Abstract
Three methods are proposed for quickly evaluating the history match of a numerical simulation to actual reservoir performance. All of the methods rely on computing a set of deviation values, each of which is defined to be a calculated simulator result minus the corresponding surveillance measurement value.
For any particular type of surveillance data, such as rates, watercuts, or gas-oil ratios, the deviation values can be grouped by well, by area, or combining all measurements in the database. The first two proposed methods rely on simple graphical presentations of each group of deviation values to show how well the simulation results match the surveillance data. Plotting together the results from more than one simulation run allows a quick comparison of the match for each run, which is useful during the history match process.
The third method converts each deviation value to a quantity called Match Factor, which is a relative measure of the confidence that the simulator actually reproduced the particular reservoir performance at the time the surveillance measurement was made. Weighted-average Match Factors can reveal the degree of match by well, by area, and by data type.
These techniques are especially valuable when matching reservoirs with a large volume of surveillance data. They can help focus the history matching process by identifying areas less well matched. They can identify when the history matching process is not significantly improving the match and can stop.
