| Title | Reduced Models for Optimizing Well Placement and Scheduling |
|---|---|
| Authors | Rishi ADIGA, John O'SULLIVAN, Andy PHILPOTT |
| Year | 2019 |
| Conference | Stanford Geothermal Workshop |
| Keywords | optimization, reduced model, well placement, scheduling, decision making |
| Abstract | Drilling geothermal wells has a very high capital cost. The location and operation of wells affects their production, so it is important to maximize value from wells by optimizing these decisions. The economic outcomes from particular well placement and operating policies can be estimated using reservoir simulations. A method has been developed to efficiently predict production outcomes from different combinations of possible wells and production starting times, using a relatively small number of reservoir simulations. This can then be used with optimization methods to select the best well locations and production starting times. A Mixed Integer Programming (MIP) model is presented to show this. Binary decision variables were used to select the combination of wells that would maximize total Net Present Value (NPV). Combined this approach provides an efficient method for finding optimal drilling plans, given a calibrated reservoir model. |