Over 80% of the vast reserves of Alberta's oil sands can be produced only by using in situ recovery methods. Among them, which is likely the most efficient and important, is the Steam-Assisted Gravity Drainage (SAGD) process. Numerical simulation allows for a practical way of predicting reservoir performance using the SAGD process during the whole field development cycle. However, in the earlier stages of development studies, when it is necessary to undertake preliminary engineering design, estimate reserves, evaluate the project against other SAGD prospects, as well as consider the uncertainty of some reservoir parameters, it may not be feasible to do a detailed simulation study due to the long computational time involved in a SAGD process simulation.
Under these circumstances, a method for predicting reservoir performance using a simple statistical model that can approximate the reservoir simulator over a given range of some important input parameters is a good approach to provide the means of comparison and preliminary predictions without resorting to numerical simulation.
The purpose of this work is to use 'experimental design' techniques to develop a response surface that can predict SAGD performance without the expense of doing simulation. A preliminary screening study was done in order to select the most influential variables on SAGD performance. The variables used for that purpose include reservoir rock/fluid properties, such as reservoir thickness, porosity, vertical permeability, horizontal-vertical permeability ratio, methane content, rock thermal conductivity, initial oil saturation and bitumen viscosity, along with SAGD design and operating variables, including spacing between injector/producer, operating pressure, preheating period, maximum steam injection rate and SAGD well pattern spacing.
In a second stage, the influential variables were used to create a statistically significant correlation by using the experimental design method and response surface techniques. This simple model allows the prediction of the SAGD performance in terms of maximum net present value (NPV) over 15 years of project life, for a given range of the most influential parameters.
Numerical simulation of complex systems such as SAGD processes require long computational times due to the compositional nature and transient temperature behaviour of the models used in the solution. Longer simulation times lead to either a delay in the decision-making process or to biased forecasts and sub-optimal decisions, since unpractical times would be required to span all possible scenarios in which a SAGD process can be developed. This is particularly important at the earliest field development stages when the high uncertainty of some reservoir and operational parameters is a significant constraint. Transference of uncertainty from the reservoir and operational parameters to the forecast variables during a SAGD process using numerical simulation is almost an impossible and very expensive task.
To overcome this situation, engineers need simple models to predict SAGD performance. As an alternative, this work proposes a "Response Surface Correlation" generated by experimental design techniques and response surface methodology. Such a correlation will substitute the reservoir simulator in a given operating domain in order to account for all necessary cases needed to quantify and transfer the reservoir uncertainty to a SAGD performance variable.