Within the context of infrastructure and economic systems analysis, we define resilience as follows: given the occurrence of a particular disruptive event, the resilience of a system to that event is the ability to efficiently reduce both the magnitude and duration of the deviation from targeted system performance levels. We propose a new methodology, originating from optimal control applications, for measuring system resilience. The approach is demonstrated through application to a national petrochemical supply chain model.

The San Juan Basin, located in northwestern New Mexico and southwestern Colorado, produces natural gas from oil, gas, and coalseam wells. Because of abundant natural gas supply and price discounts relative to other natural gas trading hubs, the San Juan Basin is an attractive location to establish greenfield manufacturing of value-added chemicals from locally produced natural gas. To assess the viability of manufacturing different types of chemicals, agent-based models of three chemical markets were created to simulate historical market operation in the United States. Using the agent-based models, potential market share of a greenfield plant in the San Juan Basin is estimated. The historical market models show that world-scale production of urea or polypropylene could be achieved by a manufacturing plant in the San Juan Basin. Production of propylene in the region likely could not sustain world-scale production, even with improvements in local transportation infrastructure connections.

This report gives an overview of the types of economic methodologies and