Optimization of Well Placement for Geological CO2 Storage to Minimize Fault Slip Tendency

Geological carbon storage is an important technology for reducing CO2 emissions to the atmosphere. Storage operations can be improved by using computational optimization to maximize effectiveness and minimize harmful impacts. In this work, we apply the Stanford Unified Optimization Framework to determine the placement of injection wells for a CO2 storage project. The simulation model includes a heterogeneous storage aquifer along with a large surrounding region, caprock, and basement rock. The storage aquifer contains two major faults. Fault slippage and seismicity can occur if the injection operation alters the stress state such that the fault slip tendency (FST) exceeds a particular value. The goal of the optimizations in this study is the minimization of the maximum FST observed along either fault in the model. The constraints imposed on the problem ensure that wells are spaced more than 1km apart, that the target amount of CO2 is injected, and that all injected CO2 remains within the storage aquifer. The simulation of the CO2 storage process is accomplished using a fully-coupled flow and geomechanical formulation in GEOS. A Differential Evolution optimization algorithm is applied to determine the locations of three injection wells, each injecting 1.5 Mt/year for 50 years. The optimization framework is shown to provide field development scenarios with maximum FST that is less than that achieved in a set of heuristic injection well designs. The optimal solutions also satisfy all constraints, in contrast to the heuristic configurations.