Asphaltene precipitation, flocculation, and deposition in the reservoir and producing wells cause serious damages to the production equipment and possible failure to develop the reservoirs. From the field production prospective, predicting asphaltene precipitation, flocculation, and deposition in the reservoir and wellbore may avoid high expenditures associated with the reservoir remediation, well intervention techniques, and field production interruption. Since asphaltene precipitation, flocculation, and deposition strongly depend on the pressure, temperature, and composition variations (e.g. phase instability due to CO2 injection), it is important to have a model that can track the asphaltene behavior during the entire production system from the injection well to the production well, which is absent in the literature. Due to economic concerns for asphaltene related problems, companies spend a lot of money to design their own asphaltene inhibition and remediation procedures. However, due to the complexity and the lack of knowledge on the asphaltene problems, these asphaltene inhibition and remediation programs are not always successful. Near-wellbore asphaltene inhibition and remediation techniques can be divided into two categories: changing operating conditions, and chemical treatment of the reservoir. Although, the field applications of these procedures are discussed in the literature, a dynamic model that can handle asphaltene inhibition and remediation in the reservoir is missing. In this dissertation, a comprehensive non-isothermal compositional reservoir simulator with the capability of modeling near-wellbore asphaltene inhibition and remediation is developed to address the effect of asphaltene deposition on the reservoir performance. This simulator has many additional features compared to the available asphaltene reservoir simulators. We are able to model asphaltene behavior during primary, secondary, and EOR stages. A new approach is presented to model asphaltene precipitation and flocculation. Adsorption, entrainment, and pore-throat plugging are considered as the main mechanisms of the asphaltene deposition. Moreover, we consider porosity, absolute permeability, and oil viscosity reductions due to asphaltene. It is well known that the asphaltene deposition on the rock surface changes the wettability of the rock towards oil-wet condition. Although many experiments in the literature have been conducted to understand the physics underlying wettability alteration due to asphaltene deposition, a comprehensive mathematical model describing this phenomenon is absent. Based on the available experimental data, a wettability alteration model due to asphaltene deposition is proposed and implemented into the simulator. Furthermore, the reservoir simulator is coupled to a wellbore simulator to model asphaltene deposition in the entire production system, from the injection well to the production well. The coupled reservoir/wellbore model can be used to track asphaltene deposition, to diagnose the potential of asphaltene problems in the wellbore and reservoir, and to find the optimum operating conditions of the well that minimizes asphaltene problems. In addition, the simulator is capable of modeling near-wellbore asphaltene remediation using chemical treatment. Based on the mechanisms of the asphaltene-dispersant interactions, a dynamic modeling approach for the near-wellbore asphaltene chemical treatments is proposed and implemented in the simulator. Using the dynamic asphaltene remediation model, we can optimize the asphaltene treatment plan to reduce asphaltene related problems in a field. The results of our simulations show that asphaltene precipitation, flocculation, and deposition in the reservoir and wellbore are dynamic processes. Many parameters, such as oil velocity, wettability alteration, pressure, temperature, and composition variations influence the trend of these processes. In the simulation test cases, we observe that asphaltene precipitation, flocculation, and deposition can occur in primary production, secondary production, or EOR stages. In addition, our results show that the wettability alteration has the major effect on the performance of the reservoir, comparing to the permeability reduction. During CO2 flooding, asphaltene precipitation occurs mostly at the front, and asphaltene deposition is at its maximum close to the reservoir boundaries where the front velocity is at its minimum. In addition, the results of the coupled reservoir/wellbore simulator show that the behavior of asphaltene in the wellbore and reservoir are fully coupled with each other. Therefore, a standalone reservoir or wellbore simulator is not able to predict the asphaltene behavior properly in the entire system. Finally, we show that the efficiency of an asphaltene chemical treatment plan depends on the type of dispersant, amount of dispersant, soaking time, number of treatment jobs, and the time period between two treatment jobs. / text

Simuladores de reservatÃrios sÃo amplamente utilizados em projetos de Engenharia de PetrÃleo. Os simuladores do tipo composicional utilizam EquaÃÃes de Estado (EdEâs) para o cÃlculo de diversas propriedades dos fluidos petrolÃferos, como a densidade da fase oleosa, o fator de compressibilidade da fase gasosa, a pressÃo de saturaÃÃo, dentre outras. No presente trabalho estudou-se a capacidade preditiva de trÃs equaÃÃes de estado (EdEâs): duas cÃbicas, e amplamente utilizadas em simuladores de reservatÃrios (Soave-Redlich-Kwong e Peng-Robinson), e uma nÃo-cÃbica, que vem ganhando notoriedade no meio cientÃfico e à oriunda da mecÃnica estatÃstica, a EdE Perturbed Chain â Statistical Association Fluid Theory (PC-SAFT). Diversos dados da literatura foram coletados e modelados pelas EdEâs selecionadas. Durante o trabalho desenvolveu-se um simulador em linguagem orientado ao objeto (Delphi 7Â) para cÃlculos de equilÃbrio lÃquido-vapor e de propriedades volumÃtricas de fluidos petrolÃferos. As EdEâs apresentaram bons resultados para propriedades como o volume relativo, fator de compressibilidade e a densidade do Ãleo. PorÃm nÃo apresentaram resultados considerÃveis para a pressÃo de saturaÃÃo, razÃo gÃs-Ãleo e fator-volume de formaÃÃo do Ãleo. Mesmo a EdE PC-SAFT apresentando resultados similares aos das outras EdEâs estudadas, muito ainda pode ser melhorado para esta equaÃÃo na aplicaÃÃo em simuladores de reservatÃrios, pois a mesma apresenta poucos estudos neste tipo de aplicaÃÃo. / Reservoir simulators are widely used in petroleum engineering projects. The simulators of compositional type using equations of state (EOSâs) for calculate various properties of petroleum fluids, as such the density of oil phase, the compressibility factor of gas phase, the saturation pressure, etc. In this work was studied the predictive capacity of three EOSâs, two cubic and widely used in reservoir simulators (Soave- Redlich-Kwong and Peng-Robinson) and a non-cubic EOS, that has had notoriety and comes of statistical mechanics, the Perturbed Chain â Statistical Association Fluid Theory (PC-SAFT). Several data from literature were collected and modeled with these EOSâs. A simulator in object-oriented language (Delphi 7Â) for calculations of liquid-vapor equilibrium and volumetric properties of petroleum fluids was developed during this work. The EOSâs present good results for some properties, such as relative volume,compressibility factor and oil density. Even the PC-SAFT EOS present similar results when compared with other EOSâs studied, much can be still improved in this equation for applications in reservoir simulators, since it contain few studies on this type of application.

[pt] Simuladores de escoamento em reservatórios são ferramentas importantes na otimização do desenvolvimento de um campo de petróleo. Estes simuladores modelam o escoamento multifásico através de meios porosos compressíveis, levando em conta as equações de equilíbrio de fases, as leis de fluxo e a variação volumétrica do meio poroso associada à variação da pressão de poros do sistema. As tensões in situ são consideradas através da aplicação de tensões constantes no contorno do reservatório. Este trabalho descreve a utilização de um simulador convencional de reservatório, baseado em diferenças finitas com e sem um módulo geomecânico, e a utilização de um simulador acoplado, que resolve as equações de escoamento e de tensão num mesmo código de elementos finitos. Nesta dissertação são feitas comparações entre os modelos geomecânicos aproximado e rigoroso oferecidos pelos simuladores comerciais, além de ser apresentada uma análise de situações em que esta última forma deve ser realmente considerada. O objetivo deste trabalho é analisar a influência das tensões in situ em reservatórios de petróleo com base na comparação entre os campos de poropressões obtidos a partir da modelagem de um mesmo sistema com os dois simuladores geomecânicos. São apresentadas as formas de acoplamento e a formulação utilizada em cada um dos modelos. Os modelos geomecânicos utilizados em cada um dos simuladores são comparados. É feita uma comparação entre os resultados obtidos pelos dois simuladores a partir de um modelo bidimensional. / [en] Numerical simulators for reservoir flow analysis are important tools for the optimization of oil field development. These simulators model the multiphase flow through compressible porous medium taking into account the phase equilibrium equations, flow laws and the rock volumetric change associated to the pore pressure change during production. Some simulators have been associated with stress analysis modules in order to use the pore pressure field obtained by the flow simulator and update the stress field within the reservoir. This dissertation describes the use of a conventional reservoir simulator based on finite differences that models multiphase flow in porous media, with and without a geomechanical module, and the use of a fully-coupled simulator that solves both the flow and stress equations in a single finite element code. This dissertation compares the two geomechanical modules, the approximated and the precise, offered by commercial simulators, and analyses the situations in which the rigorous form should be considered, or not. The aim of this dissertation is to investigate the influence of in situ stresses in petroleum reservoirs based on the comparison of the pore pressure fields obtained from the modeling of the same system with both geomechanical simulators. The coupling and formulation used in each model are presented. The geomechanical models of both simulators are described. A comparison of the simulators is made using a bidimensional model.

[pt] O desenvolvimento de um reservatório de petróleo já conhecido e delimitado consiste em encontrar uma alternativa (configuração) de poços que contribua para maximizar a receita a ser obtida com o óleo recuperado do reservatório. A busca por esta alternativa frequentemente é baseada em processos de otimização que usam o valor presente líquido (VPL) do projeto como função de avaliação das alternativas encontradas durante a busca. Dentre outras variáveis, o cálculo do VPL é diretamente dependente dos dados de produção de óleo, gás e água durante a vida produtiva do reservatório, bem como de seus custos de desenvolvimento. Determinar a localização, os tipos (produtor ou injetor) e a trajetória de poços em um reservatório é um problema de otimização complexo que depende de uma grande quantidade de variáveis, dentre elas as propriedades do reservatório (tais como porosidade e permeabilidade) e os critérios econômicos. Os processos de otimização aplicados a este tipo de problema têm um alto custo computacional devido ao uso contínuo de simuladores que reproduzem as condições do reservatório e do sistema de superfície. O uso dos simuladores pode ser substituído por um aproximador, que neste trabalho, é um modelo que utiliza Redes Neurais Artificiais. Os aproximadores aqui apresentados são feitos para substituir a simulação integrada do reservatório, do poço e da superfície (linhas de produção e riser). As amostras para a construção do aproximador é feita utilizando os simuladores de reservatório e de superfície e para reduzir o número de amostras necessárias e tornar sua construção mais rápida, utiliza-se Hipercubo Latino e Análise de Componentes Principais. Os aproximadores foram testados em dois reservatórios petrolíferos: um reservatório sintético, e baseado em um caso real. Os resultados encontrados indicam que estes aproximadores conseguem bom desempenho na substituição dos simuladores no processo de otimização devido aos baixos erros encontrados e à substancial diminuição do custo computacional. / [en] The development of an oil reservoir consists in finding an alternative of wells that contributes to maximizing the revenue to be obtained from the recovered reservoir oil. The pursuit for this alternative is often based on optimization processes using the net present value (NPV) of the project as the evaluation function of the alternatives found during this pursuit. Among other variables, the NPV calculation is directly dependent on the oil, gas and water production data during the productive life of the reservoir, as well as their development costs. Determine the number, location, type (producer or injector) and the trajectory of wells in a reservoir is a complex optimization problem which depends on a lot of variables, including the reservoir properties (such as porosity and permeability) and economic criteria. The optimization processes applied to this type of problem has a high computational cost due to the continuous use of simulators that reproduce the conditions of the reservoir and the surface system. The use of simulators may be replaced by proxies. At the present work, proxies were constructed using artificial neural networks. The proxies presented here are meant to replace the integrated reservoir, well and surface (production lines and riser) simulation to reduce the computational cost of a decision support system. The samples for the construction of the proxies are produced using reservoir and surface simulators. To reduce the number of samples needed for the proxy construction, and, to reduce the dimension of the problem, Latin Hypercube and Principal Component Analysis are used. The approximators were tested in two oil reservoirs: a synthetic reservoir, and another with real features. The results indicate that these approximators can perform well in replacement of simulators in the optimization process due to low errors found and a substantial decrease in computational cost.

Made available in DSpace on 2014-12-17T14:08:36Z (GMT). No. of bitstreams: 1 AmandaGO.pdf: 1269225 bytes, checksum: bb3d37e917eb9a6a37d5196f82512218 (MD5) Previous issue date: 2010-01-27 / The objective of reservoir engineering is to manage fields of oil production in order to maximize the production of hydrocarbons according to economic and physical restrictions. The deciding of a production strategy is a complex activity involving several variables in the process. Thus, a smart system, which assists in the optimization of the options for developing of the field, is very useful in day-to-day of reservoir engineers. This paper proposes the development of an intelligent system to aid decision making, regarding the optimization of strategies of production in oil fields. The intelligence of this system will be implemented through the use of the technique of reinforcement learning, which is presented as a powerful tool in problems of multi-stage decision. The proposed system will allow the specialist to obtain, in time, a great alternative (or near-optimal) for the development of an oil field known / O objetivo da engenharia de reservat?rios ? o de gerenciar campos de produ??o de petr?leo de forma a maximizar a produ??o dos hidrocarbonetos obedecendo a restri??es f?sicas e econ?micas existentes. A defini??o de estrat?gias de produ??o ? uma atividade complexa por envolver diversas vari?veis do processo. Deste modo, um sistema inteligente, que auxilie na otimiza??o das alternativas de desenvolvimento do campo, torna-se bastante ?til no dia-a-dia dos engenheiros de reservat?rios. Este trabalho prop?e o estudo preliminar de um sistema inteligente de aux?lio ? tomadas de decis?es, no que diz respeito ? otimiza??o de estrat?gias de produ??o em campos de petr?leo. A intelig?ncia desse sistema ser? implementada por meio do uso da t?cnica de aprendizado por refor?o, a qual se apresenta como uma poderosa ferramenta em problemas de decis?o multi-est?gios. O sistema estudado visa permitir que o especialista obtenha, em tempo h?bil, a alternativa ?tima (ou quase-?tima) para o desenvolvimento de um campo de petr?leo conhecido

[pt] A definição da estratégia de produção de petróleo é uma tarefa muito importante que consiste em um processo bastante complexo devido à grande quantidade de variáveis envolvidas. Estas variáveis estão relacionadas com características geológicas, fatores econômicos e decisões como alocação de poços, número de poços produtores e injetores, condições operacionais e cronograma de abertura de poços. No contexto da otimização da produção de petróleo, o objetivo é encontrar a melhor configuração de poços que contribua para maximizar, na maioria dos casos, o valor presente líquido (VPL). Esse valor é calculado, principalmente, a partir do óleo, gás e água produzidos do campo, que são encontrados através do uso do simulador de reservatórios. Porém, vários parâmetros e variáveis devem ser prefixados e inseridos no sistema de simulação para que esses valores de produção sejam previstos. Esse processo geralmente exige um alto custo computacional para modelar as transferências de fluidos dentro do reservatório simulado. Assim, o uso de simuladores pode ser substituído por aproximadores. Neste estudo, eles são desenvolvidos através da Programação Genética Linear com Inspiração Quântica, uma técnica da Computação Evolucionária. Esses aproximadores serão utilizados para substituir a simulação do reservatório no processo de otimização da localização e tipo de poços a serem perfurados em um campo petrolífero. Para a construção dos proxies de reservatório, as amostras, originadas utilizando a técnica do Hipercubo Latino, foram simuladas para a criação da base de dados. O modelo para criação de aproximadores foi testado em um reservatório sintético. Dois tipos de otimização foram realizados para a validação do modelo. A primeira foi a otimização determinística e a segunda uma otimização sob incerteza considerando três diferentes cenários geológicos, um caso onde o número de simulações é extremamente alto. Os resultados encontrados apontam que o modelo para a criação de proxies consegue bom desempenho na substituição dos simuladores devido aos baixos erros encontrados e na considerável redução do custo computacional. / [en] The purpose of oil production strategy in the context of production optimization is to find the best configuration of wells that contributes to maximizing the Net Present Value. This value is calculated mainly from the amount of oil, gas, and water recovered from the field, which can be obtained by running the reservoir simulator. However, many parameters and variables must be prefixed and inserted into the simulation system in order to generate these production values. This process involves a high computational cost for modeling the transfer of fluids within the simulated reservoir. Thus, the use of simulators may be substituted by approximators. In this thesis, we aim to develop these approximators using Quantum-Inspired Linear Genetic Programming, a technique of Evolutionary Computation. These approximators were used to replace the reservoir simulation in the process of optimizing the location and type of wells to be drilled in a field. For the reservoir proxies construction, samples obtained from the technique of Latin Hypercube were simulated to create the database. The model for creating approximators was tested on a synthetic reservoir. Two types of optimization were performed to validate the model. The first was a deterministic optimization and the second an optimization under uncertainty considering three different geological settings, a situation in which the number of simulations becomes extremely high. Our results indicated that the model for the creation of proxies achieves a satisfactory performance in the replacement of simulators due to low levels of errors and a considerable reduction of the computational cost.

[pt] Os estudos entre a interação do fluxo de fluido e a deformação do meio poroso têm sido realizados com o objetivo de explicar alguns fenômenos que ocorrem ao longo da produção/injeção de fluidos, e assim obter uma simulação de reservatórios cada vez mais precisa. A solução ideal para o problema é implementar um esquema, onde as leis que governam o fluxo e analise de tensões sejam obedecidas simultaneamente em cada intervalo de tempo. Este trabalho apresenta os resultados de um código (programado em C positivo positivo) que permite acoplar um simulador de fluxo convencional (ECLIPSE) e um programa que permite analisar tensões e deslocamentos (Abaqus /CAE). O objetivo deste trabalho é validar varias soluções para resolver um problema usando os diferentes tipos de acoplamento, que juntamente com uma filosofia empregada nas principais formulações permite dar respostas similares aquelas do acoplamento total. São apresentadas as formas de acoplamento e a formulação empregada em cada um dos esquemas usados. Os resultados obtidos pelos esquemas são comparados em termos de fluxo e tensões e deslocamentos a partir de modelos tridimensionais. / [en] Studies between the interaction of fluid flow and deformation of porous media have been carried out with the aim of explaining some phenomena that occur along the production/injection of fluids, thereby obtaining a more accurate reservoir simulation. The ideal solution for this problem is to implement a scheme where laws governing the flow and stress analysis are met simultaneously at each time interval. This dissertation presents the results of a computer code (programmed in C positive positive) that allows the coupling of a conventional reservoir simulator (ECLIPSE) and a stress-displacement finite element based program (Abaqus /CAE). This work presents the use of various coupling schemes for the solution of a synthetic case, in particular the use of a methodology that generates results very close to the ones predicted from the use of fully coupled methods. The results obtained by the different coupling schemes are compared in terms of fluid pressure, stress and displacement responses for synthetic three-dimensional models.

Thermal and chemical recovery processes are important EOR methods used often by the oil and gas industry to improve recovery of heavy oil and high viscous oil reservoirs. Knowledge of underlying mechanisms and their modeling in numerical simulation are crucial for a comprehensive study as well as for an evaluation of field treatment. EOS-compositional, thermal, and blackoil reservoir simulators can handle gas (or steam)/oil/water equilibrium for a compressible multiphase flow. Also, a few three-phase chemical flooding reservoir simulators that have been recently developed can model the oil/water/microemulsion equilibrium state. However, an accurate phase behavior and fluid flow formulations are absent in the literature for the thermal chemical processes to capture four-phase equilibrium. On the other hand, numerical simulation of such four-phase model with complex phase behavior in the equilibrium condition between coexisting phases (oil/water/microemulsion/gas or steam) is challenging. Inter-phase mass transfer between coexisting phases and adsorption of components on rock should properly be modeled at the different pressure and temperature to conserve volume balance (e.g. vaporization), mass balance (e.g. condensation), and energy balance (e.g. latent heat). Therefore, efforts to study and understand the performance of these EOR processes using numerical simulation treatments are quite necessary and of utmost importance in the petroleum industry. This research focuses on the development of a robust four-phase reservoir simulator with coupled phase behaviors and modeling of different mechanisms pertaining to thermal and chemical recovery methods. Development and implementation of a four-phase thermal-chemical reservoir simulator is quite important in the study as well as the evaluation of an individual or hybrid EOR methods. In this dissertation, a mathematical formulation of multi (pseudo) component, four-phase fluid flow in porous media is developed for mass conservation equation. Subsequently, a new volume balance equation is obtained for pressure of compressible real mixtures. Hence, the pressure equation is derived by extending a black oil model to a pseudo-compositional model for a wide range of components (water, oil, surfactant, polymer, anion, cation, alcohol, and gas). Mass balance equations are then solved for each component in order to compute volumetric concentrations. In this formulation, we consider interphase mass transfer between oil and gas (steam and water) as well as microemulsion and gas (microemulsion and steam). These formulations are derived at reservoir conditions. These new formulations are a set of coupled, nonlinear partial differential equations. The equations are approximated by finite difference methods implemented in a chemical flooding reservoir simulator (UTCHEM), which was a three-phase slightly compressible simulator, using an implicit pressure and an explicit concentration method. In our flow model, a comprehensive phase behavior is required for considering interphase mass transfer and phase tracking. Therefore, a four-phase behavior model is developed for gas (or steam)/ oil/water /microemulsion coexisting at equilibrium. This model represents coupling of the solution gas or steam table methods with Hand’s rule. Hand’s rule is used to capture the equilibrium between surfactant, oil, and water components as a function of salinity and concentrations for oil/water/microemulsion phases. Therefore, interphase mass transfer between gas/oil or steam/water in the presence of the microemulsion phase and the equilibrium between phases are calculated accurately. In this research, the conservation of energy equation is derived from the first law of thermodynamics based on a few assumptions and simplifications for a four-phase fluid flow model. This energy balance equation considers latent heat effect in solving for temperature due to phase change between water and steam. Accordingly, this equation is linearized and then a sequential implicit scheme is used for calculation of temperature. We also implemented the electrical Joule-heating process, where a heavy oil reservoir is heated in-situ by dissipation of electrical energy to reduce the viscosity of oil. In order to model the electrical Joule-heating in the presence of a four-phase fluid flow, Maxwell classical electromagnetism equations are used in this development. The equations are simplified and assumed for low frequency electric field to obtain the conservation of electrical current equation and the Ohm's law. The conservation of electrical current and the Ohm's law are implemented using a finite difference method in a four-phase chemical flooding reservoir simulator (UTCHEM). The Joule heating rate due to dissipation of electrical energy is calculated and added to the energy equation as a source term. Finally, we applied the developed model for solving different case studies. Our simulation results reveal that our models can accurately and successfully model the hybrid thermal chemical processes in comparison to existing models and simulators. / text