In a previous publication we introduced a methodology to assist in choosing between Enhanced Oil recovery (EOR) and infill well drilling (SPE 143300). Operating companies are often reluctant to use EOR techniques when they have the option of infill well drilling instead. Reasons for this include how operating companies assess and manage risk and uncertainties. The methodology developed includes performing reservoir calculations to evaluate additional recovery using both techniques, and then using data generated as input to economic analysis. In the previous work, polymer flooding for 10 years after two years of waterflooding was studied using a synthetic reservoir model. The technique involved running a range of reservoir simulation scenarios to test possible recovery outcomes; these outcomes then provide input data that will be used in the probabilistic economic evaluation tool to be introduced as a follow up in this paper.
This current paper presents the results of the impact of operational factors, such as delaying the start of polymer flooding. This involves assessing the best possible timing for polymer injection to achieve optimal economics. This type of assessment is possible because the economic model developed and presented here allows input from multiple reservoir simulation sensitivity calculations. Monte Carlo Simulation (MCS) is then performed to establish confidence in the method, and test economic uncertainties and the risks associated with implementation of polymer flooding. Defining variables with a probability distribution can establish more precisely the economic value of the polymer flooding project. The analysis of uncertainty involves measuring the degree to which input contributes to uncertainty in the output.
MCS is a statistics based analysis tool that yields probability impact on Net Present Value (NPV) of the key operational parameters included in the project (oil, water and polymer production and injection costs, polymer concentration, timing, etc.) and various economic factors (oil price, polymer cost, etc).