Voidage replacement is a key element in displacement processes, not only for keeping the reservoir pressure at its initial level but also in mitigating surface subsidence in certain fields. Despite its simple definition, it is a complicated process in reservoir management because of uncertainities involved and lack of all required measurements due to economical or technical restrictions. Thus, every single decision parameter and their relative significance in voidage replacement process is important for robust reservoir management. In general, voidage replacement is achieved where injection is based on production. This study investigates the case of triggers where the production rate at the bottom hole conditions is predicated on the bottom hole flowing conditions or reservoir gas injection rate. A full-physics commercial reservoir simulator is coupled with robust optimization software, where a miscible flood operation is modeled with a group bottom hole flowing target coupled with voidage replacement gas and water injection targets. The simulation results of this realistic case is presented in a way to show the relative significance of each operational parameter, which is outlined with tornado charts to serve as a guide in decision making in efficient reservoir management where voidage replacement is a crucial component. It is observed that triggers help to better manage voidage replacement, especially in large reservoirs where reservoir surveillance is a challenge due to number of wells and patterns. The results can be scaled up to different size of reservoirs and patterns with similar recovery processes. This study scrutinizes the feasibility of a reversal of the typical scenario where injection is based on production. Thus, it serves as a useful and realistic example for efficient reservoir management through optimization of voidage replacement through triggers for production rate.
Optimization has become a practical component in decision-making processes in field development and reservoir management. Although optimization simplifies decision-making, it harnesses complex equations and formulations that may be computationally expensive to solve. Numerical reservoir simulation adds another dimension to this phenomenon when combined with optimization software to find the optimum defined by an objective function. Considering the fact that current reservoir simulation models are constructed with vast amount of data and if it is coupled with optimization software, computational limits of regular computers can cause not being able to reach the aimed result although the recent technological development allows running huge reservoir models with parallel computing systems. Consequently, it is inevitable to achieve robust and faster results in optimization problems. Predefined objective functions in optimization software when combined with numerical reservoir simulators attempt to maximize the net present value or cumulative oil recovery defined with an objective function, where the objective function can be defined to be multi-objective leading to Pareto sets consisting of trade-offs between objectives. Using an optimization algorithm with predefined objective functions does not provide the flexibility to the physical reservoir fluid flow phenomenon to "maneuver" throughout the iterations of an optimization process. It is necessary to use a more flexible objective function by introducing conditional statements through procedures. In this study an optimization software is combined with a commercial reservoir simulator. Conditional statements implemented in the simulator as procedures help the software/simulator combination operate under pseudo-dynamic objective functions that lead to speed and robustness through trying sets of combinations of parameters, and thus achieving conditions that lead to highest recovery within the given time frame as defined by the conditional statement for the condition for which the simulation run is performed. The procedures feature enables implementation of codes by using conditional statements that act as piecewise objective functions, maximizing the recovery and taking into account the timeframe or condition they belong. A commercial reservoir simulator is used in this study with conditional statements enhancing production in a given timeframe featuring certain conditions. The optimized recoveries with pseudodynamic objective functions provide an enhanced recovery, as compared to that of an optimization case with predefined constant objective function in the optimization software throughout the iterations of the optimization and simulation process.
Condensate banking results from a combination of factors including fluid properties, formation flow characteristics, and pressures in the formation and wellbore. The production performance may suffer provided these factors are not understood at the beginning of field development. Determining the fluid properties can be vital in any reservoir, hence it plays a crucial role in gas-condensate reservoirs where condensate/gas ratio is significant in estimates for the sales potential of gas and liquid. Once reservoir fluids enter a wellbore both temperature and pressure conditions may change, where condensate liquid can be produced into the wellbore but liquid can also drop out within the wellbore. If the liquid falls back down the wellbore, the liquid percentage will increase and may eventually restrict the production. Thus, it is very important for robust reservoir management that each and every control and uncertainty parameter is understood not only in theory but also in practice with solid examples as done in this study. A robust commercial optimization and uncertainty software is coupled with a full-physics commercial simulator that models the phenomenon so as to investigate the significance of major parameters on performance of gas-condensate reservoirs under recycling. Control and uncertainty variables have been investigated via several simulation runs in specified ranges to represent real reservoir and performance conditions rather than theoretical assumptions. This study aims to prepare an insight into the mechanism of gas injection process in reducing gas-well productivity losses due to condensate blockage in the near wellbore region. The main goal of this work is to investigate gas recycling into the reservoir to enhance condensate recovery. The results show the influence of each control or uncertainty variable, leading to a better understanding of management of gas-condensate reservoirs under gas recycling. Impact of fractures is significant and the tornado diagrams illustrate the relative significance of each factor. The results and sensitivities are compared and discussed in light of a comprehensive literature review of recycling gas-condensate reservoirs with different process optimization methods. The significance of all major parameters are outlined using tornado charts to serve as a practical example for optimization of relevant future applications.
Asphaltene precipitation is caused by numerous factors such as temperature, pressure and compositional vartiations. Drilling, completion, acid stimulation, and hydraulic fracturing activities can also result in settling in the near-wellbore region. Heavier crudes have a fewer precipitation issue becasue of dissolving more asphaltene. Thus, it is crucial to understand the significance of each uncertainty and control variables not only theoretically, but also with application to real-life examples, such as with this model that uses a 32-degree API South American oil to demonstrate the importance of each variable to shed light in order to efficiently manage such reservoirs. A commercial optimization and uncertainty tool is combined with a full-physics commercial simulator, which can create a model to investigate the significance of major factors influencing the performance of wells in temperature-dependent asphaltene precipitation and irreversible flocculation. Temperature-dependent asphaltene precipitation and irreversible flocculation are modelled where no precipitation occurs at the original reservoir temperature, and flocculated asphaltene is allowed to deposit through surface adsorption and pore throat plugging. The exponent in the power law relating porosity reduction to the permeability resistance factor, is modified to change the effect of asphaltene deposition on permeability reduction. Lower temperatures are specified around the wellbore causing asphaltene precipitation. And then, optimization and sensitivity have been performed on major reservoir parameters including well operational parameters, and fluid and rock properties. Moreover, each parameter has been demonstrated in tornado diagrams. It was concluded that employing feasible methods on handling of reservoir uncertainties are as important as management of well operational parameters for effective reservoir management. This study provides an in-depth optimization and uncertainty analysis to outline the significance of each major parameter involved in production performance, and ultimately the recovery efficiency in reservoirs with temperature-dependent asphaltene precipitation and irreversible flocculation.
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