Most available data from shale production zones tends to point towards the presence of complex hydraulic fracture networks, especially in the Barnett and Marcellus formations. Representing these complex hydraulic fracture networks in reservoir simulators while incorporating the geo-mechanical parameters and fracture apertures is a challenge. In our work we developed a fracture to production simulation workflow using complex hydraulic fracture propagation model and a commercial reservoir simulator. The workflow was applied and validated using geological, stimulation and production data from the Marcellus shale. For validation, we used published data from a 5200 ft. long horizontal well drilled in the lower Marcellus. There were 14 fracturing stages with micro-seismic data and an available production history of 9 months. Complex hydraulic fractures simulations provided the fracture network geometry and aperture distributions as the output, which were up-scaled to grid block porosity and permeability values and imported into a reservoir model for production simulation and history match. The approach of using large grid blocks with conductivity adjustment to represent hydraulic fractures in a reservoir simulator which has been employed in this workflow was validated by comparing with published numerical and analytical solutions. Our results for history match were found to be in reasonable agreement with published results. The incorporation of apertures, complexity and geo-mechanics into reservoir models through this workflow reduces uncertainty in reservoir simulation of shale plays and leads to more realistic production forecasting. The workflow was utilized to study the effect of fracture conductivity damage on production. Homogenous and heterogeneous damage cases were considered. Capillary pressures, determined using empirical relationships and experimental data, were studied using the fracture to production workflow. Assuming homogenous instead of heterogeneous permeability damage in reservoir simulations was shown to have a significant impact on production forecasting, overestimating production by 70% or more over the course of two years. Capillary pressure however was less significant and ignoring capillary pressure in damaged hydraulic fractures led to only 3% difference in production in even the most damaged cases. / text

No description available.

Orientador: Denis José Schiozer / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica e Instituto de Geociências / Made available in DSpace on 2018-08-16T03:09:54Z (GMT). No. of bitstreams: 1 Bento_DeboraFerreira_M.pdf: 5080634 bytes, checksum: fb4f6d1d73f4079215e05919e962ccb6 (MD5) Previous issue date: 2010 / Resumo: O sucesso de um projeto de desenvolvimento de um campo de petróleo depende de uma estratégia de produção adequada. A seleção da estratégia através de um processo de otimização busca menores investimentos e custos operacionais e maiores produções de óleo e gás, melhorando o lucro medido através do valor presente líquido do projeto (VPL). Existem inúmeras metodologias para otimização da estratégia de produção que, em geral, são trabalhosas e demandam grande esforço computacional. Como o tempo é uma variável impactante no retorno econômico de projetos, a indústria tende a simplificar as simulações numéricas, principalmente separando as modelagens dos reservatórios e dos sistemas operacionais. Este trabalho tem como objetivo verificar se estas simplificações influenciam no resultado final do processo de seleção de estratégias de produção. Complementando trabalhos anteriores, foram selecionadas e estudadas duas restrições operacionais: perda de carga nas linhas de produção e o limite de escoamento do gás. Foi proposta ainda uma metodologia de otimização de estratégia de produção e de análise da influência da restrição operacional, com foco nos casos estudados. Os resultados mostram a influência das restrições no processo, possibilitando ainda identificar as características dos reservatórios, fluídos e cenário econômico onde essa influência é mais significativa / Abstract: The success of a development project of a petroleum field depends on adequate production strategy. The selection of the strategy through an optimization process searches for minors investments and operational costs and greater oil and gas productions, improving the profit measured through the liquid present value of the project (LPV). There are innumerable methodologies for production strategy optimization and, in general, they are laborious and demand a great computational effort. Considering that time is an important variable in the project economic return, the industry tends to simplify the numerical simulations, mainly separating the reservoir and operational systems. The objective of this work is to verify if these simplifications have significant influence on the final result of the production strategy selection process. Complementing previous works, two operational constraints were selected and studied: pressure drop in the production lines and the gas flow limit. Two methodologies were proposed, with focus in the studied cases: a production strategy optimization process and an operational constraints influence analysis. The results demonstrate the influence of the operational constraints restrictions in the process, making it possible to identify the characteristics of the reservoirs, fluids and economic scenario where this influence is more significant / Mestrado / Reservatórios e Gestão / Mestre em Ciências e Engenharia de Petróleo

No description available.

A variety of oil recovery improvement techniques has been developed and applied to the productive life of an oil reservoir. Reservoir simulators have a definitely established role in helping to identify the opportunity and select the most suitable techniques to optimum improvement in reservoir productivity. This is significantly important for those reservoirs whose operating and development costs are relatively expensive, because numerical modeling helps simulate the increased oil productivity process and evaluates the performance without undertaking trials in field. Moreover, rapid development in modeling provides engineers diverse choices. Hence the need for complete and comprehensive case studies is increasing. This study will show the different characteristics of in-house (UTCOMP and GPAS) and commercial simulators and also can validate implementation and development of models in the future. The purpose of this thesis is to present a series of case studies with analytical solutions, in addition to a series of more complicated field cases studies with no exact solution, to verify and test the functionality and efficiency of various simulators. These case studies are performed with three reservoir simulators, including UTCOMP, GPAS, and CMG. UTCOMP and GPAS were both developed at the Center for Petroleum and Geosystem Engineering at The University of Texas at Austin and CMG is a commercial reservoir simulator developed by Computer Modelling Group Ltd. These simulators are first applied to twenty case studies with exact solutions. The simulation results are compared with exact solutions to examine the mathematical formulations and ensure the correctness of program coding. Then, ten more complicated field-scale case studies are performed. These case studies vary in difficulty and complexity, often featuring heterogeneity, larger number of components and wells, and very fine gridblocks. / text

Orientadores: Denis José Schiozer, Gabriel Alves da Costa Lima / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica e Instituto de Geociências / Made available in DSpace on 2018-08-19T18:25:23Z (GMT). No. of bitstreams: 1 Carvalho_MarcosHenriquede_M.pdf: 3436602 bytes, checksum: 6fc653eb73d82869d8e3b2d81634b94d (MD5) Previous issue date: 2011 / Resumo: A simulação de reservatório é a base para as previsões de produção, dimensionamento de equipamentos de superfície e planejamento de atividades de produção. É uma ferramenta para elaborar a estratégia de produção que gera curvas de previsão de produção de petróleo. No entanto, mesmo sem considerar incertezas geológicas e econômicas, na prática, tal curva de produção pode apresentar baixa probabilidade de ser verificada, uma vez que a disponibilidade operacional dos sistemas físicos é uma variável incerta com valor abaixo de 100%. Então, o resultado final depende de: estratégia de produção, das incertezas presentes no modelo e da confiabilidade dos sistemas (equipamentos); este último item é o foco deste trabalho. O objetivo principal deste trabalho é verificar a importância e a influência de um estudo da análise da confiabilidade dos sistemas de produção integrada com a simulação do reservatório, a fim de verificar o impacto sobre a produção de petróleo e sobre o valor presente líquido. Sendo assim, além da opção no simulador disponível para incluir, de forma simplificada, as informações de confiabilidade dos sistemas, por meio de um índice de disponibilidade média constante, foi desenvolvido um algoritmo que trata o fechamento e restabelecimento dos sistemas de forma probabilística, a fim de a operação ser tratada em um cenário mais realista. A metodologia proposta é aplicada a um campo de petróleo com óleo leve e a um campo de petróleo com óleo pesado. Com os resultados, conclui-se que, quando as informações de confiabilidade são inseridas no simulador de forma dinâmica, a produção acumulada de óleo leve não apresenta uma diferença significativa quando comparada com o caso em que as informações de confiabilidade dos sistemas não são consideradas. Por outro lado, para o campo de óleo pesado, apesar de a média também não ter apresentado diferença significativa, observa-se uma alta variação na produção de óleo. Em ambos os campos ocorre um atraso na produção, afetando o fluxo de caixa, resultando em diferenças significativas no VPL / Abstract: The reservoir simulation is the basis for the forecasts of production, dimensioning of surface equipments and the planning of activities related to production. Therefore, a production strategy which generates oil and gas production curves over the operational lifetime. However, even without considering geological and economic uncertainties, in practice, this curve presents low probability of being verified, since the operational availability of the production systems is an uncertain variable with value below 100%. Then, the final result depends on: production strategy, uncertainties present in the model and the reliability of the systems (equipments), which is the focus of this paper. The main objective of this work is to verify the importance and influence of a study of the analysis of the reliability of the production systems integrated to the reservoir simulation, in order to verify the impact on the oil production and on the net present value. Thus, besides de option in the simulator available for including, in a simplified way, the information of reliability of the systems, through an index of availability constant, it was developed an algorithm that treats the shutting and restore of the systems in a probabilistic way, in order to them be treated in a more realistic operation scenario. The proposed methodology is applied to a light oil field and a heavy oil field. With the results, it is concluded that, when the reliability information are inserted in the simulator in a dynamic way, the cumulative production of light oil does not present a significant difference when compared to the case where the reliability information of the systems are not considered. On the other hand, the heavy oil Field, despite the mean also does not present a significant difference, it is noted a high variation in the production figures. However, for both fields occurs a delay in production, affecting the cash flow resulting in significant differences in NPV / Mestrado / Reservatórios e Gestão / Mestre em Ciências e Engenharia de Petróleo

History matching is a process wherein changes are made to an initial geologic model of a reservoir, so that the predicted reservoir performance matches with the known production history. Changes are made to the model parameters which include rock and fluid parameters (viscosity, compressibility, relative permeability, etc.) or properties within the geologic model. Assisted History Matching (AHM) provides an algorithmic framework to minimize the mismatch in simulation, and aids in accelerating this process. The changes made by AHM techniques, however, cannot ensure a geologically consistent reservoir model. In fact, the performance of these techniques depends on the initial starting model. In order to understand the impact of the initial model, this project explored the performance of the AHM approach using a specific field case, but working with multiple distinct geologic scenarios. This project involved an integrated seismic to simulation study, wherein I interpreted the seismic data, assembled the geological information, and performed petrophysical log evaluation along with well test data calibration. The ensemble of static models obtained was carried through the AHM methodology. I used sensitivity analysis to determine the most important dynamic parameters that affect the history match. These parameters govern the large scale changes in the reservoir description and are optimized using the Evolutionary Strategy Algorithm. Finally, the streamline based techniques were used for local modifications to match the water cut well by well. The following general conclusions were drawn from this study- a) The use of multiple simple geologic models is extremely useful in screening possible geologic scenarios and especially for discarding unreasonable alternative models. This was especially true for the large scale architecture of the reservoir. b) The AHM methodology was very effective in exploring a large number of parameters, running the simulation cases, and generating the calibrated reservoir models. The calibration step consistently worked better if the models had more spatial detail, instead of the simple models used for screening. c) The AHM methodology implemented a sequence of pressure and water cut history matching. An examination of specific models indicated that a better geologic description minimized the conflict between these two match criteria.

A significant body of work has demonstrated both the promise and difficulty of quantifying uncertainty in reservoir simulation forecasts. It is generally accepted that accurate and complete quantification of uncertainty should lead to better decision making and greater profitability. Many of the techniques presented in past work attempt to quantify uncertainty without sampling the full parameter space, saving on the number of simulation runs, but inherently limiting and biasing the uncertainty quantification in the resulting forecasts. In addition, past work generally has looked at uncertainty in synthetic models and does not address the practical issues of quantifying uncertainty in an actual field. Both of these issues must be addressed in order to rigorously quantify uncertainty in practice. In this study a new approach to reservoir simulation is taken whereby the traditional one-time simulation study is replaced with a new continuous process potentially spanning the life of the reservoir. In this process, reservoir models are generated and run 24 hours a day, seven days a week, allowing many more runs than previously possible and yielding a more thorough exploration of possible reservoir descriptions. In turn, more runs enabled better estimates of uncertainty in resulting forecasts. A new technology to allow this process to run continuously with little human interaction is real-time production and pressure data, which can be automatically integrated into runs. Two tests of this continuous simulation process were conducted. The first test was conducted on the Production with Uncertainty Quantification (PUNQ) synthetic reservoir. Comparison of our results with previous studies shows that the continuous approach gives consistent and reasonable estimates of uncertainty. The second study was conducted in real time on a live field. This study demonstrates the continuous simulation process and shows that it is feasible and practical for real world applications.

The large volume of water produced during the extraction of oil presents a significant problem due to the high cost of disposal in an environmentally friendly manner. On average, an estimated seven barrels of water is produced per barrel of oil in the US alone and the associated treatment and disposal cost is an estimated $5-10 billion. Besides making oil-water separation more complex, produced water also causes problems such as corrosion in the wellbore, decline in production rate and ultimate recovery of hydrocarbons and premature well or field abandonment. Water production can be more problematic during waterflooding in a highly heterogeneous reservoir with vertical communication between layers leading to unevenness in the flood front, cross-flow between high and low permeability layers and early water breakthrough from high permeability layers. Some of the different technologies that can be used to counteract this involve reducing the mobility of water or using a permeability block in the higher permeability, swept zones. This research was initiated to evaluate the potential effectiveness of the latter method, known as deep diverting gels (DDG) to plug thief zones deep within the reservoir and far from the injection well. To evaluate the performance of DDG, its injection was modeled, sensitivities run for a range of reservoir characteristics and conditions and an economic analysis was also performed. The performance of the DDG was then compared to other recovery methods, specifically waterflooding and polymer flooding from a technical and economic perspective. A literature review was performed on the background of injection profile control methods, their respective designs and technical capabilities. For the methods selected, Schlumberger's Eclipse software was used to simulate their behavior in a reservoir using realistic and simplified assumptions of reservoir characteristics and fluid properties. The simulation results obtained were then used to carry out economic analyses upon which conclusions and recommendations are based. These results show that the factor with the largest impact on the economic success of this method versus a polymer flood was the amount of incremental oil produced. By comparing net present values of the different methods, it was found that the polymer flood was the most successful with the highest NPV for each configuration followed by DDG.

Significant quantities of hydrocarbon are bypassed during conventional waterfloods. This is the direct result of fluid channeling through high permeability zones within the reservoir. Conformance control offers a mean of increasing vertical and areal sweep efficiency, thus decreasing the amount of hydrocarbon bypassed. This, in turn, results in increased hydrocarbon production, decreased water cut, and field life extension. This thesis focuses on the use of polymer microgels as a relatively novel conformance control agent. Polymer-microgel-enhanced waterflooding tackles fluid channeling by “plugging” high permeability channels, or thief zones, and diverting trailing flooding fluid to adjacent poorly swept areas of the reservoir. The first major objective of this thesis was to provide an extensive literature survey on polymer microgel technology, which can serve as the go-to reference on this topic. Colloidal Dispersion Gels (CDGs), Preformed Particle Gels (PPGs), temperature-sensitive polymer microgels (Bright Water), and pH-sensitive polymer microgels are all discussed in detail, and an attempt is made to highlight the potential mechanisms by which they plug thief zones and improve oil recovery. This thesis then outlines the results of simulating numerous polymer microgel floods, ranging from experimental cases to field cases. Specifically, Colloidal Dispersion Gels (CDGs) were chosen for the simulations undergone. All simulations were run using UTGEL, a newly developed in-house simulator designed exclusively for the simulation of polymer, gel, and microgel floods. The simulations performed provide insight on the polymer microgel flooding process, and also served as a means of validating UTGEL’s polymer microgel (CDG) models. The development of the UTGEL simulator was important as it enables the optimization of polymer microgel floods for maximized hydrocarbon recovery efficiency. The results of a simulation study, using a synthetic field case, are also outlined. This sensitivity study provides additional insight on optimal operational conditions for polymer microgel technology. More specifically, this study aimed to investigate the effectiveness of microgel flooding treatments in layered reservoirs of varying permeability contrasts, vertical-to-horizontal permeability ratios, and under a variety of different injection concentrations. / text