It has been known that volatile oil and gas condensate reservoirs cannot be modeled accurately with conventional black-oil models. One variation to the black-oil approach is the modified black-oil (MBO) model that allows the use of a simple, and less expensive computational algorithm than a fully compositional model that can result in significant timesaving in full field studies. The MBO model was tested against the fully compositional model and performances of both models were compared using various production and injection scenarios for a rich gas condensate reservoir. The software used to perform the compositional and MBO runs were Eclipse 300 and Eclipse 100 versions 2002A. The effects of black-oil PVT table generation methods, uniform composition and compositional gradient with depth, initialization methods, location of the completions, production and injection rates, kv/kh ratios on the performance of the MBO model were investigated. Vertical wells and horizontal wells with different drain hole lengths were used. Contrary to the common belief that oil-gas ratio versus depth initialization gives better representation of original fluids in place, initializations with saturation pressure versus depth gave closer original fluids in place considering the true initial fluids in place are given by the fully compositional model initialized with compositional gradient. Compared to the compositional model, results showed that initially there was a discrepancy in saturation pressures with depth in the MBO model whether it was initialized with solution gas-oil ratio (GOR) and oil-gas ratio (OGR) or dew point pressure versus depth tables. In the MBO model this discrepancy resulted in earlier condensation and lower oil production rates than compositional model at the beginning of the simulation. Unrealistic vaporization in the MBO model was encountered in both natural depletion and cycling cases. Oil saturation profiles illustrated the differences in condensate saturation distribution for the near wellbore area and the entire reservoir even though the production performance of the models was in good agreement. The MBO model representation of compositional phenomena for a gas condensate reservoir proved to be successful in the following cases: full pressure maintenance, reduced vertical communication, vertical well with upper completions, and producer set as a horizontal well.

It has been known that volatile oil and gas condensate reservoirs cannot be modeled accurately with conventional black-oil models. One variation to the black-oil approach is the modified black-oil (MBO) model that allows the use of a simple, and less expensive computational algorithm than a fully compositional model that can result in significant timesaving in full field studies. The MBO model was tested against the fully compositional model and performances of both models were compared using various production and injection scenarios for a rich gas condensate reservoir. The software used to perform the compositional and MBO runs were Eclipse 300 and Eclipse 100 versions 2002A. The effects of black-oil PVT table generation methods, uniform composition and compositional gradient with depth, initialization methods, location of the completions, production and injection rates, kv/kh ratios on the performance of the MBO model were investigated. Vertical wells and horizontal wells with different drain hole lengths were used. Contrary to the common belief that oil-gas ratio versus depth initialization gives better representation of original fluids in place, initializations with saturation pressure versus depth gave closer original fluids in place considering the true initial fluids in place are given by the fully compositional model initialized with compositional gradient. Compared to the compositional model, results showed that initially there was a discrepancy in saturation pressures with depth in the MBO model whether it was initialized with solution gas-oil ratio (GOR) and oil-gas ratio (OGR) or dew point pressure versus depth tables. In the MBO model this discrepancy resulted in earlier condensation and lower oil production rates than compositional model at the beginning of the simulation. Unrealistic vaporization in the MBO model was encountered in both natural depletion and cycling cases. Oil saturation profiles illustrated the differences in condensate saturation distribution for the near wellbore area and the entire reservoir even though the production performance of the models was in good agreement. The MBO model representation of compositional phenomena for a gas condensate reservoir proved to be successful in the following cases: full pressure maintenance, reduced vertical communication, vertical well with upper completions, and producer set as a horizontal well.

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

[pt] Nas últimas décadas, grandes investimentos foram feitos no desenvolvimento de modelos e métodos numéricos para prever e analisar os diferentes aspectos do processo de recuperação de óleo e gás. Neste contexto, os simuladores modernos devem ser capazes de incorporar uma grande variedade de opções para responder questões relacionadas ao gerenciamento de reservatórios de forma rápida e precisa. Neste trabalho, nós apresentamos um simulador de reservatórios baseado em uma arquitetura de plugins, onde diferentes formulações, solvers e modelos podem ser desenvolvidos, estendidos e aprimorados. A partir desta abordagem, utilizamos o modelo black-oil para implementar técnicas tradicionais e do estado da arte, como os métodos totalmente e adaptativamente implícito, os métodos de Newton-Raphson e Newton Inexato, controladores heurístico e PID para passo de tempo adaptativo e aproximações de fluxo de um ponto baseados no potencial de fase tradicional e C1-contínuo. Diversas configurações de plugins foram testadas e validadas com simuladores comerciais e seus desempenhos foram utilizados para determinar quais as mais adequadas para resolver problemas de escoamento multifásico. / [en] During the last decades, large investments were made towards the development of numerical models and methods to forecast and analyze the different aspects of oil and gas recovery. In this context, modern simulators must be able to incorporate a wide variety of options to answer questions related to reservoir management accurately and effectively. In this work, we present a reservoir simulator based on a plugin architecture, where different formulations, solvers, and models can be developed, extended, and enhanced. With this approach, we use the black-oil model to implement traditional and state-of-the-art techniques, including fully- and adaptiveimplicit methods, heuristic and PID time-step controllers, Newton-Raphson and Inexact Newton, and C1-continuous and conventional phase-potential single-point upstream weighting. Several plugin configurations were tested and validated with commercial simulators, and their performances were used to determine which are the most suitable to solve multiphase flow problems.