Many projects in the Brazilian pre-salt assume the use of water alternating gas (WAG-CO2) injection as an ecologically safe carbon storage strategy, with improved hydrocarbon recovery. However, studies that compare these advantages with a simpler management plan are not common. The objective of this work is to compare WAG-CO2 injection with continuous injection of water and gas (CIWG) rich in CO2 in separate wells for the development and management of a light-oil fractured carbonate reservoir subject to full gas recycling. We employed the UNISIM-II benchmark model, a naturally fractured carbonate reservoir with Brazilian pre-salt characteristics, which enables an application in controlled environment where the reference response is known (UNISIM-II-R). We used a model-based decision analysis for production strategy selection, hierarchical optimization of the decision variables and algorithms to maximize the objective function. Representative models (RM) are selected from the ensemble of models and used to incorporate the effects of geological, reservoir, and operational uncertainties into the optimization process. The net present value is the objective function during the nominal optimization of candidate strategies of each RM and the expected monetary value and risk analysis are considered to select the final production strategy considering uncertainties. The risk analysis was quantified based on downside risk and upside potential relation to a benchmark return. We optimized two alternative development plans (one considering WAG-CO2 injection and the other continuous injection of water and gas in separate wells) and compared their performance indicators and decision variables, including design variables (number, type and placement of well, and size of production facilities) and life-cycle control rules (management of equipment over time). We then applied a cross-simulation, where the best strategy optimized for one recovery method was applied to the other and the injection strategy was optimized again. We were therefore able to assess the need to pre-define the recovery method before defining design variables to validate the flexibility of each strategy for possible future changes in the recovery mechanism. Finally, we repeated the study for different reservoir scenarios to compare the alternatives considering typical uncertainties of the Brazilian pre-salt and validated the final strategies in the reference model to quantify the real value in decision making. The strategies reached a full gas recycling in both recovery methods and allowed a comparison of their advantages and disadvantages. The operations of WAG-CO2 injection can be more complex and the equipment more expensive. The novelty of this work is the consideration of continuous injection of water and gas in separate wells as a simpler alternative to the development and management of pre-salt oil fields, since this method may also meet operators’ and environmental demands, bearing simpler operating challenges and promoting good recovery and profitability.
Tag: equation of state
Model-Based Life-Cycle Optimization for Field Development and Management Integrated with Production Facilities
Reservoir simulation models often support decision making in the development and management of petroleum fields. The process is complex, sometimes treated subjectively, and many methods and parameterization techniques are available. When added to uncertainties, the lack of standardized procedures may yield largely suboptimal decisions. In this work, we present a comprehensive outline for model-based life-cycle production optimization problems, establishing guidelines to make the process less subjective. Based on several applications and a literature review, we established a consistent methodology by defining seven elements of the process: (1) the degree of fidelity of reservoir models; (2) objective function (single- or multi-objective, nominal or probabilistic); (3) integration between reservoir and production facilities (boundary conditions, IPM); (4) parametrization (design, control and revitalization optimization variables); (5) monitoring variables (for search space reduction); (6) optimization method, including optimizer/ algorithm, search space exploration, faster-objective function estimators (coarse models, emulators, others), type of ensemble-based optimization (robust or nominal based on representative models); (7) additional improvements (value of information and flexibility). With an application on a publicly available benchmark reservoir, this work shows how a model-based life-cycle optimization process can be systematically defined. In this initial work, the focus is the field development phase and some simplifications were made due to the high computational demand, but in future works we plan to address the control and revitalization variables and reduce the number of simplifications to compare. The optimization results are analyzed to understand the evolution of the objective function and the evolution of the optimization variables. We also discuss the importance of including uncertainties in the process and we discuss future work to emphasize the difference between life-cycle (control rules) and short-term (effective control) management of equipment, as well as ways to deal with the computational intensity of the problem, such as the combined use of representative models and fast simulation models.