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 Camboriú 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 cross-plots. 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

Cycle-consistent convolutional neural network for seismic impedance inversion: An application for high-resolution 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 learning-based seismic inversion has recently gained attention
due to its capacity to establish non-linear relationships between observed data and model parameters, producing
robust acoustic impedance estimates. We employed a 1D cycle-consistent convolutional neural network (CNN) to
perform the high-resolution seismic impedance inversion in the turbidite reservoirs of the Jubarte Field, Campos
Basin, Brazil. The neural network was trained using geostatistics-based pseudo-wells with high pattern variability. Before applying the trained CNN, we performed the seismic data pre-conditioning to remove high and
low-frequency noises affecting the data amplitudes, making the dataset more suitable for seismic impedance
inversion. Our results show that the deep learning-based inversion produced a high-resolution 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 pre-conditioning 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 open-loop CNN and
the traditional model-based inversion, the cycle-consistent network produced the best estimate, with good lateral
continuity, vertical resolution, and correlation. We support that modern deep-learning architectures like the one presented can be efficiently integrated into reservoir characterization workflows for enhancing subsurface

Artigo em Revista

Magneto-polariton: Strong tilted magnetic field applied on confined electron gas in a wide Ga(1-x)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 magneto-polariton. 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, NE-Brazil.
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 three-dimensional 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 pre-salt 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

First-break prediction in 3-D land seismic data using the dynamic time warping algorithm
This paper presents a new methodology to assist geophysicists in determining the first-break event in a 3-D seismic data set using the well-known technique called dynamic time warping algorithm (DTW), which is usually used to find the optimal alignment between two time-series.
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 pre-conditioned by the topographic and linear moveout to improve the method’s
accuracy. To demonstrate the technique’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 Polo-Miranga 3-D seismic cube located in the Reconcavo sedimentary basin, Bahia-Brazil, and in the seismic data acquired from the Blackfoot field in Alberta, Canada. The high-quality 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 short-time averages with long-time averages. Finally, we performed the static correction calculation to ensure that the time distortion resulting from the terrain and the low-velocity layer was mitigated in shoot gathers and in the stacked section.

Artigo em Revista

Prediction of stress components using the Beltrami-Michell method
This paper describes some numerical experiments for stress modeling in the zone around a reservoir in a sedi-mentary basin, where oil and gas exploration is real or potential. We aim to map mainly low- and high-pressure
zones, under the principle that they act as push-and-pull natural pumps for fluid accumulation. The necessary data for practical work is based on seismic data, as a post-migration 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 Beltrami-Michell’s partial
differential equation with Dirichlet conditions. The method employed was the Green’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 Beltrami-Michell problem, which takes the form of a Poisson’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 long-term correlations and trend in time series of precipitation. Two databases were used for this purpose: in situ observations along the period of 1960–2020 and the Climate Hazards group InfraRed Precipitation with Stations (CHIRPS) dataset, along the period from 1981 to 2021. We have applied the rescaled-range analysis and the detrended fluctuation analysis for long memory investigation, and the linear
regression and Mann-Kendall 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 ill-conditioned 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 well-to-well 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 stratigraphic-structural trapping in pre-salt carbonate reservoirs of the Santos Basin: A case study in the Iara complex
The reservoir characterization of the Brazilian Santos basin’s pre-salt 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 pre-salt
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 range’s five main seismic patterns indicates potential stratigraphic-structural barrier zones. The well log analysis correlated with formation pressure data
enabled the identification of several irregular oil-water contacts and free water levels. Small relative variations
are associated with the perched-water phenomenon, while large variations are related to compartmentalization.
The formation pressure analysis shows the hydraulic compartmentalization of the reservoirs in the Berbigao ˜
Field. Sururu and Atapu fields’ 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 oil-associated 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 perched-water phenomenon. Our study highlights the importance of
multidisciplinary analysis to comprehend complex carbonate reservoirs connectivity, and offers input to de-risk
new ventures’ pre-salt reservoir quality.

Artigo em Revista

Analysis of alternative strategies applied to Naïve-Bayes classifier into the recognition of electrofacies: Application in well-log data at Recôncavo Basin, North-East Brazil.
This paper is concerned with the applicability of different strategies to improve the definition of prior probabilities and/or likelihoods of naïve Bayes (NB) classifiers. Standard NB method computes likelihoods and priors by means of normal distributions and evaluation of the entire training data-set, 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 data-set in individual wells in a committee architecture framework. A tuning strategy is also considered for automatic estimation of prior probabilities in an optimization-scheme. 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 above-mentioned 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., 7-MP-50D-BA) of Massapê Field, in Recôncavo 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.

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