Real-time Optimal Resource Allocation in an Industrial Symbiotic Network using Transient Measurements

Offshore oil and gas production network often comprises of one or more groups of production wells producing from different reservoir sections, with shared resources. We consider the problem of gas-lift optimization, where the lift-gas (which is a shared resource) must be optimally allocated among the wells operated by different companies. The production optimization problem with shared gas-lift resource is solved as a distributed optimization problem using Lagrangian decomposition to limit information sharing among the different subsystems and enable industrial symbiosis. However, when solving steady-state real-time optimization, a fundamental limiting factor is the steady-state wait time associated with the online model adaptation. The result is suboptimal operation during transients because we discard large chunks of transient measurement data. To address the steady-state wait time issue, we propose to update the model of each subsystem using dynamic models and transient measurements, and the distributed optimization is performed using the corresponding updated steady-state models. Using simulation results, we show that the proposed distributed RTO approach using transient measurements enable optimal resource allocation among the different subsystems.