Design of Solvent-Assisted SAGD Processes in Heterogeneous Reservoirs Using Hybrid Optimization Techniques

Abstract

Summary Numerous steam-assisted gravity-drainage (SAGD) optimization studies published in the literature combined numerical simulation with graphical or analytical techniques for design and performance evaluation. Efforts have integrated the simulation exercise with global optimization algorithms. Some studies focused on optimization of cumulative steam/oil ratio (cSOR) in SAGD by altering steam-injection rates, while others focused on optimization of net cumulative energy/oil ratio (cEOR) in solvent-additive SAGD by altering injection pressures and fraction of solvent in the injection stream. Several studies also considered total project net-present-value (NPV) calculation by changing total project area, capital-cost intensities, solvent prices, and risk factors to determine the well spacing and drilling schedule. Optimization techniques commonly used in those studies were scattered search, simulated annealing, and genetic algorithm (GA). However, applications of hybrid GA were rarely found. In this paper, we focused on optimization of solvent-assisted SAGD using various GA implementations. In our models, hexane was selected to be coinjected with steam. The objective function, defined on the basis of cSOR and recovery factor, was optimized by changing injection pressures, production pressures, and injected solvent/steam ratio. Techniques, including orthogonal arrays (OA) for experimental design (e.g., Taguchi's arrays) and proxy models for objective-function (F) evaluations, were incorporated with the GA method to improve computational and convergence efficiency. Results from these hybrid approaches revealed that an optimized solution could be achieved with less central-processing-unit time (e.g., fewer number of iterations) compared with the conventional GA method. Sensitivity analysis was also conducted on the choice of proxy model to study the robustness of the proposed methods. To investigate the effects of heterogeneity in the design process, optimization of solvent-assisted SAGD was performed on various synthetic heterogeneous reservoir models of porosity, permeability, and shale distributions. Our results highlight the potential application of the proposed techniques in other solvent-enhanced heavy-oil-recovery processes.

Quick Screening of Pareto-Optimal Operating Conditions for Expanding Solvent–Steam Assisted Gravity Drainage Using Hybrid Multi-Objective Optimization Approach

“…Subsequently, the proxy models were adopted as the objective estimators of NSGA-II in the proposed framework. Figure 6 shows the response surface plots of the three performance indicators corresponding to the four levels of Tinj (6,12,18, and 24 months) in variable-objective space. The x-axis, the y-axis, and the z-axis indicate Pinj, Sfrac, and the performance indicator, respectively.…”

“…A larger amount of steam injected at a higher injection pressure caused an increasing trend of cSOR. A longer duration of steam injection without solvent caused the decrease in RF and the increase in both cSOR and SR. Figure 7 shows the response surface plots of the three performance indicators corresponding to the four levels of Tinj (6,12,18, and 24 months) in three-dimensional objective space. The boundary of Table 6 presents the optimization setting used for executing NSGA-II in the proposed hybrid framework.…”

“…Proxies have also been investigated to alleviate computation costs accompanied with computationally intensive thermal reservoir simulation runs. Al-Gosayir et al [18] implemented a hybrid technique that combined GA with a response surface model. The optimization works above have found the operating condition compromising bitumen recovery and energy efficiency due to the form of objective functions.…”

In-situ recovery of heavy-oil from fractured carbonate reservoirs: Optimization of steam-over-solvent injection method

“…With so many operating parameters, a remarkably large number of scenarios need to be tested to reach an optimal solution, which would be very exhaustive to accomplish manually. Therefore, in this paper, we tested a hybrid optimization technique introduced in our previous publication for ES-SAGD optimization (Al-Gosayir et al 2011b, 2012a to propose optimal application conditions that maximized the recovery and profit for the SOS-FR method. This approach was first tested to optimize the heavy oil recovery by SOS-FR method for single well (huff-and-puff) applications in our previous publication (Al-Gosayir et al 2013).…”

Real-time reservoir model updating in thermal recovery: Application of analytical proxies and Kalman filtering

“…To design solvent-assisted SAGD process in heterogeneous reservoirs Al-Gosayir et al (2012) proposed a hybrid genetic algorithm to build their proxy for optimization purposes. In another study, Ghasemi and Whitson (2011) used an isothermal black-oil simulator to calibrate an analytical proxy for modeling the SAGD process.…”