450737 Optimization Models for Shale Gas Development Planning: A Real-World Marcellus Shale Case Study

Sunday, November 13, 2016: 4:46 PM
Monterey I (Hotel Nikko San Francisco)
Markus G. Drouven and Ignacio E. Grossmann, Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA

 Optimization Models for Shale Gas Development Planning:  

A Real-World Marcellus Shale Case Study

Markus G. Drouven1 and Ignacio E. Grossmann2

Department of Chemical Engineering

Carnegie Mellon University

Pittsburgh, PA 15213

 

1mdrouven@cmu.edu, 2grossmann@cmu.edu

 

Abstract

The production of shale gas from unconventional resource plays is transforming the energy landscape in the United States. Advances in production technologies, notably the dual application of horizontal drilling and hydraulic fracturing, allow the extraction of vast deposits of trapped natural gas that, until recently, were uneconomic to produce. The Energy Information Administration predicts that shale gas will account for 50% of total U.S. natural gas production by 2040 [1]. Natural gas demand is also expected to increase in the electric power and nearly all other industrial sectors. The future development of shale gas resources requires an extensive expansion of the existing gas production, transmission, and processing infrastructure. Virtually all stages of the shale gas supply chain need to be expanded and upgraded to match the ever growing natural gas supply and demand [2]. Since the necessary capital investments for drilling rigs, pipelines, boosting stations and midstream processing facilities are substantial, the long-term planning of upstream production and natural gas transmission is a key challenge.

In this presentation we address a real-world case study for which the general problem can be stated as follows. Within a potential shale gas development area an upstream operator has identified a set of candidate well pads from which shale gas may or may not be extracted. To extract the gas the operator can develop, i.e., drill and fracture a limited number of wells at every candidate pad. Ultimately, the operator wishes to sell extracted gas at a set of downstream delivery nodes which are typically located along interstate transmission pipelines. For this purpose a gathering system superstructure has been identified. This superstructure specifies all feasible, alternative options for laying out gathering pipelines to connect candidate well pads with the given set of delivery nodes. In addition, the superstructure indicates candidate locations for compressor stations as well as the location of existing processing plants.

The long-term shale gas development problem involves planning, design and strategic decisions. In terms of planning decisions the operator needs to decide: a) where, when and how many wells to drill at every candidate well pad, b) whether selected wells should be shut-in and, if so, for how long, and c) how to allocate drilling rigs over time. The design decisions involve: a) where to lay out gathering pipelines, b) what size pipelines to install, c) where to construct compressor stations, and d) how much compression power to provide. The upstream operator’s objective is to determine the optimal development strategy by making the right planning and design decisions such that the net present value is maximized. 

In this work [3] we present a real-world Marcellus Shale case study that was performed in close collaboration with the EQT Corporation. EQT is one of the largest exploration and production operators in the Appalachian Basin. Their business activities include locating productive natural gas deposits, drilling wells to extract gas and transporting gas through pipelines to transmission and distribution system. The objective of this case study was twofold: (a) validate and refine the proposed modeling framework and (b) attempt to quantify the economic potential of mixed-integer optimization models for long-term shale gas development planning.

As part of a “lookback analysis” the proposed model was applied to an existing gathering system in the Appalachian Basin – owned and operated by the EQT Corporation – using real, historic data. By comparing the development strategy proposed by the optimization with the actual, historic development strategy, we are able to demonstrate and quantify the economic potential of optimization tools for shale gas development. Our findings suggest, in the past, development strategies were primarily driven by trying to drill as many wells as possible at a given location and turning them in line as quickly as possible. However, considering the characteristically steep decline curves of shale gas wells we find that these development strategies led to gathering equipment – including pipelines and compressors – being over-sized and therefore heavily under-utilized over long periods of time.

Our optimization, on the other hand, reveals that so-called return-to-pad operations appear much more suitable and economically promising for shale gas development projects. The idea behind return-to-pad operations is to drill and complete only a small number of wells at a time, but then to “return to the pad” eventually to repeat the process. This strategy allows upstream operators to size gathering pipelines and compressor smaller and to keep them “full”, i.e., utilized, over extended periods of time.

Our comprehensive economic analysis reveals that return-to-pad operations and an increased equipment utilization could have improved the profitability of this particular development project by several million U.S. dollars. To the best of our knowledge this is the first case study that provides such deep and realistic insight into past and future shale gas development strategies in collaboration with a major natural gas producer.

 

 

References

[1] U.S. Energy Information Administration (EIA). Annual Energy Outlook with Projections to 2040. April 2013.

[2] Goellner, J. F. Expanding the Shale Gas Infrastructure. AIChE CEP August 2012, 49-52.

[3] Drouven, M. G.; Grossmann, I. E. Multi-Period Planning, Design and Strategic Models for Long-Term Quality-Sensitive Shale Gas Development. AIChE J. 2016 (accepted for publication).


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