142 registros encontrados - unidade Centro de Estudos de Energia e Petróleo
ARTIGO - Inglês
Assunto: Artigo original
Abstract: This paper explores a methodology for estimating the minimum time duration of experiments focused on wax deposition studies to be carried...
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Abstract: This paper explores a methodology for estimating the minimum time duration of experiments focused on wax deposition studies to be carried out for a passive manifold subsea cooler prototype geometry, upon relevant conditions for offshore oil & gas applications. The methodology encompasses 1D thermohydraulic numerical simulations of a CO2-rich dense-gas and waxy oil mixture flowing, as well as a mass transfer approach for the wax deposition. The idea is to obtain the minimum measurable impact of wax deposits on the pressure drop and temperature at the locations in which corresponding sensors shall be installed. The results applied to 10 different operational conditions for the cooler prototype are presented and thoroughly discussed, together with the phenomenology of the wax deposition and its relationship with the test conditions (operating pressure, liquid content and gas flow rates) and other important flow parameters, such as the mixture temperature, the occurrence of condensation, the pressure profile, among others. The main conclusions and possible next steps for this work are then outlined
ARTIGO - Inglês
Assunto: Calibração
Decisions in petroleum reservoir management usually involve high level of uncertainties. Therefore, information of different types is used to...
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Decisions in petroleum reservoir management usually involve high level of uncertainties. Therefore, information of different types is used to calibrate reservoir models for the production forecasts and decision analysis. One source of information is 3D seismic, which is highly correlated to petrophysical properties. These properties are a major source of uncertainty. The incorporation of 3D seismic data in flow models is affected by errors caused by discretization, scale differences, seismic modeling uncertainties, seismic propagation related distortions, among others. Nevertheless, these errors are commonly neglected in conventional model calibration workflows. This work treats seismic resolution loss as a form of model error that needs to be considered in the data assimilation process. In our tests, we used the synthetic data from a realistic benchmark case. First, we extended the methodology proposed by Oliver and Alfonzo (2018a) to 3D seismic data assimilation. We focus on the model improvement by estimating a “total” observation error covariance matrix. Furthermore, we reduced the influence of systematic errors by including a simple analytical function in our forward model. The function is defined based on physical premises and the parameter is calibrated in the data assimilation workflow. This procedure increases the dimension of the problem. The error covariance update improved the reservoir volume characterization in all of our tests. Moreover, we show that the update provides a way to improve the determination of the residual weights in the data assimilation problem. These weights are difficult to define in practice and the results were relatively insensitive to the initial values. By using the proposed methodology, we were able to improve the reservoir volume calibration using a relatively low-resolution data. If the correlated errors were neglected, the data assimilation would lead to implausible parameter distributions
4D petroelastic modeling based on a presalt well
ARTIGO - Inglês
Assunto: Reservatórios
After their initial discovery in 2006, followed by an accumulated production of over 2 billion barrels of oil equivalent, the presalt carbonate...
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After their initial discovery in 2006, followed by an accumulated production of over 2 billion barrels of oil equivalent, the presalt carbonate reservoirs of offshore Brazil are now candidates for time-lapse seismic analysis. Therefore, we have conducted a 4D feasibility study in a Brazilian presalt reservoir well, which is composed of two types of carbonate rocks: microbialite and coquina. We evaluated two petroelastic models to obtain the acoustic impedance (AI) and shear impedance (SI) needed to estimate potential time-lapse differences (ΔAI, ΔSI, and ΔVP/VS). For this, we used the Gassmann and Xu-Payne models, in which the latter considers the pore geometry of the rock in its equations. Our analysis of both models shows that changes in pressure and saturation are very similar, and we can conclude that, despite being a carbonate, the application of Gassmann’s model is sufficient for the 4D feasibility studies conducted in the deemed reservoir because it does not require pore space geometry parameters, as does the Xu-Payne model. The analysis of the time-lapse attributes provided us with a greater comprehension of the 4D scenarios modeled, some of which presented detectability of changes in the microbialite and coquina
A comparative study to accelerate field development plan optimization
ARTIGO - Inglês
Assunto: Artigo original
Abstract: Rigorous and continual advancement in the computational domain have drastically reduced the time consumed for simulations. Despite this, the...
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Abstract: Rigorous and continual advancement in the computational domain have drastically reduced the time consumed for simulations. Despite this, the heterogeneity and requirement to use compositional models, among constraints such as field size, can still thwart the optimization of the field development plan (FDP) in terms of time spent. To address this, we proposed and compared different techniques to underscore how to optimize FDP efficiently under uncertainty using an example of a giant benchmark field. We compared four workflows to improve the efficiency of the optimization process. Method 1 uses a full-field model (FFM) approach with an intelligent selection process to eliminate the poorest FDPs. As it is usual to divide a field into sectors for risk-aversion and strategic purposes, Method 2 uses an isolated-sector approach to reduce average simulation time. Method 3 employs the FFM approach to perform the optimization using only the monetary value of the partial life of the field. Method 4 uses a cluster-based search space reduction technique for a predictive analysis from the technical results obtained with partial simulations, which are similar to Method 3. To ensure good decisions, the optimized FDP was always implemented in the FFM with complete field-life at the end of all methods. All proposed workflows are promising in terms of efficiency, acknowledge the entire envelope of uncertainty, and consider multiple scenarios to improve the chances of success of the optimized FDP in the real field. Aside from obtaining good results when compared to traditional methods, we also saved 80–93% of the computational time with these methods. Thus, one can reduce exorbitant costs and delays in performing the FDP optimization. As anticipated, we observed a generic trade-off between decreasing computational time and increasing field objective function. Despite this, using a new algorithm with predictive analytics in Method 4 produced the best improvement within the shortest timespan, which demonstrates that one can use shorter-term data to understand a field's non-linear response. Numerous authors have already presented various algorithms to optimize an FDP. Despite the existing computational capabilities, these algorithms are still inept at developing a field with time-consuming simulation models. Unlike previous studies, this work presents practical solutions to assist field development, considering probabilistic scenarios to capture associated uncertainty. We also discuss the advantages and disadvantages of the methods to establish their application in different situations
ARTIGO - Inglês
Assunto: Artigo de evento
Abstract: Net Present Value (NPV) measures whether an investment will be profitable within a given period of time. In oil production planning, it...
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Abstract: Net Present Value (NPV) measures whether an investment will be profitable within a given period of time. In oil production planning, it consists of an important indicator to evaluate different production strategies. The NPV estimate is calculated on the basis of the production data which are generally obtained by means of numerical simulations, which consider the strategy details and the physical reservoir model. However, the simulator demands high computational resource, which may take hours or days of processing time to evaluate a single strategy, depending on the size of the reservoir model. To speed up this process a simpler model, referred to as a surrogate model, can be used to approximate the simulator output. In this work, we hypothesize that it is possible to predict the NPV using only wells arrangement data as predictors. Moreover, we present a comparison among six machine learning algorithms used as a surrogate model: Linear Regression, K-Nearest Neighbor, Multi-Layer Perceptron, Kernel Ridge Regression, Support Vector Regression, and Gradient Tree Boosting. Results confirm it is viable to predict NPV from wells arrangement data, in special with kernel-based methods
DOI: https://doi.org/10.1109/ijcnn.2019.8851708
Texto completo: https://ieeexplore.ieee.org/document/8851708
ARTIGO - Inglês
Assunto: Algoritmos genéticos
Abstract: Net Present Value (NPV) is an important indicator to guide investment decisions. In oil production planning, NPV is employed to evaluate and...
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Abstract: Net Present Value (NPV) is an important indicator to guide investment decisions. In oil production planning, NPV is employed to evaluate and select among different production strategies. However, NPV estimation requires computational costly numerical simulations. So, evaluating as many production strategies as is desirable may be prohibitive. Therefore, one can only evaluate a small part of the search space, decreasing the chance of finding a near-optimal production strategy. To speed up the searching process, a much faster, but error-prone, surrogate model is used to approximate the simulator output. Data-driven surrogate modeling depends on both: 1) building a simple model to reproduce the quality of a high-fidelity model, while 2) considering a large volume of data to build it. In this work, we address the well placement optimization task by considering a binary data representation, indicating the presence or absence of a given well in a production strategy. We show the possibility of predicting the NPV from binary data, thus reducing data dimension and model complexity. Specifically, we compare six machine learning regression algorithms to predict the NPV. The simulations conducted in a benchmark case, based on a real field, showed that some regression algorithms can be used as a surrogate model to the simulator to efficiently perform well placement optimization considering binary data. The best results were obtained with Multi-Layer Perceptron, whose estimations covered a wide range of NPV with a small and constant error
A continuous learning algorithm for history matching
ARTIGO - Inglês
Assunto: Inteligência artificial
Abstract: History matching is a classical petroleum reservoir engineering data assimilation process whereby a reservoir model is calibrated to...
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Abstract: History matching is a classical petroleum reservoir engineering data assimilation process whereby a reservoir model is calibrated to reproduce the behavior of a real reservoir yielding more reliable models for reservoir management, reservoir performance forecast and field development decisions. In this paper, we introduce a continuous learning-from-data algorithm for history-matching problems that generates solutions using the patterns of input attributes identified in the k-best solutions for each variable involved in the process. The proposed algorithm consists of a two-staged optimization strategy, in which each stage handles different types of reservoir uncertain attributes. The proposed learning approach continuously evaluates the data of all-available models and supports the strategic choice of input patterns that can be used in the generation of different and eventually better history-matched models. We apply the proposed algorithm to the UNISIM-I-H benchmark case, a complex synthetic reservoir model based on Namorado field, Campos basin, Brazil. The results outperform the ones from related work for the same benchmark, indicating the efficiency and effectiveness of the proposed strategy towards improving the history-matching quality of an initial set of solutions, with a lower simulation footprint
ARTIGO - Português
Assunto: Artigo original
Abstract: The Barra Velha Formation encompasses the most important hydrocarbon reservoirs of the Pre-salt section of the Santos Basin, SE Brazil, and...
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Abstract: The Barra Velha Formation encompasses the most important hydrocarbon reservoirs of the Pre-salt section of the Santos Basin, SE Brazil, and its lacustrine carbonates have drawn much attention in the past decade due to their sedimentological complexity and overall heterogeneity. Among the main challenges in the characterization of such rocks are the great depth of the reservoirs and the difficulty to characterize geological features in non-cored intervals. Additionally, the relationship between facies and petrophysical properties is difficult to establish with conventional well log evaluation routines. In this study, a continuous ultrasonic borehole image log (UBI) is integrated with conventional logs, nuclear magnetic resonance logs (NMR), and core samples to support the detailed geological interpretation and petrophysical evaluation of the lacustrine carbonates of the Barra Velha Formation (wholly Aptian). The systematic interpretation of the UBI log resulted in the identification of acoustic image log facies (AIFs), which were then translated into lithofacies. The entire studied interval was divided into eight zones, characterized by particular facies associations and petrophysical properties. Each zone was interpreted to have formed in depositional environments ranging from deep subaqueous to emergent conditions. A general shallowing and cleaning upward pattern was identified for the Barra Velha Formation, with a main reservoir zone associated with intermediate-to-shallow subaqueous conditions. This work aimed to explore the applications and limitations of the acoustic image log in the context of the Brazilian pre-salt and establish the relationship between image log facies and reservoir properties retrieved from NMR data
A CRS-based heterogeneity attribute
ARTIGO - Inglês
Assunto: Heterogeneidade
Abstract: An attribute describing heterogeneity is proposed based on the diffracted-wave contribution. In areas of complex geology the amount of...
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Abstract: An attribute describing heterogeneity is proposed based on the diffracted-wave contribution. In areas of complex geology the amount of diffracted energy will increase relative the specular reflections. By use of the modified CRS technique, a reliable measure of the diffractions can be obtained. Proper scaling with the output from a conventional CRS stack gives a normalized measure of the complexity of the geology. The new attribute has possible use both in seismic texture analysis and as a weight factor employed to combine CRS based reflection- and diffraction-enhanced stacks. The potential of the heterogeneity attribute is demonstrated using seismic data from offshore Brazil
ARTIGO - Inglês
Assunto: Artigo original
Abstract: Time-lapse seismic (four-dimensional seismic) data play a preeminent role in closed-loop reservoir management by providing a full-field...
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Abstract: Time-lapse seismic (four-dimensional seismic) data play a preeminent role in closed-loop reservoir management by providing a full-field image of dynamic reservoir behaviour during production. Nonetheless, the multidisciplinary nature of four-dimensional closed-loop approaches demands more quantitative and fast methods to integrate rock physics models, reservoir flow simulation models and four-dimensional seismic analysis. In this work, we tackle this time-consuming and expensive process and develop a data-driven quantitative approach to leverage the inherent physics between four-dimensional seismic and reservoir property changes. We propose an inversion flow method using machine learning strategies to estimate changes in reservoir properties directly from a fast-derived four-dimensional seismic attribute. This study was carried out in a Brazilian deep-water field where production started in 2013 with 3 years of production and injection history. For this reservoir, the estimation of fluid saturation maps is a critical objective to assist engineers with data assimilation procedures. We also generated millions of training data samples using 200 simulation models from the field mentioned above (before history matching) to highlight the benefits of restricting training samples to proper fluid flow consistent combinations. Results demonstrate high prediction accuracy for the targeted reservoir property changes. Additionally, it provides insights for the detection of sweet spots and positioning of infill wells. We significantly simplify the four-dimensional seismic integration process, allowing initial engagements of reservoir engineers with decision-making processes and data assimilation applications
A methodology to calibrate water saturation estimated from 4D seismic data
ARTIGO - Inglês
Assunto: Calibração
Time-lapse seismic data can be used to estimate saturation changes within a reservoir, which is valuable information for reservoir management as it...
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Time-lapse seismic data can be used to estimate saturation changes within a reservoir, which is valuable information for reservoir management as it plays an important role in updating reservoir simulation models. The process of updating reservoir properties, history matching, can incorporate estimated saturation changes qualitatively or quantitatively. For quantitative approaches, reliable information from 4D seismic data is important. This work proposes a methodology to calibrate the volume of water in the estimated saturation maps, as these maps can be wrongly estimated due to problems with seismic signals (such as noise, errors associated with data processing and resolution issues). The idea is to condition the 4D seismic data to known information provided by engineering, in this case the known amount of injected and produced water in the field. The application of the proposed methodology in an inversion process (previously published) that estimates saturation from 4D seismic data is presented, followed by a discussion concerning the use of such data in a history matching process. The methodology is applied to a synthetic dataset to validate the results, the main of which are: (1) reduction of the effects of noise and errors in the estimated saturation, yielding more reliable data to be used quantitatively or qualitatively and (2) an improvement in the properties update after using this data in a history matching procedure
A modified elasto-viscoplastic thixotropic model for two commercial gelled waxy crude oils
ARTIGO - Inglês
Assunto: Óleos minerais
A severe problem to flow assurance occurs when subsea flowlines become blocked with gelled waxy crudes. To design proper surface pump facilities, it...
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A severe problem to flow assurance occurs when subsea flowlines become blocked with gelled waxy crudes. To design proper surface pump facilities, it is essential to know the minimum pressure required to restart the flow. Simulating and predicting this minimum pressure require the understanding of several physical phenomena, including compressibility, shrinkage, and rheological behavior. This study aims to characterize and simulate the rheological behavior of two commercial waxy crude oils. Based on its survey of the literature, we select the de Souza Mendes and Thompson (2013) model to fit the oil’s behavior and then conduct, using a rheometer, a considerable number of experiments with the selected oils. To verify the solution of our algorithm, we compared our theoretical solutions with some results of the literature. When comparing the simulation with experiments, the model was unable to predict the data perfectly; hence, we propose a modified version without changing the physical meaning of the equations, to improve its predictions. Once any of the empirical parameters were able to influence the elastic behavior in such a way that the shear stress decreased with time, the structural elastic modulus function was modified, which means that the relation of the structure parameter and the storage modulus was modified. One of the interesting results of the analysis is when relating the storage modulus and a new parameter added in the modification, a value was found to be, regardless of the aging time or the oil used, constant
Analysis of inflow-control-valves shutdown effects in well production and economics
ARTIGO - Inglês
Assunto: Gasolina
Inflow control valves (ICV) can be used to add flexibility to petroleum production operation. They can be used as a reaction of an undesired event...
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Inflow control valves (ICV) can be used to add flexibility to petroleum production operation. They can be used as a reaction of an undesired event (reactive control), like water breakthrough, but they can also be used to prevent or to delay these events (proactive control). Proactive control can be an efficient form to control intelligent wells. However, the benefits of proactive control require an appropriate study to avoid premature decisions that lead to suboptimal results. This paper focuses on the evaluation of the effects caused by ICV operation and its impact on long term field production and cash flow, giving support to tools or equipment to apply proactive controls (use of seismic, sensors etc.). The main objective is to show when possible benefits of a proactive operation can be reached. An inverted five-spot model, representing a specific region of a reservoir, is used to verify the effects of ICV operation, with different production and injection constraints. The results show that proactive control with ICV can, in some cases, improve the performance of the field by increasing oil production and decreasing water production, however, this kind of control is not always profitable. The results also show that ICV shutdowns can significantly alter the behavior of the wells
DOI: https://doi.org/10.2118/169368-MS
Texto completo: https://www.onepetro.org/conference-paper/SPE-169368-MS
Analysis of the bounded and unbounded forms of USBM wettability index
ARTIGO - Inglês
Assunto: Artigo original
Abstract: Understanding wettability is important in many processes where porous media and fluids are in contact. The U.S. Bureau of Mines (USBM) is...
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Abstract: Understanding wettability is important in many processes where porous media and fluids are in contact. The U.S. Bureau of Mines (USBM) is one of the industry standard techniques for measuring wettability. This index is calculated as U S B M = l g ( A 1 A 2 ) , where A 1 and A 2 are the areas under capillary pressure curves of oil-drive and water-drive processes, respectively. Usually, the USBM is mistakenly assumed to vary over the range of -1 to 1 and compared with other indices. In this study we indicate that the lower and upper bounds of this index are not fully known in practice. As a result, comparison between USBM and other indices may cause erroneous interpretations due to dissimilar ranges of variation. In addition, even during examining the USBM of a sample it may not be possible to accurately interpret its wettability. We highlight the bounded form of the USBM index (denoted as U S B M * = A 1 - A 2 A 1 + A 2 ), which varies over the range of -1 to 1, and suggest that it should replace the traditional form of USBM index. Twenty limestone core-plugs were collected from Asmari and Fahlian formations in two Iranian fields. These samples were used for performing primary imbibition relative permeability measurements, as well as primary imbibition and secondary drainage capillary pressure tests. These experiments are used to show the differences between USBM and USBM* in comparative studies and compare them against other indices of Amott-Harvey, Lak and modified Lak
ARTIGO - Inglês
Assunto: Escoamento multifásico
In integrated models, reservoirs and production systems have many variables that make problems difficult to solve. This work complements a suggested...
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In integrated models, reservoirs and production systems have many variables that make problems difficult to solve. This work complements a suggested methodology to reduce the number of design and operational parameters to obtain a good performance of the field production. We evaluated and validated the applied methodology for a different benchmark case, checking possibilities of extension to other cases. The case study considered a carbonate reservoir benchmark similar to a Brazilian pre-salt case. We evaluated the combination of several parameters through a decoupled sensitivity analysis for production system, selecting those which promoted greater impacts on production to be evaluated and selected in an integrated sensitivity analysis leading to an improvement in the field productivity and net present value. Sensitivity analyses were relevant to reduce the number of variables for robust optimisation problems through the reduction of the search space, favouring the decrease of the computational time and discontinuity problems
Analysis of time-lapse seismic and production data for reservoir model classification and assessment
ARTIGO - Inglês
Assunto: Reservatórios
The heterogeneous distribution of reservoir properties is one of the most important uncertainties in static and dynamic reservoir modelling....
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The heterogeneous distribution of reservoir properties is one of the most important uncertainties in static and dynamic reservoir modelling. Petrophysical properties are usually interpolated within reservoir models from sparse well-log data, which can lead to highly uncertain estimates at inter-well locations that directly affect the reliability of fluid-flow model predictions of reservoir behaviour. To address this issue, one approach is to build an ensemble of equiprobable models that combine different geostatistical realisations of reservoir properties that ideally span the range of potential outcomes. While this process captures the impact of reservoir property distributions on the model response, a major challenge is classifying the subset of models in the ensemble best representing reservoir fluid-flow behaviour. Time-lapse seismic attributes are useful for reducing such uncertainties, since they image fluid-movement trends that provide insights regarding fault locations and distribution of reservoir properties, such as permeability and porosity. Accordingly, we introduce a methodology combining 4D seismic amplitude attributes and reservoir production data to classify fluid-flow models. This classification is based on applying thresholds for independent seismic and production objective functions. We develop and apply a new formulation of local dissimilarity maps to quantify differences between observed and modelled 4D seismic amplitudes. We test our methodology on the benchmark case UNISIM-I developed from observations from the Namorado Field, Campos Basin, Brazil. By comparing injection and production rates in relation to 4D seismic amplitude trends within each region, we identify nine models out of an ensemble of 100 that are judged optimal via the required seismic and production objective function thresholds. Thus, we obtain an improved quantitative evaluation of the impact of reservoir production on the 4D seismic signal. Combining seismic and production data offers interpretation scenarios that automatically identify realistic fluid-flow models that would be helpful for updating reservoir properties
ARTIGO - Inglês
Assunto: Artigo original
Abstract: Two-phase flow in pipes can generate different geometric distribution of phases depending on the flow conditions, called flow patterns. The...
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Abstract: Two-phase flow in pipes can generate different geometric distribution of phases depending on the flow conditions, called flow patterns. The identification of such flow patterns is fundamental for designing operational conditions of complex oil and gas industrial plants for production and transport of such fluids by pipes. Amongst them, the intermittent flow is the most relevant for industrial applications as it can lead to increased vibration levels with catastrophic failures, and also to several flow assurance problems. In this flow condition, an elongated gas bubble travels along the pipe followed by a liquid slug with or without dispersed bubbles. The two-phase flow induced vibration research have been mostly focused on the modal approaches, which can be very sensitive to boundary and operational conditions thus limiting its practical applicability in field conditions. On the other hand, wave-based approaches can overcome this limitation since they are based on local properties. In this paper, bending wave propagation in horizontal ducts conveying intermittent flow is investigated. A periodic unit cell model is assumed to describe the intermittent flow and the mass density along the duct is thus given by a Fourier series, representing space and time fluctuations. Subsequently, the wave dispersion characteristics can be analytically calculated for a duct in bending conveying intermittent flow, assuming small mixture velocity when compared to the bending waves. The periodic flow creates a periodic dispersion diagram which is distorted by the flow velocity. This effect accounts for the asymmetry in the wave propagating along and against the flow direction. The wave dispersion curves are experimentally estimated for typical intermittent flow conditions and it is shown that they can be approximated by equivalent homogeneous fluid. In addition, this curve is sensitive to the gas fraction of the two-phase fluid. The presented approach introduces a new perspective on two-phase flow induced vibrations of pipes and opens the way for better understanding the effect of the periodic two-phase flow in the dynamic behaviour of pipes
An artificial intelligence method for improving upscaling in complex reservoirs
ARTIGO - Inglês
Assunto: Artigo original
Abstract: The upscaling of geological properties is a fundamental requirement to construct a suitable simulation model since the geological model...
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Abstract: The upscaling of geological properties is a fundamental requirement to construct a suitable simulation model since the geological model typically contains millions of cells, which makes it computationally difficult to simulate it on such a scale. The process consists of a scale transfer that adapts the petrophysical properties of a high-resolution grid to a coarser grid. Nevertheless, this is not a trivial operation, especially for absolute permeability, which is a non-additive property. One of the most reliable methods is to perform a flow simulation on fine-scale cells that correspond to the coarse block and derive the single permeability value that reflects the same flow value. Still, this is a very time-consuming method and depends on the imposed boundary conditions. This work aims to take advantage of recent advances in artificial intelligence to produce results with similar or better quality of flow-based methods, and more adaptive. It handles models with multiple geological realizations by employing machine learning to capture patterns from a subset of scenarios and use it to generalize for all others. The methodology is divided into two stages — local and global. In the first one, a deep neural network is trained with a fraction of geological realizations using the flow-based results as a reference. In the second stage, clustering analysis is employed along with a neural network optimization to learn an adjustment procedure for the coarse simulation model concerning the cumulative field production predicted by the fine model simulation. Afterward, the trained network performs the upscaling of remaining realizations, but more efficiently in terms of computational time and providing better output in terms of production and injection. The method was applied to a benchmark model and the experimental results demonstrate that the local technique was capable of reproducing very similar values to the flow-based upscaling using only one scenario in training and at the global stage the coarse model was improved even further matching the field oil production forecast of the fine model. Different scenarios were used for training and testing and the results were consistent showing no bias towards a specific configuration and capability of generalization to different scenarios. Ultimately, the proposed artificial intelligence approach performed an accurate upscaling, surpassing the reference approach with forecast production similar to the fine model, and also fast to compute when considering multiple geological realizations, since it reduces the required numerical simulations to a fraction of the total
A new approach to measure wettability by relative permeability measurements
ARTIGO - Inglês
Assunto: Artigo original
Abstract: Wettability is a key factor controlling the flow of fluids, solutes, heat and electrical current in porous media, and therefore it is...
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Abstract: Wettability is a key factor controlling the flow of fluids, solutes, heat and electrical current in porous media, and therefore it is important in studies of various processes including CO2 storage, secondary and tertiary oil recovery, as well as the displacement of water and nonaqueous phase liquid (NAPL). Although Amott-Harvey and USBM are conventional industry-standard techniques for measuring average wettability, they have some limitations. In this paper, we show that, in a plot of the relative permeability of a fluid, the area below the curve is closely related to the wettability. By using the areas below the water and oil relative permeability curves, we derive a new wettability index (called modified Lak). To demonstrate the applicability of this new index and testing other indices, we performed primary imbibition relative permeability, and primary imbibition and secondary drainage capillary pressure measurements on twenty carbonate reservoir samples. In general, all indices predicted oil-wet character of the tested rocks. USBM was associated with the broadest range of variation, whereas the new index corresponded to the smallest range of variation. Amott-Harvey and Lak, however, fell between USBM and the new index, with fairly similar ranges of variation. In addition, we report the correlations between different indices, and the change of wettability indices vs. reservoir depth. Advantages and limitations of different wettability indices are also discussed. Since each wettability index has some limitations in revealing the true state of wettability, none of these indices can be considered as an absolute measurement. Therefore, different indices should be regarded as complementary to each other, and determination of wettability should not be limited to only one method
ARTIGO - Inglês
Assunto: Geologia - Métodos estatísticos
To maintain geological consistency, it is necessary to carry out the history matching process integrated to the geostatistical modeling. However, this...
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To maintain geological consistency, it is necessary to carry out the history matching process integrated to the geostatistical modeling. However, this integration leads to a complex optimization problem because the relationship between the input and output variables can be highly nonlinear. The purpose of this paper is to present a framework to integrate the history matching of production and seismic-derived dynamic data through a genetic algorithm with adaptive bounds. A new procedure is proposed to reduce the range of the parameters during the optimization process. The methodology was applied to a synthetic reservoir model with structural and petrophysical properties similar to a real reservoir and the results showed that it is possible to apply genetic algorithm in the integration of history matching and geostatistical modeling with feasible computational effort in terms of number of flow simulations
ARTIGO - Inglês
Assunto: Artigo original
Abstract: Determining reservoir quality is vital in order to efficiently produce hydrocarbon and/or inject fluids for secondary/tertiary recovery and...
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Abstract: Determining reservoir quality is vital in order to efficiently produce hydrocarbon and/or inject fluids for secondary/tertiary recovery and carbon sequestration. In this study, we introduce a new approach and present dynamic reservoir quality index (DRQI). A high-quality reservoir would have high displacement (recovery) rate and displaceable (recoverable) saturation of oil. A modified true effective mobility (TEM) function is developed representing displacement rate of oil by an injected fluid (e.g., water or CO2). DRQI is defined as the area under modified TEM curve of oil and includes the well-known reservoir quality index (RQI) as its special case. A large dataset composed of 220 water displacing oil relative permeability experiments, conducted on limestone and dolomite rocks from three Iranian carbonate reservoirs, was used to investigate the potential relationships between DRQI and other reservoir characteristics (e.g., irreducible water saturation, bulk irreducible water, maximum movable oil saturation, and bulk maximum movable oil) as well as quality indicators of RQI, flow zone indicator (FZI), and Winland r35. Results showed that irreducible water saturation and maximum movable oil saturation as well as their bulk variants may not be appropriate for characterizing multiphase quality of reservoirs. Furthermore, the frequently-used single-phase rock quality indicators RQI, FZI, and Winland r35 were not found to be very accurate in characterization of dynamic reservoir quality. DRQI can be used in reservoir simulation studies as a criterion for defining quality maps, and in petrophysical tasks for rock typing and comparing between dynamic qualities (in terms of displacement rate and displaceable saturation of oil) of rock samples
ARTIGO - Inglês
Assunto: Artigo original
Abstract: During data assimilation (history matching), wells are normally controlled by observed rates over the history period, typically liquid or...
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Abstract: During data assimilation (history matching), wells are normally controlled by observed rates over the history period, typically liquid or oil rate for producer and gas or water rate for injectors. The well rates are imposed as target to be honored by the simulator. To perform production forecasts (immediately after the history period) wells control (operational conditions) must be changed to the forecast mode where wells are typically controlled by pressure: bottom-hole pressure (BHP) or well-head pressure. Especially for off-shore fields, group controls (that represent platform limits) should also be defined. The target constraint imposed over the history period may hide productivity and injectivity issues that arise in the beginning of the forecast causing fluctuations in the transition from history to prediction. Even when the BHP curves are well matched (within a tolerance), this problem occurs for most cases. These fluctuations may impair the use of simulation models especially for short-term forecast. Reservoir properties, such as absolute permeability and relative permeability, and well parameters used to adjust the well index, act at the same time in the productivity index (PI), making it more difficult to match all data simultaneously (rates, pressure and well productivity) in a probabilistic history matching approach. This paper addresses this intrinsic complexity by separating the process into two stages: the first one consists of the data assimilation process focused on well rates and pressure matching. The second stage consists of the well productivity calibration considering each model (selected from the first stage) separately, which permits to isolate the other effects that change the well productivity over time, such as fluid mobility, and also the well-block permeabilities, that affect the well index (the static part of the well productivity). When the model is fixed, the effect of the well productivity variation on the flow rate variation is linear, making it much easier the PI calibration. The proposed approach was successfully applied to a real field from Campos basin (Brazil), a deep-water heterogeneous turbiditic reservoir containing heavy oil at the initial pressure. The main contribution of this paper is to increase the simulation models reliability for production forecast, especially for short-term forecasts
An experimental investigation on phase behavior of a light oil and CO2
ARTIGO - Inglês
Assunto: Petróleo
The current oil frontier in Brazil is located in Santos and Campos Basin, where huge oil accumulations have been identified. Well tests have shown...
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Resumo
The current oil frontier in Brazil is located in Santos and Campos Basin, where huge oil accumulations have been identified. Well tests have shown high pressures and high carbon dioxide concentration in these reservoirs. The characterization of the fluids existing in the reservoir rock is a key task for the better exploitation of the hydrocarbons. The objective of the paper is to present the results of an experimental PVT analysis of the oils found in the Brazilian pre-salt reserves in the region of Campos Basin using the same reservoir conditions of temperature and pressure. Dead oil and synthetic gas were recombined in laboratory to obtain the original live oil, which originally had 17.84% molar of CO2. Relevant data were collected and they are reported for oil and gas composition, formation volume factors, densities and viscosities at different pressures. A swelling test was also carried out through successive additions of carbon dioxide to the live oil from its original concentration up to 60.53% molar
ARTIGO - Inglês
Assunto: Artigo de evento