Short-term supply chain management in upstream natural gas systems

Abstract

Natural gas supply chain planning and optimization is important to ensure security and reliability of natural gas supply. However, it is challenging due to the distinctive features of natural gas supply chains. These features arise from the low volumetric energy density of natural gas and the significance of gas quality and pressure in supply chain operations. Contracts play a central role in the entire supply chain due to high capital cost, specificity and investment risks associated with gas infrastructure. An upstream production planning framework is crucial for supply-side optimization and scenario evaluation in the natural gas supply chain. The technical features of upstream systems imply that the most efficient mode of operation is by single entity central control of the system, while their economics favor involvement of multiple parties in ownership. To resolve this conflict, upstream systems are generally operated by a single operator on the basis of governing rules that stem from agreements between the upstream operator, multiple stakeholders and consumer facilities. These agreements govern production sharing, operational strategy and gas sales in the upstream system. A short-term operational planning framework (with a 2-12 weeks planning horizon) for upstream natural gas systems is presented that can help to maximize production infrastructure utilization and aid in its management, minimize costs and meet production targets while simultaneously satisfying governing rules. Its requirements are inspired by the Sarawak Gas Production System (SGPS), an offshore gas production system in the South China Sea, which supplies the liquefied natural gas (LNG) plant complex at Bintulu in East Malaysia. This is the first attempt to formulate a comprehensive modeling framework for an upstream gas production system that includes a production infrastructure model and a methodology to incorporate governing rules.

(cont.) The model has two components: the infrastructure model is a model of the physical system, i.e., of wells, trunkline network and facilities while the contractual model is a mathematical representation of the governing rules, e.g., production-sharing contracts (PSC), customer specifications and operational rules. The model formulation and objectives are from the perspective of the upstream operator. The infrastructure model incorporates the capability to track multiple qualities of gas throughout the network and determine the optimal routing and blending of gas such that the quality specifications are satisfied at the demand nodes. Nonlinear pressure-flowrate relationships in wells and the network are included for predicting a sufficiently accurate pressure-flowrate profile thereby facilitating implementation of the production strategy on the network. Modeling of complex platform configurations with reversible lines, lines that can be shut-off in normal operation and compression facilities, further improve the realistic representation of the network. A simplified prediction of natural gas liquids (NGL) production is included to maximize NGL revenue. The contractual model represents the framework for modeling the governing rules that are central to the operation of upstream systems. Modeling of productionsharing contracts is a two-fold challenge: accounting for gas volumes and converting the logical rules as stated in the system operations manual to binary constraints. A PSC network representation is proposed to account for gas volumes as well as interactions between different PSC. PSC rules are expressed as logical expressions in terms of availability, priority and transfer Boolean-states, and converted to binary constraints. Additional logical constraints are required to model the inference and intent of the rules. Operational rules can be modeled within the same framework.

(cont.) The resulting mathematical program is a mixed-integer nonlinear program (MINLP) with nonconvex functions and can be solved with the current state-of-the-art global optimization approaches, provided careful attention is paid to the model formulation.A hierarchical multi-objective approach is proposed to address multiple objectives when operating upstream systems, by optimizing a lower priority objective over the multiple optimal solutions of a program with a higher priority objective to obtain a win-win scenario. A reproducible case study that captures all the features of natural gas upstream systems is constructed to facilitate future work in algorithm development for such problems. A preliminary comparison with the existing approach indicates that substantial benefits may be possible by using the proposed approach for short-term planning. The application of a reduced-space global optimization approach to planning in upstream gas networks has also been demonstrated, which can significantly lower the number of variables in the branch-and-bound algorithm. The lower bounding problem is implemented using McCormick (convex) relaxations of computer evaluated functions and solved by implementing a nonsmooth bundle solver as a linearization tool to obtain a linear programming relaxation. The upper bounding problem is implemented using automatic differentiation and a local NLP solver. Branch-and-bound with reduction heuristics and linearization propagation is used for global optimization.This approach has been found to be competitive with current state-of-the-art global optimization algorithms for upstream planning problems.