This work describes a new methodology for integrated decision analysis in the development and management of petroleum fields considering reservoir simulation, risk analysis, history matching, ...uncertainty reduction, representative models, and production strategy selection under uncertainty. Based on the concept of closed-loop reservoir management, we establish 12 steps to assist engineers in model updating and production optimization under uncertainty. The methodology is applied to UNISIM-I-D, a benchmark case based on the Namorado field in the Campos Basin, Brazil. The results show that the method is suitable for use in practical applications of complex reservoirs in different field stages (development and management). First, uncertainty is characterized in detail and then scenarios are generated using an efficient sampling technique, which reduces the number of evaluations and is suitable for use with numerical reservoir simulation. We then perform multi-objective history-matching procedures, integrating static data (geostatistical realizations generated using reservoir information) and dynamic data (well production and pressure) to reduce uncertainty and thus provide a set of matched models for production forecasts. We select a small set of Representative Models (RMs) for decision risk analysis, integrating reservoir, economic and other uncertainties to base decisions on risk-return techniques. We optimize the production strategies for (1) each individual RM to obtain different specialized solutions for field development and (2) all RMs simultaneously in a probabilistic procedure to obtain a robust strategy. While the second approach ensures the best performance under uncertainty, the first provides valuable insights for the expected value of information and flexibility analyses. Finally, we integrate reservoir and production systems to ensure realistic production forecasts. This methodology uses reservoir simulations, not proxy models, to reliably predict field performance. The proposed methodology is efficient, easy-to-use and compatible with real-time operations, even in complex cases where the computational time is restrictive.
Well prioritization rules on integrated production models are required for the interaction between reservoirs and restricted production systems, thus predicting the behavior of multiple reservoir ...sharing facilities. This study verified the impact of well management with an economic evaluation based on the distinct prioritizations by reservoir with different fluids. We described the impact of the well management method in a field development project using a consolidated methodology for production strategy optimization. We used a benchmark case based on two offshore fields, a light oil carbonate and a black-oil sandstone, with gas production constraint in the platform. The independent reservoir models were tested on three different approaches for platform production sharing: (Approach 1) fixed apportionment of platform production and injection, (Approach 2) dynamic flow-based apportionment, and (Approach 3) dynamic flow-based apportionment, including economic differences using weights for each reservoir. Approach 1 provided the intermediate NPV compared with the other approaches. On the other hand, it provided the lowest oil recovery. We observed that the exclusion of several wells in the light oil field led to a good valuation of the project, despite these wells producing a fluid with higher value. Approach 2 provided the lower NPV performance and intermediate oil recovery. We found that the well prioritization based on flow failed to capture the effects related to the different valuation of the fluids produced by the two reservoirs. Approach 3, which handled the type of fluids similarly to Approach 1, provided a greater NPV and oil recovery than the other approaches. The weight for each reservoir applied to well prioritization better captured the gains related to different valuation of the fluids produced by the two reservoirs. Dynamic prioritization with weights performed better results than fixed apportionment to shared platform capacities. We obtained different improvements in the project development optimization due to the anticipation of financial returns and CAPEX changes, due mainly from adequate well apportionment by different management algorithm. Well management algorithms implemented in traditional simulators are not developed to prioritize different reservoir wells separately, especially if there are different economic conditions exemplified here by a different valuation of produced fluids. This valuation should be taken into account in the short term optimization for wells.
This paper proposes a new iterative discrete Latin hypercube sampling based method to maximize the objective function (OF) in production strategy optimization. This methodology adequately treats ...posterior frequency distributions of discrete random variables and maximizes non-necessarily monotonic objective functions within discontinuous search spaces and many local optimums. To validate the method, we used an exhaustive process with an net present value (NPV) proxy, as the objective function, to be maximized. Using as an application case, the benchmark UNISIM-I-D reservoir model, based on Namorado field, Campos basin, Brazil, the method successfully maximized the NPV in the intermediate phase of production strategy optimization, and even compared favorably with a well-established optimization methodology. Population based optimization using discrete Latin hypercube sampling best suited this methodology, with consistent convergence to global optimum, few OF evaluations and the simultaneous multiple numeric reservoir simulations runs. This easy to use, reliable methodology with low computational time costs is an interesting option for optimization methods in problems of production strategy design related to the oil industry.
Comprehensive studies of oil reservoir and production systems present many variables which evaluation may lead to increase in both computational time and potential discontinuities. Using a reduced ...number of variables, we can effectively evaluate oil production and indicate decisions to be made for production management. The work was divided into two steps. In step one, decoupled production system, focusing on well and gathering systems were analyzed to identify the influence of parameters on field production. This decreases the number of variables, which promotes simulations with less computational effort and more robust optimization studies. In step two, an integrated reservoir and production system is considered, including the parameters that most impacted the production (from step one), and its influence on net present value. The integrated and decoupled analyses showed that, even if the reservoir can produce at a particular flow rate, there is no guarantee that production will be as forecasted. We also noted that future changes in the production system can contribute to maintain or to increase production and may improve financial return. The integrated analysis showed more realistic results for the production of this field, in an analysis combining oil production and financial return.
The management of oil fields that present high gas content is challenging, mainly in cases where this represents a bottleneck for oil production due to gas platform constraints. One way to deal with ...this problem is with the use of ICVs (Interval Control Valves), which enables the production to be controlled by zones in the wells.
In this work, we propose a methodology using reactive control rules for producers and ICVs, with GOR as monitoring variable, to improve the economic performance of the field. We compare the management of the field in three ways: (a) well management by shutting down producers when they reach an uneconomic GOR limit, (b) the use of ICVs on-off type and (c) application of multi-position type ICVs. We extend the application of algorithm IDLHC (Iterative Discrete Latin Hypercube) for the optimization process in this context. This study is made in a synthetic simulation case (Lira1_2022) with characteristics of a Brazilian pre-salt carbonate field with karstic features, high CO2 content and using WAG (Water-Alternate-Gas) injection as recovery mechanism.
The results demonstrated that the use of ICVs has a great potential to increase the performance of the field, both in economic and production indicators, when compared to well shut-in management. Both ICV on-off and multi-position types achieved similar results, with a slight advantage to the multi-position type ICVs. The improvement in the field's performance was mainly caused by the interference among zones and wells, in which the closure of less productive wells, or zones, reflected in improvements in other more productive wells.
•We compare the management of wells with and without ICVs applying reactive rules using GOR as monitoring variable.•Multi-position and ON-OFF ICVs achieved similar results, both being superior than just shutting wells for field management.•Algorithm IDLHC was compared to other methods and proved to be an effective method for control variables optimization.•Using GOR as trigger for ICV optimization showed to be a good method for the management of fields with high gas content.
Numerical reservoir simulation is an important tool that is widely used in the petroleum industry for production forecast and decision-making processes. In a context of integrated production system ...involving the reservoir, wells, and production facilities, the quality of production forecast depends not only on the quality of reservoir models and well productivity/injectivity but also on the boundary condition for the future extrapolation which, in turn, depends on the production system characteristics. Both systems, reservoir and production facilities, are characterized by uncertain properties and behavior, such as porosity and permeability, among others, for reservoir; pipeline roughness, multiphase flow behavior in pipes, among others, for the production system. This paper proposes a methodology for dynamic data assimilation to reduce uncertainty in both reservoir and production system models to improve short- and medium-term production forecast. The methodology was applied to a benchmark case built using real data from an offshore field in The Campos Basin (Brazil). The results from this study show that it is important to perform data assimilation process in both reservoir and production systems to obtain more reliable production forecasts. We also show that, by focusing on the short- and medium-term production forecast, the production system and reservoir uncertainties cause variability in the production forecast in the same order or magnitude. Based on that, it is recommended to consider multiple solutions of the production system to obtain more realistic production forecasts.
•Reservoir and production system may cause similar variability in production forecast.•A new methodology to deal with uncertainties in both reservoir and production systems was proposed.•It is important to consider multiple solutions of the production system in the entire process.•Data assimilation in both reservoir and production systems provide more reliable forecast.
The significant world oil and gas reserves related to naturally fractured carbonate reservoirs adds new frontiers to the development of upscaling and numerical simulation procedures for reducing ...simulation time. This work aims to accurately represent fractured reservoirs in reservoir simulators within a shorter simulation time when compared to dual porosity models, based on special connections between matrix and fracture mediums, both modeled in different grid domains of a single porosity flow model.
For the definition of special connection fracture model (SCFM), four stages are necessary: (a) construction of a single porosity model with two symmetric structural grids, (b) geomodelling of fracture and matrix properties for the corresponding grid domain, (c) application of special connections through the conventional reservoir simulator to represent the fluid transfer between matrix and fracture medium, (d) calculation of the fracture-matrix fluid-transfer. For a proper validation, we apply our methodology in a fractured reservoir type II (tight matrix with flow controlled by fractures) and consider a probabilistic framework regarding geological and dynamic uncertainties.
The probabilistic approach of SCFM under several static uncertainties revealed a good dynamic matching with DP. Under three rock-wettability scenarios (water-wet, oil-wet and intermediate-wet) the dynamic matching with DP is preserved. Furthermore, SCFM did not present convergence issues, considering all probabilistic realizations.
The results revealed that the new method can be applied to commercial flow simulators in fractured reservoirs and it presents itself as a solution to reduce simulation time without disregarding the upscaling and dynamic representation of dual porosity flow models.
•Special connections applied to a single porosity flow model to represent fractured reservoirs.•Solution to reduce simulation time in simulation of fractured reservoirs.•Dynamic performance regarding a matching response with dual porosity flow models.
Brazilian pre-salt oil fields include ultra-deep water reservoirs with high CO2 content and high gas/oil ratio (GOR). For these cases, large volumes of CO2-rich gas reach the topside facilities that ...present limited gas processing capacity. In this context, the production of the oil field is restricted to the maximum gas production capacity of these facilities. The use of a subsea gas-liquid separation (SGLS) and reinjection system may be a solution to boost oil production, as this strategy allows reinjecting part of produced gas directly from the seabed. In this study, we developed a methodology for modeling the subsea separation and reinjection process, which is integrated with a compositional reservoir simulator. A proxy based on an equation of state (EOS) was used for volumetric phase separation in the subsea separator. This approach eliminates the necessity of flash calculation at the SGLS conditions. The methodology makes it possible to assess the potential impact of implementing this technology from a reservoir management perspective. The modeling methodology is applied to a benchmark case (synthetic simulation model representative of a pre-salt reservoir) and evaluated the impact of the SGLS over total production. The results show that the SGLS technology can successfully boost oil production in the context of platform gas production restriction. As soon as the SGLS was implemented, an extended oil production plateau was achieved due to increased gas production capacity. We observed a significant GOR increment in produced fluids during the simulation as a result of gas recycling strategy. This increasing GOR caused the field production to be restricted by maximum gas production constraint most of the time, despite the SGLS implementation. A higher GOR also affects the SGLS performance, increasing the proportion of gas that becomes available for separation at subsea separator conditions. An economic analysis is presented, showing that the SGLS has the potential to increase the financial return of the project. The introduced methodology will enable the inclusion of the subsea separation process in future analyses, paving the way for feasibility assessments and optimization processes for cases in which the SGLS may be an alternative.
•We model the subsea gas-liquid separation (SGLS) and reinjection process in a compositional reservoir simulator.•The presented modeling methodology is applied in a benchmark representative of a Brazilian pre-salt field.•SGLS can boost oil production in a context of limited gas processing capacity, by increasing the total field gas production.•Increasing gas/oil ratio (GOR), due to gas recycling, affects SGLS performance.•SGLS has the potential to improve economic return of the project.
Simulation models of integrated reservoir and production systems are required for a robust production forecast. Traditionally, reservoir and production system models are calibrated against dynamic ...data to establish future boundary conditions. Herein, we propose probabilistic data assimilation for production system models to improve the quality of production forecasts. We used a benchmark case through a reference model, which represents the real field, and a simulation model for (1) sensitivity analysis of production system parameters; (2) adjustment of production system parameters, based on dynamic production history data, to minimize the gap between data and model using an optimization method; and (3) comparison of production forecast in the simulation model, coupled to history-matched and non-matched production systems, and a reference model. Sensitivity analysis of production system parameters indicated a significant impact of the pressure gradient adjustment parameter. But we verified that there were no unique correlations (multiphase flow and fluid) and absolute roughness in the production tubing that fit overall production history, affecting production forecast. Comparing production curves of simulations, coupled with history-matched and non-matched production system models to the reference model, we show that adequately adjusted models are closer to the real model. It is mainly the case for systems with higher capacity, where production is more dependent on the responses of the production system. The probabilistic calibration approach of production systems before integrating reservoir models to adjust production systems simulation models is simple to perform. It can improve the quality of the forecast of the field.
Orientador: Denis José Schiozer
Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica e Instituto de Geociências
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Previous issue date: 2012
Resumo: Várias metodologias de acoplamento entre reservatórios e sistemas de produção têm sido aplicadas na indústria de petróleo nos últimos anos devido à necessidade de modelar adequadamente projetos de produção de petróleo cada vez mais complexos, que envolvem a solução integrada dos modelos que representam o escoamento de fluidos desde o reservatório até a superfície. Estas metodologias são utilizadas para fazer a previsão da produção de múltiplos reservatórios, compartilhando plataformas de produção com capacidades de produção e injeção limitadas gerenciadas por sistemas de produção complexos. Elas podem ser agrupadas em dois tipos básicos: metodologias de acoplamento implícito e explícito. A metodologia explícita é uma possível escolha para integrar simulações porque permite acoplar simuladores distintos para modelar o sistema com um todo adequadamente e também fornecer flexibilidade no estudo de alternativas de gerenciamento de poços. Esta metodologia, contudo, deve ser testada para verificar a qualidade dos resultados e eficiência. Desta forma, um estudo de validação da metodologia de acoplamento explícita é apresentado neste trabalho onde o sistema de produção é testado em condições operacionais comuns durante a produção e injeção de fluidos, verificando vantagens e limitações da metodologia explícita. Alguns métodos para o melhoramento da resposta explícita são propostos e avaliados. Um exemplo de aplicação mostra o ganho na flexibilidade de priorização de poços no gerenciamento de grupo obtido pelo uso de uma metodologia externa ao simulador de reservatórios. O acoplamento explícito, como implementado, mesmo com alguns problemas relacionados a instabilidade da solução numérica em situações específicas, apresentou resultados satisfatórios para a integração entre os simuladores, honrando as restrições operacionais fixadas nos casos de avaliação. Algumas análises em relação ao tempo total de simulação acoplada são apresentadas, mostrando uma não dependência do tamanho do problema em relação ao tempo total gasto
Abstract: Various methodologies to model the coupling of reservoirs and production systems have been applied in the oil industry in recent years due to the need to model properly the integrated solution of models that represent the flow of fluids through the reservoir to the surface. These methodologies are used to forecast production of multiple reservoirs, sharing production facilities with limited capacities ruled by complex systems. They can be grouped into two basic types: implicit and explicit coupling methodologies. Explicit methodology can be an efficient choice to integrate simulations because it allows coupling adequate simulators to model the whole system and also to add flexibility to study well management alternatives. A validation study of explicit coupling methodology is presented in this work where the production system is tested on common operating conditions during production and injection of fluids, verifying benefits and limitations of the methodology. Some methods for improving the explicit response are proposed and evaluated. An example of application verifies the gain of flexibility in well prioritization by the group management obtained by use of an external methodology for reservoir simulator. The explicit coupling, as implemented, even with some problems related to instability of numerical solution in specific situations, has shown a satisfactory result for the integration between the simulators, honoring operating constraints. Some analyses about elapsed time of coupling simulation are shown
Mestrado
Reservatórios e Gestão
Mestre em Ciências e Engenharia de Petróleo
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