Autor: João Lucas Braga Da Silva

Incorporation of Conceptual Geological Model for Fracture Distribution in 3D Reservoir Modeling

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Conceptual Geological Models (CGM) serve as a robust tool for 3D reservoir model building, since they allow the representation of geological knowledge in the subsurface, guiding the depiction of fault and fracture distribution, providing insights into their local occurrences, densities, orientations, and aperture. The Brazilian pre-salt carbonate reservoirs are characterized by complex fault systems and natural fractures, with variations related to structural geology, paleotopography, and stratigraphy. This study aims to integrate a CGM into 3D reservoir modeling, focusing on faults and fractures below seismic resolution for an area within an oilfield in the Santos Basin (Santos Outer High), centered on the Barra Velha Formation (BVE), where a PSDM seismic volume, wells (with conventional and special logs), and core samples and thin sections were available. Data analysis resulted in the interpretation of the main horizons in the area and the preferential distribution of fracture families (P10, P20, and P21). Findings from a CGM of fracture distribution were incorporated into reservoir modeling through the Discrete Fracture Network (DFN) methodology, in particular, that the fractures in the BVE are generally correlated with silica-rich zones of the formation. From this, maps of silica distribution were elaborated for the different stratigraphic units of the BVE and used as a constraint for the creation of the fracture networks and the DFN model. Preliminary results show that the use of a CGM proved to be advantageous in the DFN model creation process.

Estimating Rock Typing in Uncored Wells Using Machine Learning Techniques for Brazilian Pre-Salt Carbonate Reservoir

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Accurate rock typing in uncored wells is essential for enhancing reservoir models, particularly in complex geological formations like the Brazilian pre-salt carbonate reservoirs. This study explores the application of machine learning (ML) techniques to estimate rock types in uncored wells. The research leveraged core data from 11 cored wells to calculate the Rock Quality Index (RQI) and Flow Zone Indicator (FZI), identifying 14 distinct rock types through the Discrete Rock Typing (DRT) method, along with well log data such as gamma ray, density, neutron, permeability, and porosity. Various machine learning models, including Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Decision Tree, Gradient Boosting, Naive Bayes, XGBoost, and Random Forest were tested, where XGBoost achieved the highest accuracy of 73.3%. Applying XGBoost to all wells resulted in accuracy ranging from 0.6 to 0.91 and the model was subsequently used to estimate rock types in over 20 uncored wells to generate reservoir simulation models. This study highlights the efficacy of machine learning (particularly XGBoost) in addressing reservoir complexities and offering significant improvements in the understanding and development of carbonate reservoirs.

A numerical procedure to identify vugs and fractures in rock samples based on CT scan data

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This article introduces novel algorithms for fractures and vugs recognition in computed tomography (CT) rock images. The proposed algorithms can be used in both two-dimensional (2D) and three-dimensional (3D) approaches to accurately identify fractures and vugs within rock samples. A detailed explanation of the implemented method is provided, elucidating the underlying principles of the algorithms. Furthermore, the method’s applicability is investigated through testing with various models of pre-trained neural networks.The study contributes to rock image analysis by introducing effective techniques for identifying fractures and vugs in CT scans that can be applied for geological and engineering purposes. In a demonstrative application, this methodology was implemented to generate a two-dimensional finite element mesh, thereby facilitating the simulation of the Darcy equation using the Finite Elements Method.

Numerical Simulation Study of Relative Permeability Hysteresis in a Fractured Carbonate Reservoir Subjected to Water-Alternating-Gas Injection (WAG-CO2)

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The hysteresis phenomenon in relative permeability curves is an important aspect when modeling WAG- CO2 processes. Although experimentally validated, this phenomenon is often overlooked in numerical studies. Furthermore, the impact of hysteresis on oil recovery is a complex issue, which may hinder or contribute to the sweep efficiency. This work evaluates different hysteresis scenarios for a comprehensive analysis of this phenomenon in a synthetic fractured carbonate field analogous to a pre-salt field in Brazil (UNISIM-II-D). The hysteresis is applied in two different scenarios: (i) in low-permeability porous medium (LK); (ii) also included to a lesser extent in high-permeability layers (LSK). The work initially presents sensitivity analyses based on attributes of the Larsen-Skauge WAG hysteresis model. The results reveal that the impact of hysteresis on oil recovery differ for different production strategies. The sensitivity profile of each hysteresis attribute also differs notably between the two assessed hysteresis scenarios, with the effect being more pronounced in the LSK scenario, even at low attribute values. Then, a nominal optimization of reservoir development and management variables is presented for each hysteresis scenario and for the scenario with no hysteresis. We verified that the application of an optimized solution in a non-corresponding scenario may compromise economic and production indicators. The results demonstrate the importance of incorporating the hysteresis phenomenon into models used in life cycle optimization processes (LCO), as the field should be operated differently when hysteresis is identified as a real phenomenon. Finally, the impact of hysteresis on an ensemble of 197 models under uncertainty was evaluated considering two approaches: (i) hysteresis scenario as uncertainty; (ii) values of the Larsen-Skauge’s hysteresis model as uncertainty. In both cases, the NPV risk curves were similar to the original one, in which hysteresis was not included as uncertainty. However, changes were observed for some production indicators and the impact may be more significant for different cases. The results also revealed that different hysteresis scenarios can impact the NPV and production indicators differently when applied to an ensemble of reservoir scenarios, resulting in either positive or negative trends. In this benchmark, hysteresis in low-permeability porous medium at immiscible conditions tend to cause a slight decrease of oil recovery, while hysteresis in Super-k promoted a better mobility control of gas and water in these layers, favoring the production and economic outcomes. Hence, this numerical study provides an extensive analysis of the effects of different hysteresis scenarios on applications that have not been previously explored, such as hysteresis in high- permeability layers, in reservoir life-cycle optimizations, and in a probabilistic approach.

A Posteriori Error Estimation For Linear Elasticity With Weak Stress Sym- metry

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This work focuses on the development of a posteriori error estimation for linear elasticity with weak stress symmetry [1]. The procedure is based on the post-processing of the enriched displacement field computed by a mixed finite element formulation, as in [2]. Inspired by [3], the estimation involves two post-processing techniques: averaging the numerical displacement over element interfaces and solving a set of local problems. By applying the Prager-Synge theorem in the context of linear elasticity [4], we are able to develop an estimator with known constants.

Visualization of Single- and Two-Phase Flows in the Stage of a Transparent Electrical Submersible Pump (ESP) Prototype

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Dynamic multiphase flow behavior inside a mixed flow Electrical Submersible Pump (ESP) has been studied experimentally and theoretically for the first time. The overall objectives of this study are to determine the flow patterns and bubble behavior inside the ESP and to predict the operational conditions that cause surging. An experimental facility has been designed and constructed to enable flow pattern visualization inside the second stage of a real ESP. Special high speed instrumentation was selected to acquire visual flow dynamics and bubble size measurements inside the impeller channel. Experimental data was acquired utilizing two types of tests (surging test and bubble diameter measurement test) to completely evaluate the pump behavior at different operational conditions. A similarity analysis performed for single-phase flow inside the pump concluded that viscosity effects are negligible compared to the centrifugal field effects for rotational speeds higher than 600 rpm. Therefore, the two-phase flow tests were performed for rotational speeds of 600, 900, 1200, and 1500 rpm. Results showed formation of a large gas pocket at the pump intake during surging conditions.