Produção Científica



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.

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.

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.

Artigo em Revista
18/07/2022

Mineralogy based classification of carbonate rocks using elastic parameters: A case study from Buzios Field
Brazilian presalt carbonate reservoirs are highly heterogeneous. This feature is mostly justified by the nature of the original depositional system and subsequently diagenetic processes. Consequently, reserve estimates and production forecasting are under large uncertainties. In this geologic context, it is of great relevance to develop techniques that helps to obtain a detailed description on the spatial distribution of these different rocks. In doing so, it contributes to the understanding of presalt carbonate sedimentary deposits, providing inputs for more predictive reservoir models. Traditionally, these carbonates are grouped into three classes, from which only one exhibits reservoir properties. Using a dataset from Buzios Field, this work proposes a characterization of presalt carbonate reservoir rocks by grouping them in terms of their mineral composition. Taking advantage of rock physics concepts, we aim to potentialize the use of elastic parameters for multiple rock type discrimination. We explored several attempts for rock classification by using a Bayesian approach. Among all the tested propositions, a two-step workflow for five lithotypes classification, emerges as the most appropriate for the Buzios Field. In this scheme, three lithotypes represent good-quality reservoirs and the other two are low-porosity and Mg-clay-rich carbonates. The average root-mean-square error of the most likely a posteriori rock proportions is around 8.4%, only approximately 1% higher than the conventional three lithotypes configuration. To support that, we compared different methodologies for Bayesian classification at well-log scale through acoustic impedance and compressional to shear velocity ratio. Potential applicability of the proposed methodology at field scale is reinforced by similar results achieved using well-logs filtered to the seismic bandwidth.

Artigo em Revista
18/07/2022

The influence of subseismic-scale fracture interconnectivity on fluid flow in fracture corridors of the Brejões carbonate karst system, Brazil
The present study used a multitool approach to characterize fractures of several orders of magnitude in large fracture corridors, caves, and canyons to investigate their impact on fluid flow in carbonate units. The study area is the Brejões carbonate karst system that is located in the Neoproterozoic Salitre Formation in the Irecê Basin, São Francisco Craton, Brazil. The approach included satellite imagery, used for interpreting the regional structural context, Unmanned Aerial Vehicle (UAV) and ground-based Light Detection And Ranging (LiDAR) imagery, used for detailed structural interpretation. Regional interpretation revealed that fracture corridors, caves and canyons occur along a N–S-oriented anticline hinge. An advanced stage of karstification caused fracture enlargement and intrabed dissolution, and the formation of caves and canyons. A river captured by the highly fractured zone along the anticline hinge played an important role as an erosive agent. Detailed characterization of fracture corridors comprised structural analysis, topological studies, persistence estimations, power-law fitting of fracture trace length distributions, and identification of network backbones. Our results indicate that fracture corridors comprise four subvertical fracture sets: N–S and E-W and a conjugate pair, NNE-SSW and NW-SE. Fractures observed in the caves show the same dominant directions. Fracture directions are consistent with a common origin associated with the anticline folding. Fracture traces range from 1.0 m to 300 m, comprising both subseismic (<50 m) and seismic scale fractures (>50 m). Networks have dominance of node terminations Y and X (notably Y), CB values higher than 1.8, high P20 and P21 persistence values, and highly interconnected backbones. Fracture network connectivity is associated with power-law exponents greater than 2.5 for the fracture trace distributions, indicating large influence of subseismic-scale fractures on fluid flow. As the final result of folding and karstification, large volumes of secondary macroporosity were created, particularly in the zone of maximum fracture intensity around the hinge zone of the anticline. This scenario can be used to understand better oil reservoirs formed in similar structural controls in near-surface conditions.

Artigo em Revista
18/07/2022

A constrained version for the stereology inverse problem: Honoring power law and persistences of the fracture traces exposed on arbitrary surfaces
We present a stereological study in a cave setting that is part of a karstic carbonate system located in the SĂŁo Francisco Craton, Brazil. Using a Lagrangian approach, a constrained version of the nonlinear inverse problem of stereology is solved. Besides the classical demand of fitting the histogram of fracture traces measured on arbitrary exposed surface, it is imposed that the solution honors also measures of surface intensity (p21) and power law exponent obtained from fracture traces on the same exposed surfaces. Estimates of volumetric intensities (p32) of conjugate fracture pairs might be also imposed to be close values. The resulting cost functional is minimized using the Particle Swarm Optimization (PSO) method. The implemented version of PSO furnishes the best solution and a set of suboptimal quasisolutions, from which the solution uncertainty is evaluated. A key aspect of the implemented approach is that all terms composing the cost functional are normalized, obtaining as a result, robustness for the weighting parameters to changes in the input data. The resulting stochastically simulated discrete fracture networks honor all statistical observations but, in general, do not reproduce the positions of the observed fracture traces. The methodology is applied to synthetic and field data examples. All obtained solutions are stable and geologically reliable.

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