Integrated Production Optimization and Surface Facilities Management through Advanced Optimization Techniques

摘要

The Production Optimization is one of the most complex and multi-disciplinary task in the oil&gas industry from an operational point of view: it involves the surface asset during all its production life and requires a continuous improvement process. In the gathering facilities and process plant engineering design, the optimization is driven by inputs that are subjected, during the asset life, to changes; this fact, coupled to improvements and modifications in surface facilities, creates the necessity to manage and optimize production scenarios with a more frequent time-frame. Technology improvements have enabled a widespread use of integrated simulation models for a better asset management to be fully combined with measured field data. In this paper we present a dedicated workflow for surface facilities - gathering system and process plant - production enhancement and management coupled with an advanced optimization technique based on a powerful algorithm. The main feature of this algorithm - and consequently of the proposed workflow - is the ability to control many variables simultaneously according to the system constraints even with complex, conflicting and non-direct interconnections between them and the objective to be reached. It has been proven that this algorithm has a robust practice that detects the global optimum of the feasible area avoiding a premature stop in a local optimum region, a situation quite common in highly- constrained and non-linear optimization problems in oil&gas industry. The technical contributions of the work are the abilities to support operations in: definition of field potential, production optimization and de-bottlenecking activities. In the paper a case study, based on a highly-constrained field with gas treating limitations, is reported and the proposed workflow's results are compared with another integrated optimization available from other software, showing an improved ability to detect global optimum combining well management to the plant capabilities.