A Comprehensive Techno-Economic Framework for Shale Gas Exploitation and Distribution in the United States

Over the past years, shale gas has turned into one of the most significant sources of energy in the United States. Technological advancements have provided the energy industry with the necessary tools to allow the economic exploitation of an enormous volume of natural gas trapped in shale formations. This has boosted the domestic gas production and generated a boom in other sectors of the economy in the country. However, major challenges are involved in the development of shale gas resources. A drastic decline of wells’ productivity, the costs involved in the gas production and distribution facets, and the volatile behavior of the energy market represent some of the complexities faced by a gas operator. In this context, the utilization of a comprehensive frameworks to analyze and develop long-term strategies can represent a meaningful supporting tool for shale gas operators. The main objective of this research work is the development and implementation a novel techno-economic framework for the optimal exploitation and delivery of shale gas in the United States. The proposed framework is based on an interdisciplinary approach that combines data driven techniques, petroleum engineering practices, reservoir simulations and mathematical programming methods. Data analysis algorithms are implemented to guide the decision-making processes involved in the unconventional reservoir and define the predominant trends of certain exogenous parameters of the system. Petroleum engineering practices and reservoir simulation models are required for a realistic description of the formations and the proper definition of strategies to extract the gas from the shale rock. Finally, the mathematical programming is required for describing the surface facilities design and operations to ensure the allocation of the shale gas in the different commercialization points. The output of this framework will provide the optimal operations and infrastructure by maximizing the net present value (NPV). To demonstrate the efficacy of the proposed decision-making structure, a case study based on the liquid-rich region of the Marcellus play is considered in this work. The application of the proposed framework depicts the influence of reservoir complexities and external factors in establishing optimal strategic decisions for the exploitation, processing and allocation of shale gas. The coordination of the different facets including the drilling and completion activities and the design and operation of the surface facilities has a key role in maintaining the economy of a shale gas venture above its economic threshold

Modeling the Crude Oil Scheduling Problem with Integration with Lower Level Production Optimization and Uncertainty

This research is focused on the modeling and optimization of the crude oil scheduling problem in order to generate the most appropriate schedule for the unloading, charging, blending, and movement of crude oil in a refinery, which means obtaining the schedule that generates the lowest costs. Uncertainty, which is often present in these types of optimization problems, is also analyzed and taken into account for the resolution of crude oil scheduling problem. A comprehensive novel model is proposed to describe the upper level crude oil scheduling problem, generate an optimal solution for the mentioned problem, and allow integration with the lower level production optimization problem of a refinery. This integration is possible due to the consideration of total flows of the different types of crude oil instead of flows of a particular key component in the crude oil to linearize the upper level problem and generate a less complex model. The proposed approach incorporates all the logistical costs including the sea waiting, unloading and inventory costs together with the costs associated with the transfer of crude oil from one to another entity. Moreover, this model also offers the possibility of considering multiple tank types including storage and blending tanks throughout the supply chain and the incorporation of the capability of storing more than one crude oil type in the storage tanks during the schedule horizon. A comparative analysis is performed against other models proposed and preliminary results of integration with a lower operational level are provided. In order to take into account the possibility of uncertainty or fuzziness in the scheduling problem, for the first time an approach is proposed to face the resolution of this problem in order to obtain a more realistic scheduling of the allocations of crude oil. Fuzzy linear programming theory is used here to represent this uncertainty in order to find an optimal solution that takes into account the lack of precise information on the part of the decision maker without losing the linearity of the original system. Uncertainty in the minimum demand to be satisfied in the distillation unit according to the necessities of the market and the lack of precise information about certain costs involved in the operations throughout the supply chain are separately considered. Among the different approaches utilized in fuzzy linear programming, the flexible programming or Zimmermann method and its extension to fuzziness in objective functions are implemented. A comparison between the two cases studied and the crisp model is performed with the aim of determining the effect of these uncertainties in the schedule of the crude oils movements between the different entities in the supply chain and the total cost generated