Estudo de modelos composicionais de óleo na injeção contínua de vapor

The objective of the thermal recovery is to heat the resevoir and the oil in it to increase its recovery. In the Potiguar river basin there are located several heavy oil reservoirs whose primary recovery energy provides us with a little oil flow, which makes these reservoirs great candidates for application of a method of recovery advanced of the oil, especially the thermal. The steam injection can occur on a cyclical or continuous manner. The continuous steam injection occurs through injection wells, which in its vicinity form a zone of steam that expands itself, having as a consequence the displace of the oil with viscosity and mobility improved towards the producing wells. Another possible mechanism of displacement of oil in reservoirs subjected to continuous injection of steam is the distillation of oil by steam, which at high temperatures; their lighter fractions can be vaporized by changing the composition of the oil produced, of the oil residual or to shatter in the amount of oil produced. In this context, this paper aims to study the influence of compositional models in the continuous injection of steam through in the analysis of some parameters such as flow injection steam and temperature of injection. Were made various leading comparative analysis taking the various models of fluid, varying from a good elementary, with 03 pseudocomponents to a modeling of fluids with increasing numbers of pseudocomponents. A commercial numerical simulator was used for the study from a homogeneous reservoir model with similar features to those found in northeastern Brazil. Some conclusions as the increasing of the simulation time with increasing number of pseudocomponents, the significant influence of flow injection on cumulative production of oil and little influence of the number of pseudocomponents in the flows and cumulative production of oil were found

Estudo do processo de drenagem gravitacional do óleo assistido com injeção de vapor e solvente

Como os recursos de hidrocarbonetos convencionais estão se esgotando, a crescente demanda mundial por energia impulsiona a indústria do petróleo para desenvolver mais reservatórios não convencionais. Os recursos mundiais de betume e óleo pesado são estimados em 5,6 trilhões de barris, dos quais 80% estão localizados na Venezuela, Canadá e EUA. Um dos métodos para explorar estes hidrocarbonetos é o processo de drenagem gravitacional assistido com injeção de vapor e solvente (ES-SAGD Expanding Solvent Steam Assisted Gravity Drainage). Neste processo são utilizados dois poços horizontais paralelos e situados verticalmente um acima do outro, um produtor na base do reservatório e um injetor de vapor e solvente no topo do reservatório. Este processo é composto por um método térmico (injeção de vapor) e um método miscível (injeção de solvente) com a finalidade de causar a redução das tensões interfaciais e da viscosidade do óleo ou betume. O objetivo deste estudo é analisar a sensibilidade de alguns parâmetros operacionais, tais como: tipo de solvente injetado, qualidade do vapor, distância vertical entre os poços, porcentagem de solvente injetado e vazão de injeção de vapor sobre o fator de recuperação para 5, 10 e 15 anos. Os estudos foram realizados através de simulações concretizadas no módulo STARS (Steam Thermal, and Advanced Processes Reservoir Simulator) do programa da CMG (Computer Modelling Group), versão 2010.10, onde as interações entre os parâmetros operacionais, estudados em um modelo homogêneo com características de reservatórios semelhantes aos encontrados no Nordeste Brasileiro, foram observadas. Os resultados obtidos neste estudo mostraram que os melhores fatores de recuperação ocorreram para níveis máximos do percentual de solvente injetado e da distância vertical entre os poços. Observou-se também que o processo será rentável dependendo do tipo e do valor do solvente injetado

Efeito da perda de carga e calor no poço injetor no processo de drenagem gravitacional assistido com vapor e solvente

Nowadays, most of the hydrocarbon reserves in the world are in the form of heavy oil, ultra - heavy or bitumen. For the extraction and production of this resource is required to implement new technologies. One of the promising processes for the recovery of this oil is the Expanding Solvent Steam Assisted Gravity Drainage (ES-SAGD) which uses two parallel horizontal wells, where the injection well is situated vertically above the production well. The completion of the process occurs upon injection of a hydrocarbon additive at low concentration in conjunction with steam. The steam adds heat to reduce the viscosity of the oil and solvent aids in reducing the interfacial tension between oil/ solvent. The main force acting in this process is the gravitational and the heat transfer takes place by conduction, convection and latent heat of steam. In this study was used the discretized wellbore model, where the well is discretized in the same way that the reservoir and each section of the well treated as a block of grid, with interblock connection with the reservoir. This study aims to analyze the influence of the pressure drop and heat along the injection well in the ES-SAGD process. The model used for the study is a homogeneous reservoir, semi synthetic with characteristics of the Brazilian Northeast and numerical simulations were performed using the STARS thermal simulator from CMG (Computer Modelling Group). The operational parameters analyzed were: percentage of solvent injected, the flow of steam injection, vertical distance between the wells and steam quality. All of them were significant in oil recovery factor positively influencing this. The results showed that, for all cases analyzed, the model considers the pressure drop has cumulative production of oil below its respective model that disregards such loss. This difference is more pronounced the lower the value of the flow of steam injection

Análise de viabilidade de injeção de fluidos alternativos ao vapor em reservatórios de óleo pesado

Many of hydrocarbon reserves existing in the world are formed by heavy oils (°API between 10 and 20). Moreover, several heavy oil fields are mature and, thus, offer great challenges for oil industry. Among the thermal methods used to recover these resources, steamflooding has been the main economically viable alternative. Latent heat carried by steam heats the reservoir, reducing oil viscosity and facilitating the production. This method has many variations and has been studied both theoretically and experimentally (in pilot projects and in full field applications). In order to increase oil recovery and reduce steam injection costs, the injection of alternative fluid has been used on three main ways: alternately, co-injected with steam and after steam injection interruption. The main objective of these injection systems is to reduce the amount of heat supplied to the reservoir, using cheaper fluids and maintaining the same oil production levels. This works discusses the use of carbon dioxide, nitrogen, methane and water as an alternative fluid to the steam. The analyzed parameters were oil recoveries and net cumulative oil productions. The reservoir simulation model corresponds to an oil reservoir of 100 m x 100 m x 28 m size, on a Cartesian coordinates system (x, y and z directions). It is a semi synthetic model with some reservoir data similar to those found in Brazilian Potiguar Basin. All studied cases were done using the simulator STARS from CMG (Computer Modelling Group, version 2009.10). It was found that waterflood after steam injection interruption achieved the highest net cumulative oil compared to other fluids injection. Moreover, it was observed that steam and alternative fluids, co-injected and alternately, did not present increase on profitability project compared with steamflooding

Análise paramétrica da injeção de vapor e solvente em reservatórios de óleo pesado

A significant fraction of the hydrocarbon reserves in the world is formed by heavy oils. From the thermal methods used to recovery these resources, Steamflooding has been one of the main economically viable alternatives. In Brazil, this technology is widely used by Petrobras in Northeast fields. Latent heat carried by steam heats the oil in the reservoir, reducing its viscosity and facilitating the production. In the last years, an alternative more and more used by the oil industry to increase the efficiency of this mechanism has been the addition of solvents. When co-injected with steam, the vaporized solvent condenses in the cooler regions of the reservoir and mixes with the oil, creating a low viscosity zone between the steam and the heavy oil. The mobility of the displaced fluid is then improved, resulting in an increase of oil recovery. To better understand this improved oil recovery method and investigate its applicability in reservoirs with properties similar to those found in Potiguar Basin, a numerical study was done to analyze the influence of some operational parameters (steam injection rate, injected solvent volume and solvent type) on oil recovery. Simulations were performed in STARS ("Steam, Thermal, and Advanced Processes Reservoir Simulator"), a CMG ("Computer Modelling Group") program, version 2009.10. It was found that solvents addition to the injected steam not only anticipated the heated oil bank arrival to the producer well, but also increased the oil recovery. Lower cold water equivalent volumes were required to achieve the same oil recoveries from the models that injected only steam. Furthermore, much of the injected solvent was produced with the oil from the reservoir

Estudo do acoplamento do poço injetor nas simulações de injeção cíclica de vapor

Steam injection is a method usually applied to very viscous oils and consists of injecting heat to reduce the viscosity and, therefore, increase the oil mobility, improving the oil production. For designing a steam injection project it is necessary to have a reservoir simulation in order to define the various parameters necessary for an efficient heat reservoir management, and with this, improve the recovery factor of the reservoir. The purpose of this work is to show the influence of the coupled wellbore/reservoir on the thermal simulation of reservoirs under cyclic steam stimulation. In this study, the methodology used in the solution of the problem involved the development of a wellbore model for the integration of steam flow model in injection wellbores, VapMec, and a blackoil reservoir model for the injection of cyclic steam in oil reservoirs. Thus, case studies were developed for shallow and deep reservoirs, whereas the usual configurations of injector well existing in the oil industry, i.e., conventional tubing without packer, conventional tubing with packer and insulated tubing with packer. A comparative study of the injection and production parameters was performed, always considering the same operational conditions, for the two simulation models, non-coupled and a coupled model. It was observed that the results are very similar for the specified well injection rate, whereas significant differences for the specified well pressure. Finally, on the basis of computational experiments, it was concluded that the influence of the coupled wellbore/reservoir in thermal simulations using cyclic steam injection as an enhanced oil recovery method is greater for the specified well pressure, while for the specified well injection rate, the steam flow model for the injector well and the reservoir may be simulated in a non- coupled way

Modelagem de dados de falhas de equipamentos de sub-superfície em poços de petróleo da Bacia Potiguar

This master´s thesis presents a reliability study conducted among onshore oil fields in the Potiguar Basin (RN/CE) of Petrobras company, Brazil. The main study objective was to build a regression model to predict the risk of failures that impede production wells to function properly using the information of explanatory variables related to wells such as the elevation method, the amount of water produced in the well (BSW), the ratio gas-oil (RGO), the depth of the production bomb, the operational unit of the oil field, among others. The study was based on a retrospective sample of 603 oil columns from all that were functioning between 2000 and 2006. Statistical hypothesis tests under a Weibull regression model fitted to the failure data allowed the selection of some significant predictors in the set considered to explain the first failure time in the wells

Sistema de detecção e isolamento de falhas em sistemas dinâmicos baseado em identificação paramétrica

The present research aims at contributing to the area of detection and diagnosis of failure through the proposal of a new system architecture of detection and isolation of failures (FDI, Fault Detection and Isolation). The proposed architecture presents innovations related to the way the physical values monitored are linked to the FDI system and, as a consequence, the way the failures are detected, isolated and classified. A search for mathematical tools able to satisfy the objectives of the proposed architecture has pointed at the use of the Kalman Filter and its derivatives EKF (Extended Kalman Filter) and UKF (Unscented Kalman Filter). The use of the first one is efficient when the monitored process presents a linear relation among its physical values to be monitored and its out-put. The other two are proficient in case this dynamics is no-linear. After that, a short comparative of features and abilities in the context of failure detection concludes that the UFK system is a better alternative than the EKF one to compose the architecture of the FDI system proposed in case of processes of no-linear dynamics. The results shown in the end of the research refer to the linear and no-linear industrial processes. The efficiency of the proposed architecture may be observed since it has been applied to simulated and real processes. To conclude, the contributions of this thesis are found in the end of the text

Detecção e isolamento de falhas em sistemas dinâmicos baseados em redes neurais

This master dissertation presents the development of a fault detection and isolation system based in neural network. The system is composed of two parts: an identification subsystem and a classification subsystem. Both of the subsystems use neural network techniques with multilayer perceptron training algorithm. Two approaches for identifica-tion stage were analyzed. The fault classifier uses only residue signals from the identification subsystem. To validate the proposal we have done simulation and real experiments in a level system with two water reservoirs. Several faults were generated above this plant and the proposed fault detection system presented very acceptable behavior. In the end of this work we highlight the main difficulties found in real tests that do not exist when it works only with simulation environments

Proposta de integração das redes de comunicação da COSERN como uma solução de contigêncvia em caso de falhas nos enlaces do backbone de automação

T'his dissertation proposes alternative models to allow the interconnectioin of the data communication networks of COSERN Companhia Energética do Rio Grande do Norte. These networks comprise the oorporative data network, based on TCP/IP architecture, and the automation system linking remote electric energy distribution substations to the main Operatin Centre, based on digital radio links and using the IEC 60870-5-101 protoco1s. The envisaged interconnection aims to provide automation data originated from substations with a contingent route to the Operation Center, in moments of failure or maintenance of the digital radio links. Among the presented models, the one chosen for development consists of a computational prototype based on a standard personal computer, working under LINUX operational system and running na application, developesd in C language, wich functions as a Gateway between the protocols of the TCP/IP stack and the IEC 60870-5-101 suite. So, it is described this model analysis, implementation and tests of functionality and performance. During the test phase it was basically verified the delay introduced by the TCP/IP network when transporting automation data, in order to guarantee that it was cionsistent with the time periods present on the automation network. Besides , additional modules are suggested to the prototype, in order to handle other issues such as security and prioriz\ation of the automation system data, whenever they are travesing the TCP/IP network. Finally, a study hás been done aiming to integrate, in more complete way, the two considered networks. It uses IP platform as a solution of convergence to the communication subsystem of na unified network, as the most recente market tendencies for supervisory and other automation systems indicate

Sistema híbrido para detecção e diagnóstico de falhas em sistemas dinâmicos

The industries are getting more and more rigorous, when security is in question, no matter is to avoid financial damages due to accidents and low productivity, or when it s related to the environment protection. It was thinking about great world accidents around the world involving aircrafts and industrial process (nuclear, petrochemical and so on) that we decided to invest in systems that could detect fault and diagnosis (FDD) them. The FDD systems can avoid eventual fault helping man on the maintenance and exchange of defective equipments. Nowadays, the issues that involve detection, isolation, diagnose and the controlling of tolerance fault are gathering strength in the academic and industrial environment. It is based on this fact, in this work, we discuss the importance of techniques that can assist in the development of systems for Fault Detection and Diagnosis (FDD) and propose a hybrid method for FDD in dynamic systems. We present a brief history to contextualize the techniques used in working environments. The detection of fault in the proposed system is based on state observers in conjunction with other statistical techniques. The principal idea is to use the observer himself, in addition to serving as an analytical redundancy, in allowing the creation of a residue. This residue is used in FDD. A signature database assists in the identification of system faults, which based on the signatures derived from trend analysis of the residue signal and its difference, performs the classification of the faults based purely on a decision tree. This FDD system is tested and validated in two plants: a simulated plant with coupled tanks and didactic plant with industrial instrumentation. All collected results of those tests will be discussed

Eosi: um modelo para desenvolvimento de sistemas embarcados tolerantes a falhas

The semiconductor technologies evolutions leads devices to be developed with higher processing capability. Thus, those components have been used widely in more fields. Many industrial environment such as: oils, mines, automotives and hospitals are frequently using those devices on theirs process. Those industries activities are direct related to environment and health safe. So, it is quite important that those systems have extra safe features yield more reliability, safe and availability. The reference model eOSI that will be presented by this work is aimed to allow the development of systems under a new view perspective which can improve and make simpler the choice of strategies for fault tolerant. As a way to validate the model na architecture FPGA-based was developed.

Aplicação de sistemas multi-classificadores no diagnóstico de falhas em motores de indução trifásicos

Equipment maintenance is the major cost factor in industrial plants, it is very important the development of fault predict techniques. Three-phase induction motors are key electrical equipments used in industrial applications mainly because presents low cost and large robustness, however, it isn t protected from other fault types such as shorted winding and broken bars. Several acquisition ways, processing and signal analysis are applied to improve its diagnosis. More efficient techniques use current sensors and its signature analysis. In this dissertation, starting of these sensors, it is to make signal analysis through Park s vector that provides a good visualization capability. Faults data acquisition is an arduous task; in this way, it is developed a methodology for data base construction. Park s transformer is applied into stationary reference for machine modeling of the machine s differential equations solution. Faults detection needs a detailed analysis of variables and its influences that becomes the diagnosis more complex. The tasks of pattern recognition allow that systems are automatically generated, based in patterns and data concepts, in the majority cases undetectable for specialists, helping decision tasks. Classifiers algorithms with diverse learning paradigms: k-Neighborhood, Neural Networks, Decision Trees and Naïves Bayes are used to patterns recognition of machines faults. Multi-classifier systems are used to improve classification errors. It inspected the algorithms homogeneous: Bagging and Boosting and heterogeneous: Vote, Stacking and Stacking C. Results present the effectiveness of constructed model to faults modeling, such as the possibility of using multi-classifiers algorithm on faults classification

Reconhecimento de padrões de falhas em motores trifásicos utilizando redes neurais

This work presents a diagnosis faults system (rotor, stator, and contamination) of three-phase induction motor through equivalent circuit parameters and using techniques patterns recognition. The technology fault diagnostics in engines are evolving and becoming increasingly important in the field of electrical machinery. The neural networks have the ability to classify non-linear relationships between signals through the patterns identification of signals related. It is carried out induction motor´s simulations through the program Matlab R & Simulink R , and produced some faults from modifications in the equivalent circuit parameters. A system is implemented with multiples classifying neural network two neural networks to receive these results and, after well-trained, to accomplish the identification of fault´s pattern

Utilização de redes neurais artificiais para detecção e diagnóstico de falhas

In a real process, all used resources, whether physical or developed in software, are subject to interruptions or operational commitments. However, in situations in which operate critical systems, any kind of problem may bring big consequences. Knowing this, this paper aims to develop a system capable to detect the presence and indicate the types of failures that may occur in a process. For implementing and testing the proposed methodology, a coupled tank system was used as a study model case. The system should be developed to generate a set of signals that notify the process operator and that may be post-processed, enabling changes in control strategy or control parameters. Due to the damage risks involved with sensors, actuators and amplifiers of the real plant, the data set of the faults will be computationally generated and the results collected from numerical simulations of the process model. The system will be composed by structures with Artificial Neural Networks, trained in offline mode using Matlab®