Abstract
Probabilistic assessment of reserves is commonly performed through a series of reservoir simulations over the range of field parameters. In most cases, an exhaustive study of parameter combinations is unfeasible because the number of parameters to be investigated is usually large. Statistical design of experiments (DOE) can be used to select a small number of reservoir simulation runs. The choice of design, especially its ability to capture complex interactions in field parameters, is crucial for DOE to be successful. To this end, we have developed a Scenario Analysis Tool (SAT) using DOE methodology for selecting scenarios to run in 3-D modelling and analyse the resulting reserves values to estimate the ultimate recovery.
The primary goal of SAT is to minimise experimental effort (and cost) by recommending the minimum number of reservoir simulation runs required to accurately estimate uncertainty in hydrocarbon reserves for a given set of uncertainty parameters. The process has three main steps:
specify the uncertainty framework to generate appropriate scenarios;
model scenarios in 3-D simulators and input the response into SAT; and
use SAT to perform the analysis and generate the probabilistic response curve.
SAT is implemented within the Microsoft Excel environment, making it user friendly with simple and intuitive data entry and minimal training requirements. The user is guided by menus and dialog boxes through a few simple sequential steps. SAT output includes reserves estimates, probabilistic response curves, tornado charts, and a comprehensive statistical output. Efficient designs results in a significant reduction in simulation effort for generating the reserves value. Usually, less than 0.1% of possible models need to be simulated and confidence levels are beyond exploration teams' expectations. The capability of SAT will be demonstrated through a number of examples.
