| dc.description.abstract | This study proposes a probabilistic decision-making support model (“Green Tree”), created in Microsoft Excel, to assist operators of marginal assets in prioritizing well workover decisions. Such a tool can help operators of legacy, low volume oil and gas assets to maximize their asset value by allocating capital towards the best well workover options to achieve equitable production increases. The framework for this model was constructed by following interventions taken in a marginal oil field in the Permian Basin from the time it was acquired in 2013 through 2016. The Green Tree decision model quantifies historic uncertainty in outcomes and uses the probabilistic present values of all interventions to display the optimum path value in a decision tree. Relatively few inputs are needed for the decision tree to show an optimum intervention path. These inputs include historic production data for the field, service costs for each wellbore workover, anticipated production increase from each workover, and expected probabilities for each intervention based off of the operator’s historical results. Once the inputs have been entered, the user is able to manually adjust the projected commodity prices and see the corresponding changes in the optimum path value. The Green Tree is applied to the Permian basin asset to identify the optimum sequence of interventions, revealing the risk adjusted upside to the base case PV10 for the field calculated in the workbook. A summation of the expected monetary values (EMVs) from several interventions can be used to estimate the total upside value to the asset owner. The tool developed here may benefit marginal well producers in evaluating asset value when looking at an acquisition or divestiture. Lastly, posterior probabilities can be used in this model as the results of actual workovers in the field are examined, adjusting the tree in real time to account for any changes in the outcome of probabilities or production responses. | en |
