Karst Networks. This integrative approach brought relevant insights into the cave development due to dissolution along fracture clusters. Our methodology offers better geological data handling to build static models to be used in a fluid flow modeling environment, contributing to bridge the gap between geophysics/geology and engineering approaches. 

Artigo em Revista
Firstbreak prediction in 3D land seismic data using the dynamic time warping algorithm This paper presents a new methodology to assist geophysicists in determining the firstbreak event in a 3D seismic data set using the wellknown technique called dynamic time warping algorithm (DTW), which is usually used to find the optimal alignment between two timeseries. We used the optimal path from the cost matrix to identify the first break in the seismogram using a few picks (seeds) made by an interpreter as a reference to perform this task. Furthermore, the data were preconditioned by the topographic and linear moveout to improve the methodâ€™s accuracy. To demonstrate the techniqueâ€™s robustness, first, we applied the methodology in a synthetic seismic data. After demonstrating the efficiency of the algorithm, we applied the aforementioned methodology in the PoloMiranga 3D seismic cube located in the Reconcavo sedimentary basin, BahiaBrazil, and in the seismic data acquired from the Blackfoot field in Alberta, Canada. The highquality results showed consistency in determining the first break in all ranges of offsets, demonstrating an alternative way to accelerate this seismic processing step. Furthermore, we compared the results obtained by the proposed methodology with an algorithm based on comparing the shorttime averages with longtime averages. Finally, we performed the static correction calculation to ensure that the time distortion resulting from the terrain and the lowvelocity layer was mitigated in shoot gathers and in the stacked section. 

Artigo em Revista
Prediction of stress components using the BeltramiMichell method This paper describes some numerical experiments for stress modeling in the zone around a reservoir in a sedimentary basin, where oil and gas exploration is real or potential. We aim to map mainly low and highpressure zones, under the principle that they act as pushandpull natural pumps for fluid accumulation. The necessary data for practical work is based on seismic data, as a postmigration process with the knowledge of velocities of the P and S waves, and the density information. The computation is designed for simple geometries to represent a reservoir geology, and it is addressed as a boundary value problem (BVP) involving the BeltramiMichellâ€™s partial differential equation with Dirichlet conditions. The method employed was the Greenâ€™s function expressed by Fourier series for the solution of the BVP, where the boundary conditions are given by the stress components along the boundary of the target volume. The first stress invariant controls the elastic mechanical behavior of the subsoil; therefore, once the distribution of rock pressure is obtained, and the boundary conditions are defined, solving the BVP allows the calculation of the stress components distribution (normal and tangential) within a separate target volume for details. The relationship between rock pressure and stress components is established by the BeltramiMichell problem, which takes the form of a Poissonâ€™s equation. The proposed method was applied in a more complex target zone present in the Marmousi model, which contains reservoirs within regions of interest, expanding to more realistic complex problems. 

Artigo em Revista
Long memory and trend in time series of precipitation in Mozambique Many climate studies in Mozambique have clearly identified signals of climate change, especially changes in the extreme temperatures. Regarding precipitation, there is still a gap on the knowledge of how it is behaving due to both internal and external factors in the climate system. In this study, we have investigated the existence of longterm correlations and trend in time series of precipitation. Two databases were used for this purpose: in situ observations along the period of 1960â€“2020 and the Climate Hazards group InfraRed Precipitation with Stations (CHIRPS) dataset, along the period from 1981 to 2021. We have applied the rescaledrange analysis and the detrended fluctuation analysis for long memory investigation, and the linear regression and MannKendall methods for trend analysis. Results have shown the existence of long memory in precipitation in most parts of Mozambique, being stronger in the southern and central regions and weakening toward the north of the country. On the other hand, significant trend signals of precipitation were detected in some isolated areas of Mozambique, presenting an increase in some regions such as the southern part of Manica and eastern of Inhambane provinces and a decrease in other regions such as the coastal areas of Zambezia and Nampula. These findings indicate that the probability of a random occurrence of precipitation is minimal, and the observed trends are likely to continue for a long period in future. Dry land agriculture should be prepared to adapt to new precipitation regime in the regions mentioned hereof 

Artigo em Revista
Barbieri Criterion for Solution Appraisal in Geophysical Diffraction Tomography. Diffraction tomography provides a high resolution velocity image from the region under study. Because it is a type of illconditioned inverse problem, diffraction tomography requires some kind of regularization, such as regularization by derivative matrices. Quantitative or qualitative criteria for the solution appraisal of inverse problems are just as important as the solution itself. An effective criterion is the Barbieri approach, which is the main scope in this study. It is implemented in three steps: (i) the estimated model obtained through the inversion of the observed data (scattered acoustic field); (ii) a second inversion, this time of the complementary observed data which provides the complementary estimated model; (iii) the sum of the estimated model and complementary estimated model. If the inversion is exact, this sum must be a constant value for the whole vector. If this does not occur, the sum image indicates that the inversion was not satisfactory (quantitative effect) and in which regions the estimated model was not well recovered (qualitative effect). Simulations were performed on two synthetic models, one with welltowell geometry and the other with surface seismics geometry. The results, confronted with the RMS deviation between the estimated and the true model, validated the use of the Barbieri criterion in diffraction tomography. 

Artigo em Revista
Compartmentalization and stratigraphicstructural trapping in presalt carbonate reservoirs of the Santos Basin: A case study in the Iara complex The reservoir characterization of the Brazilian Santos basinâ€™s presalt carbonates is a major challenge due to the faciological and depositional complexity, providing high lateral and vertical heterogeneities, and consequently, the formation of static/dynamic intraformational seals. Regarding this context, there is a massive presalt accumulation known as the Iara Cluster. During the early development stage, this cluster was split into three distinct accumulations named Berbigao, Sururu, and Atapu. This study aims to characterize the geological and hydrodynamic factors that affect the Iara Cluster reservoir compartmentalization. To achieve this objective, we applied an integrated analysis based on 3D seismic interpretation, well logs, pressure formation and fluid geochemistry analysis. The spatial distribution of the reservoir rangeâ€™s five main seismic patterns indicates potential stratigraphicstructural barrier zones. The well log analysis correlated with formation pressure data enabled the identification of several irregular oilwater contacts and free water levels. Small relative variations are associated with the perchedwater phenomenon, while large variations are related to compartmentalization. The formation pressure analysis shows the hydraulic compartmentalization of the reservoirs in the Berbigao Ëœ Field. Sururu and Atapu fieldsâ€™ oil zones are possibly connected by a dynamic sealing zone or a common aquifer, which provides a pressure balance on a geological time scale, since their oil gradients are similar. Our analyzes identified stratigraphic components in reservoir trapping associated with reservoir quality lateral obliteration. Dissimilarities in the oil sample composition and properties indicate different petroleum charge histories along with the distinct CO2 contamination timing. The Berbigao oilassociated gas formed in earlier stages of maturation than the Sururu and Atapu samples. The results integration through a risk matrix revealed areas with a greater chance of compartmentalization and perchedwater phenomenon. Our study highlights the importance of multidisciplinary analysis to comprehend complex carbonate reservoirs connectivity, and offers input to derisk new venturesâ€™ presalt reservoir quality. 

Artigo em Revista
Analysis of alternative strategies applied to NaÃ¯veBayes classifier into the recognition of electrofacies: Application in welllog data at RecÃ´ncavo Basin, NorthEast Brazil. This paper is concerned with the applicability of different strategies to improve the definition of prior probabilities and/or likelihoods of naÃ¯ve Bayes (NB) classifiers. Standard NB method computes likelihoods and priors by means of normal distributions and evaluation of the entire training dataset, respectively. NB is one of the most prolific classification methods in data mining and machine learning. Despite decent efficiency facing good training data, NB classifiers present the intriguing assumption of conditional independence between the attributes. Several algorithms have been proposed to improve the effectiveness of NB classifiers by inserting discriminant approaches into its generative structure. From a reliability perspective, the standard NB approach might not explore the real capabilities of NB classifiers facing the lithologic classification problem. To cover such distrust, a novel approach considering four particular strategies are suggested and compared to the standard NB classification outcomes. At first, a kernel density estimation (KDE) is considered to ameliorate the likelihood models. We also apply the NB classifier in parts by separating the training dataset in individual wells in a committee architecture framework. A tuning strategy is also considered for automatic estimation of prior probabilities in an optimizationscheme. Another novel alternative, named as CRC, adapted to the standard NB classifier consists in defining priors based on depth zones from regional stratigraphic information in which to apply NB classifier. We prepare an extensive statistical investigation, based on precision, recall, classification errors, fscores and confusion matrices to bespeak the most relevant NB strategy for classification of electrofacies. Despite the decent classification outcomes for all abovementioned strategies, CRC can be considered, by a narrow margin, the most prolific method to be applied as an improvement of the standard NB to classify rock units. Tests are performed on a validation well (i.e., 7MP50DBA) of MassapÃª Field, in RecÃ´ncavo Basin, northeast Brazil to highlight the classification particularities provided by the improved strategy. A significant improvement in the classification of sandstones (i.e., from 68 % to 83 % accuracy) is observed, according to the confusion matrix analysis. Additionally, a minimal decreasing is observed into the classification of shales and slurries (i.e., from 92% to 90% and to % to 56%, respectively), which is acceptable according to the fscores and errors. This aspect reinforces the relevance of using the NB classifier jointly with previous geologic information to optimize the lithologic classification. 
