Optimizing well placement is one of the primary challenges in oil field development. The number and positions of wells must be carefully considered, as it is directly related to the infrastructure cost and the profits over the field’s life cycle. In this paper, we propose three estimation of distribution algorithms to optimize well placement with the objective of maximizing the net present value. The methods are guided by an elite set of solutions and are able to obtain multiple local optima in a single run. We also present an auxiliary regression model to preemptively discard candidate solutions with poor performance prediction, thus avoiding running computationally expensive simulations for unpromising candidates. The model is trained with the data obtained during the search process and does not require previous training. Our algorithms yielded a significant improvement compared to a state-of-the-art reference method from the literature, as evidenced by computational experiments with two benchmarks.
Tag: Reservoir simulation
Immiscible Viscous Fingering Modeling of Tertiary Polymer Flooding Based on Real Case of Heavy Oil Reservoir Model
In immiscible displacements, lower viscosity injected fluids with higher mobility than crude oil can create viscous fingers, affecting displacement efficiency. The Buckley–Leverett approach for relative permeabilities (kr) may not represent accurately 2D features like increased water saturation in viscous fingering. Based on the physics issue, this work applies Sorbie’s 4-Steps methodology to a 3D simulation of an offshore heavy oil reservoir focusing on waterflooding and tertiary polymer flooding, assessing their impact on oil production forecasts. It also explores the application of this methodology to coarse grid simulation models, employing pseudo kr functions by data assimilation. During tertiary polymer injection, two processes were identified in oil displacement: viscous crossflow mechanism and oil bank mobilization by a second finger. This combination resulted in earlier and increased oil production. For both strategies, refining the grid increased simulation runtime from minutes to days compared to coarse grids, making it impractical for intensive processes. From data assimilation, the best solution with matched field indicators reduced runtime from days to minutes. This study expanded the 4-Steps methodology for 3D reservoir simulation, proposing kr as uncertainties. Data assimilation enhances the methodology, generating pseudo kr for coarser grid simulations, reducing computational costs, and capturing small-scale phenomena.
Integration between experimental investigation and numerical simulation of alkaline surfactant foam flooding in carbonate reservoirs
In Brazil, pre-salt carbonate reservoirs are largely responsible for the current increase in oil production. However, due to its peculiar characteristics, increasing oil recovery by water injection is not enough. Therefore, we seek to evaluate the recovery potential using chemical methods (cEOR). Among these, the Alkali Surfactant Foam (ASF) method appears with high potential, a variant of Alkali Surfactant Polymers (ASP) without the problems presented by it. Therefore, this work presents an innovative methodology, which seeks to evaluate the potential for recovery with ASF in carbonate reservoirs by integrating experimental characterization and recovery prediction using reservoir simulation. For this, phase behavior and adsorption analyses were carried out. The experimental results provided key parameters for the simulation, such as optimal salinity, surfactant adsorption, foam mobility reduction factors. The results are from two case studies of AS and ASF flooding, using a section of UNISIM-II benchmark, using a one-quarter of five-spot model. Having the modelling for these cEOR methods defined, an optimization process for each method was applied, allowing a reliable comparison among the methods and over a base case of water injection, seeking the maximization of the net present value (NPV). As a result, in the experimental part, a low interfacial tension (IFT) value of 0.003 mN/m was achieved with a surfactant adsorption reduction of 17.9% for an optimal setting among brine (NaCl), alkali (NaBO2.4H2O), and surfactant (BIO-TERGE AS 40). In the reservoir simulation part, using a fast genetic algorithm in the optimization process, a NPV of US$ 14.43 million higher than the base case (water injection) and a 4.5% increase in cumulative oil production for the ASF injection case were obtained. Considering the analyses of production curves (cumulative oil production and oil rate) and oil saturation maps, a considerable oil production anticipation was observed, which was the main reason for NPV improvement, proving the high potential for application of the ASF method in carbonate reservoirs.
Model-Based Petroleum Field Management in Three Stages: Life-Cycle, Short-Term, and Real-Time
The objective of this work is to present a new practical methodology to manage petroleum fields considering three stages (life-cycle, short-term, and real-time) that can run alongside different model fidelities and characteristics. The model-based field management process follows the general methodology proposed by Schiozer et al. (2019) with four activities: (1) fit-for-purpose models construction, (2) data assimilation for uncertainty reduction, (3) life-cycle production optimization and (4) short-term optimization for real-time implementation. The selection of the production strategy for field management comprehends the last two activities. Life-cycle optimization is the first stage of the process and generates control setpoints for short-term analysis. Short-term optimization is then used to improve the quality of the solutions considering the control parameters of the next cycle (considering a closed-loop procedure). Real-time solution is then implemented considering operational disturbances from real operations. The methodology was applied to a benchmark case (UNISIM-IV-2026) which is a case based on a typical carbonate field from the Brazilian Pre-salt, with light oil and submitted to Water-Alternate-Gas injection with CO2 (WAG-CO2). The results show that the methodology is applicable to real and complex fields. As the three stages can run simultaneously, one can (1) use different model fidelities to improve the quality of the solutions and (2) use model-based solutions for real-time implementation. Life-cycle optimization using complex simulation models and long-term objectives can run in the background to generate control setpoints for short-term analysis in which lower fidelity models and simplified solutions can be used for the control and field revitalization parameters of each closed-loop cycle. Real-time solutions can be implemented considering operational problems and disturbances. This work presents a novel procedure to integrate three stages for production optimization that can run in parallel, allowing the integration of life-cycle and real-time solutions. The methodology (1) allows the use of complex reservoir simulation models from the life-cycle production strategy optimization, (2) focuses short-term control parameters that improve the quality of the short-term solution, and (3) guides real-time implementation, so it can be the basis to a digital field management.
Binary well placement optimization using a decomposition-based multi-objective evolutionary algorithm with diversity preservation
In binary multi-objective well placement optimization, multiple conflicting objective functions must be optimized simultaneously in reservoir simulation models containing discrete decision variables. Although multi-objective algorithms have been developed or adapted to tackle this scenario, such as the derivative-free evolutionary algorithms, these methods are known to generate a high number of duplicated strategies in discrete problems. Duplicated strategies negatively impact the optimization process since they: (i) degrade the efficiency of recombination operators in evolutionary algorithms; (ii) slow the convergence speed as they require more iterations to find a well-distributed set of strategies; and (iii) perform unnecessary re-evaluations of previously seen strategies through reservoir simulation. To perform multi-objective well placement optimization while avoiding duplicated strategies, this paper investigates the application of a newly proposed algorithm named MOEA/D-NFTS, with a modified diversity preservation mechanism that incorporates prior knowledge of the problem, on a multi-objective well placement optimization problem. The proposed methodology is evaluated on the UNISIM-II-D benchmark case, a synthetic carbonate black-oil simulation model in a well placement optimization problem using a binary strategy representation, indicating the presence or absence of a given candidate well position in the final strategy. The objective functions are the maximization of the Net Present Value, the maximization of the Cumulative Oil Production, and the minimization of Cumulative Water Production. The modified MOEA/D-NFTS performance is compared with a baseline algorithm without diversity preservation, and the evidence shows that the MOEA/D-NFTS produces statistically significant superior results, and is suitable for binary multi-objective well placement optimization.
Comparing WAG-CO 2 injection with continuous water and gas injection in separate wells for the development and management of a CO2-rich light oil fractured carbonate reservoir subject to full gas recycling
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.
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.
Methodology to optimize the WAG-CO2 injection strategy and injection well ICV control rules in light-oil carbonate reservoirs with pre-salt features
Reservoirs of the pre-salt contain a significate amount of CO2 that should not be emitted into the atmosphere. The WAG-CO2 injection process is an alternative to give an ecologically sustainable destination to the CO2 and can increase oil recovery in the pre-salt fields. The optimization of the WAG-CO2 injection scheme, such as cycle duration, can significantly affect its performance in terms of oil recovery and net present value (NPV), raising the need for good optimization methods. In the face of the high uncertainty that typically exists in these scenarios, Inflow Control Valves (ICV) provide operational flexibility to the production strategy, allowing to manage field injection/production more efficiently. This work proposes a methodology to optimize the injection well control variables since the early stages of field development that considers the condition of total gas reinjection (CO2 and natural gas). The methodology optimizes the
opening phase that each well will start injecting during the ramp-up period of the platform, the cycle duration and the phase, gas or water, that each well will inject in the first WAG-CO 2 bank, and the injection wells ICV control rules. The developed methodology was applied to a benchmark case called UNISIM-II-D, based on Brazilian pre-salt trends. Compared to a based injection strategy, the methodology proved capable of improving field management at minimum added cost, increasing oil recovery and the net present value.
A multi-scale mixed method for a two-phase flow in fractured reservoirs considering passive tracer
In this research, the mathematical model represents a two-phase flow in a fractured porous reservoir media, where the Darcy law represents the flow in both fractures and matrix. The flux/pressure of the fluid flow is approximated using a hybridized mixed formulation coupling the fluid in the volume with the fluid flow through th fractures. The spatial dimension of the rock matrix is three and and is coupled with two-dimensional discrete frac- tures. The transport equation is approximated using a lower order finite volume system solved through an upwind scheme. The C++ computational implementation is made using the NeoPZ framework, an object oriented finite element library. The generation of the geometric meshes is done with the software Gmsh. Numerical simulations in 3D are presented demonstrating the advantages of the adopted numerical scheme and these approximations are compared with results of other methods.