Produção Científica



Artigo em Revista
29/03/2023

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 BerbigĂŁo, 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
08/03/2023

Bibliometric analysis of surface water detection and mapping using remote sensing in South America
The detection and mapping of surface water resources for South America (DMSWSA) in Remote sensing context is a highly relevant issue from a scientific point of view due to the impact on the understanding of changes in the hydrological cycle, water availability, and climate in global terms since 45% of all water resources available on the globe are present on this continent. This study presents a new approach to evaluating the scientific literature of the last 21 years focused on DMSWSA in a Remote sensing scientific literature. Our study aims to carry out a bibliometric analysis on the application of the DMSWSA in a Remote sensing dominium to assess researchers, countries, and trends. We used the Scopus database for the literature search. Then we used bibliometric tools to access information and reveal quantification patterns of literature. Our results show that the most relevant contributions involved Brazil and Argentina. DMSWSA has only shown an expansion in recent years regarding the number of articles published and citations. It was possible to show that the DMSWSA in a Remote sensing scientific area needs further collaboration expansion between countries within South America and beyond this continental border. We reveal aspects of great importance and interest in the literature using bibliometric approaches to give a clear view of research trends for DMSWSA.

Artigo em Revista
08/03/2023

On the estimation of reflectivity in reverse time migration: Implementational forms of the inverse-scattering imaging condition
The inverse-scattering imaging condition (ISIC) for reverse time migration (RTM) aims at recovering amplitudes proportional to seismic reflectivity. It has been derived as the high-frequency asymptotic inverse of Born modeling, which justifies its being called a true-amplitude imaging condition. It involves the temporal and spatial derivatives of the up- and downgoing wavefields, in this way generalizing the conventional crosscorrelation imaging condition. The temporal derivations can be redistributed between different wavefield contributions, in this way deriving a set of different implementational forms of the ISIC. By making use of the wave equation for the up- and downgoing wavefields, one can substitute the time derivatives by the Laplacian operator. This provides a theoretical foundation for a popular filter for reducing the backscattering artifacts in RTM. Using Born data from a simple three-layer model and the Marmousi II model as well as the Sigsbee2b data, we have determined that the theoretical equivalence of the equations leads to similar but not identical images. Our numerical tests indicate that the ISIC versions using spatial derivatives are the most economical approach, and that the images obtained with the second time derivative of the source wavefield indicate slightly improved resolution over the other implementations, making the combination of these two characteristics the best choice.

Artigo em Revista
08/03/2023

Controls of fracturing on porosity in pre-salt carbonate reservoirs
This work aims to improve the understanding of how fracture zones affect carbonate reservoir properties based on
observations of a pre-salt well located in the Santos Basin, Brazil. The identification of fracture zones allowed for the observation of a relationship between the occurrence of rock fractures and the silicification, as the latter plays an important role in determining porosity (higher silica content may increase brittleness of the rocks therefore increasing the likelihood of creating fractures zones and fractures may be filled up reducing the total porosity). To support the proposed observation, an inte-grated study was conducted using borehole imaging, spectroscopy logs, and sidewall core samples. The
porosities were defined using nuclear magnetic resonance log analysis, alongside sidewall core samples, and thin sections. The integration of rock samples and well data with seismic analysis was performed to analyze the presence of a regional fault system that could explain high fracture densities as well as observed silica content characteristics. The results show how different types of cement filling up the formation pores affect fracture densities and total porosity. Furthermore, it was possible to infer that the amount of silica content observed in well logs and thin sections relates to hydrothermal fluids reaching out the reservoir through regional fault systems detected in the seismic section. Therefore, this paper
supports the comprehension of how diagenetic processes can significantly affect the properties of pre-salt reservoirs.

Material Didático
06/02/2023

MANUAL DE MODELAGEM DE DADOS DE GPR NO DOMÍNIO DO TEMPO (GPRMAX) APLICANDO EFEITOS DA DISPERSÃO ATRAVÉS DE UMA ABORDAGEM LINEAR PARA SIMULAR UM MODELO DE Q CONSTANTE USANDO VÁRIOS POLOS DEBYE.

Artigo em Revista
10/10/2022

Viscoelastic and viscoacoustic modelling using the Lie product formula
We present efficient and accurate modelling of seismic wavefields in anelastic media.We use a first-order viscoelastic wave equation based on the generalized Robertsson’sformulation. In our work, viscoacoustic and viscoelastic wave equations use the stan-dard linear solid mechanism. To numerically solve the first-order wave equation, weemployed a scheme derived from the Lie product formula, where the time evolutionoperator of the analytic solution is written as a product of exponential matrices, andeach exponential matrix term is approximated by the Taylor series expansion. Theaccuracy of the proposed scheme is evaluated by comparison with the analytical so-lution for a homogeneous medium. We also present simulations of some geologicalmodels with different structural complexities, whose results confirm the accuracy ofthe proposed scheme and illustrate the attenuation effect on the seismic energy duringits propagation in the medium. Our results demonstrate that the numerical schemeemployed can be used to extrapolate wavefields stably for even larger time steps thanthose usually used by traditional finite-difference schemes.

Artigo em Revista
10/10/2022

Multiparameter vector-acoustic least-squares reverse time migration
The use of dual-sensor acquisitions enabled different studies using the so-calledvector-acoustic equations, which admit particle velocity (displacement or accel-eration) information instead of solely the pressure wavefield. With cost far fromelastic formulations but comparable with the usually used second-order acousticequation, previous works involving the use of vector-acoustic equations along withmulticomponent data have been applied to conventional reverse time migration andfull-waveform inversion, always emphasizing the benefits of using wavefields con-taining directivity information, which make the receiver ghosts interact constructivelywith the backpropagated reflected wavefield. Thus, generated results are superior tothose of conventional single-component data imaging techniques, particularly withspatial subsampling of marine seismic data. To assess whether the effects of applyingthe vector-acoustic equations persist in a linearized inversion, we developed a multi-parameter vector-acoustic least-squares reverse time migration, inverting reflectivitiesassociated with velocity and density. To demonstrate the method’s performance, weapply it to two-dimensional numerical examples and compare the results with thoseobtained by the conventional acoustic least-squares reverse time migration. Theresults obtained by the vector-acoustic least-squares reverse time migration methodare accurate for all inverted parameters and also deliver better convergence whencompared with the conventional least-squares reverse time migration.

Dissertação de Mestrado
10/10/2022

Avaliação do modelamento da propagação de ondas sísmicas pelo método lowrank
O modelamento da propagação da onda Ă© uma parte fundamental para o imageamento sĂ­smico, pelo qual se requer mĂ©todos precisos para representar o campo de onda. O mĂ©todo lowrank Ă© aplicado Ă  matriz propagadora determinada pela extrapolação da solução da equação da onda. Nesse trabalho, Ă© avaliado o desempenho absoluto e relativo do mĂ©todo lowrank em meios homogĂȘneos nos quais tem-se expressĂ”es teĂłricas, assim como em meios heterogĂȘneos. Realizamos vĂĄrios testes em modelos de meios homogĂȘneos com diferentes discretizaçÔes espacias e temporais, e a resposta do modelamento foi comparada com a solução analĂ­tica, mostrando boa acurĂĄcia cinematicamente, enquanto o desempenho na dinĂąmica foi afetado pelo intervalo de amostragem temporal, embora para cada modelo foi possĂ­vel determinar uma discretização temporal no qual conseguiu-se um erro dinĂąmico menor que 1% para modelar a onda em meios homogĂȘneos. Para determinar o desempenho relativo foi considerado o mĂ©todo de diferenças finitas tradicional de segunda ordem em tempo e espaço. Os coeficientes de reflexĂŁo aproximados pelo mĂ©todo lowrank considerando um modelo com um refletor plano foram comparados com os coeficientes de reflexĂŁo de ondas planas para os quais tem-se expressĂ”es teĂłricas. Neste caso, observa-se que com o mĂ©todo lowrank obtĂ©m-se os coeficientes com erro menor que 1% quando comparada ao coeficiente teĂłrico, mostrando melhor resultado do que obtido por diferenças finitas. O tempo computacional dos mĂ©todos foi avaliado, sendo que lowrank presenta um crescimento linear do tempo com o tamanho do modelo, isto sugere que para modelos de grande porte, lowrank economize o tempo de modelamento em comparação com diferenças finitas.

Artigo em Revista
18/07/2022

Characterizing seismic facies in a carbonate reservoir, using machine learning offshore Brazil.
The authors propose an approach that uses machine learning to characterize carbonate facies in a wildcat (Gato do Mato) prospect in the Santos basin, offshore Brazil. We analyzed different seismic attributes and selected those that best responded to the seismic patterns identified in the study area as input for an unsupervised classification.
The classification method used is the self-growing neural network (SGNN) technique that consists of the following steps:

1. Seismic pattern identification in seismic amplitude. The main patterns identified are build-up, debris, carbonate platform and bottom lake facies.
2. Generation and analysis of seismic attributes to characterize seismic patterns. We chose Eigen coherence, dip-steered enhancement, relief and relative acoustic impedance to help in seismic characterization.
3. We performed principal component analysis (PCA) of the attributes: amplitude filtered from dip-steered enhancement (seismic-driven structural filtering), Eigen coherence and relief.
4. Unsupervised seismic classification from the PCA of seismic attributes (item 3 above).

Using this approach, we associated the classified seismic facies with the patterns identified in the amplitude data. The seismic facies allowed us to differentiate the carbonate platforms from the build-up facies. However, the classification encountered difficulties in identifying the patterns associated with lake bottom facies and the chaotic seismic pattern of debris facies.

Artigo em Revista
18/07/2022

Probabilistic Estimation of Seismically Thin-Layer Thicknesses with Application to Evaporite Formations
The identification of potassium (K) and magnesium (Mg) salts prior to the well drilling is a key factor to avoid washouts, closing pipes, fluid loss damage, and borehole collapse. The Bayesian classification combines the outcomes from statistical rock physics and seismic inversion, providing the spatial occurrence of the most-probable salt types. It serves as a facies identifier of Mg–K-rich salts (bittern salts) before drilling. Nevertheless, the most-probable classification is limited to the seismic resolution which may underestimate seismically thin-layer thicknesses. Along with the most-probable facies, the Bayesian classification renders the facies probability volume. We demonstrate that the facies probability and facies-specific total thickness highly correlate to each other even under the threshold of seismic resolution. Thus, we employ the bittern-salts probability volume to predict thin-bed bittern-salts thickness in undrilled locations. To capture the variability of the seismic estimation, we resort to Monte Carlo-assisted simulations of wells that emulate the layering patterns of a site-specific deposition environment. These simulations are crucial to assist the estimation of the joint probability density function between the facies volume and the total thickness. Therefore, given the facies probability, the joint probability density function enables us to derive the conditional expectation and percentiles of thin-bed thicknesses. Furthermore, this paper proposes a method to quantify the negative influence of seismic noise in the estimation of thin-bed thicknesses. The blind well confirms the consistency of this technique to unfold the uncertainty in the seismic predictability of thin layers. We argue that this procedure is extendable to other facies.

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