Impact of Smart Completions on Optimal Well Trajectories

摘要

• In the planning of new wells, typically the same trajectory is used for conventional wells and wells with smart completions. This study demonstrates that the economically optimized trajectory for smart and conventional wells can be very different. Two new well trajectory optimization algorithms were developed using Stochastic Pattern Search (SPS) principles. In both algorithms random perturbations are made starting from an initial well trajectory, which are sent to a reservoir simulator whereafter the perturbation with the highest Net Present Value (NPV) is selected. New perturbations of the selected well trajectory are made and simulated to, again, select the highest NPV. This process is repeated until a certain stopping criteria is met. The two methods differ in the selection of the perturbations used to initiate the new iteration. In the SPS1 method every subsequent iteration starts from the perturbation with the highest NPV which may be the starting well from the previous iteration. In the SPS2 method the starting well from the previous iteration is excluded. This does not allow the SPS2 method to converge, but it avoids one of the main risks of the SPS1 method, i.e. that the optimization remains stuck in a local optimum. To demonstrate the difference between the optimal well trajectory of well with a conventional and smart completion, both the SPS1 and SPS2 method were evaluated using a realistic, but slightly simplified reservoir model. Both methods were able to optimize the trajectory for both conventional and smart completions. The SPS1 method quickly converged to a local optimum, whilst the SPS2 method was able to determine a trajectory with a significantly higher NPV for both the conventional and smart wells. Moreover, the optimal well trajectory with the smart completion, as found by the SPS2 algorithm, had a NPV that was 40% higher than the optimal trajectory for the conventional completion. It can therefore be concluded that when smart completions are assessed, well trajectory optimization can have very significant value impact and may be crucial in evaluating the full potential of the completion. Furthermore it was shown that, for the example considered, the SPS2 procedure is a good method for well trajectory optimization in a three-dimensional reservoir and although more testing is needed it is believed that is has potential to work with any type of completion.