Optimal Resource Allocation for Parallel Reservoir Simulation

Abstract

Over the past few decades, the oil and gas (O&G) industry has become heavily dependent on parallel scientific computing. The turnaround time of such applications depends heavily on the amount of resources dedicated to the task. Increasing the number of compute processes for the same job tends to produce diminishing returns, and does not always guarantee an increase in performance of a justified impact. This point describes scalability limits, which this work aims to avoid surpassing. An algorithm is presented in which a reservoir simulation run automatically adjusts and finds the optimal resources, which leads to improved performance, and the efficient utilization of compute resources, resulting in significant cost savings.