... static reservoir models with dynamic flow data are quite time-consuming. Furthermore, numerical flow simulation could provide only approximate solutions to the recovery responses, as numerous simplifications and assumptions must be invoked. This study proposes a workflow integrating artificial...

... dependent on temperature. This work is focused on the temperature dependency of elastic properties of oil sand and its impact on geomechanical responses during a SAGD operation. Coupled geomechanical and fluid flow modeling technique is employed to illuminate the impact of the change in elastic properties...

... and operational constraints representative of Athabasca oil sands reservoirs. The underlying reservoir simulation model is homogeneous, and two-dimensional. Its petrophysical properties, such as the porosity, permeability, initial oil saturation and net pay thickness, have been taken from average values...

...-interpretation criteria, together with model parameter uncertainty due to learning algorithm and initialization on the final ANN predictions. Workflows involving Monte Carlo and bootstrapping methods are applied successfully. A comprehensive uncertainty analysis using an actual SAGD dataset is a novel...

... their effects on SAGD performance; however, a comprehensive and systematic investigation of the heterogeneous distribution (location, continuity, size, and proportions) of shale barriers and lean zones is still lacking. In this study, numerical simulations are used to model the SAGD process. Capillarity...

... dealing with high-dimensional data space consisting of large number of operational and geological parameters. Data-driven modeling techniques, which entail comprehensive data analysis and implementation of machine learning methods for system forecast, provide an attractive alternative. In this paper...

.... Subsequently, we comment on permeability modeling using particle size distribution data and list the techniques available for cleaning and modeling of multivariate PSDs. We document a methodology for accurate modeling of PSDs and provide a workflow for incorporating these data in improved understanding...

... for recovery performance evaluation for SAGD, the simulation process is usually deterministic and computationally demanding, and it not quite practical for real-time decision-making and forecasting. Data mining and machine learning algorithms provide efficient modeling alternatives, particularly when...

..., a full lifecycle methodology is proposed to assess wellbore integrity as a measure of the risk of leakage. The methodology identifies the key elements to model the wellbore element and incorporates the use of a statistical approach to better understand the uncertainty in the risk estimation...