Improved Well Boundary Conditions: Automated Adaptation of Numerical Well Controls in Reservoir Simulation Models

Wells in reservoir simulation models are set using constant boundary conditions. This results in producers being shut due to high water or gas production. In actual field operations, well flow rates and pressures are adjusted to control high water and gas production. This thesis introduces a novel yet simple method that automates adaptation of well conditions to the dynamic wellbore or near wellbore (reservoir) performance. The adaptive conditions algorithm was incorporated within a developed 3D three-phase black-oil reservoir simulator. Several 1D wellbore model candidates were compared against 3D computational fluid dynamics models in predicting published two-phase pipe flow results. Improvement in oil recovery, increase in well operational lifetime, and reduction in produced water and gas were all observed when using adaptive well controls. This thesis can result in a positive outlook when assessing business plans compared to the cost associated with early abandonment of wells. One of the many advantages of this methodology is the reduction in number of variables for optimization studies due to the elimination of rate control steps. Methods of maximizing reservoir net present value via production rate optimizations are limiting. The optimization problem requires setting the variables beforehand and doing so limits solutions to a predefined number of rate changes at exact and specific times. Integrating adaptive well controls to an optimization study increased convergence rates and enhanced the optimized solution. This is due to the well rates being able to automatically adapt to reservoir/well performances thereby having unbounded access to rate changes which would have been numerically expensive to include in rate optimization setups. Comparison of conversion times showed that optimization runs using adaptive well conditions converging earlier than the base case. Furthermore, the adaptive case required less than half the number of generations to produce an improved maximum NPV compared the base case. Several studies were performed using a three-phase reservoir model with six production wells and seven water injectors. In all optimization cases, the maximum NPV for the respective base model was consistently lower than the NPV of the first generation for all the different adaptive rate models