Abstract
Well testing may be performed to support many decisions including ones related to production optimization of an oil production system. In production optimization information such as gas oil ratio and water cut/water oil ratio is used to decide on, for example, which wells to prioritize for choking back/opening to avoid over-/underutilization of the production capacity. Since the reservoir properties change with time, the uncertainties of their estimated values increase with time, and eventually a new well test will be required. As the uncertainty in the estimates grows, so does the risk for prioritizing the wrong well(s) giving lower oil production rate than possible. A computer program is developed to decide which well to test based on historical test data. The program uses a Monte Carlo approach for identifying which well test is likely to lead to highest increase in the total oil production rate after the well test information is utilized to optimize the oil production. The computer program is applied to field data quantifying the benefits when applied to this specific field.
