Natural Gas Value-Chain and Network Assessments

Kobos, Peter H.; Outkin, Alexander V.; Beyeler, Walter E.; Walker, LaTonya Nicole; Malczynski, Leonard A.; Myerly, Melissa M.; Vargas, Vanessa N.; Tenney, Craig M.; Borns, David J.

doi:10.2172/1221180

Title: Natural Gas Value-Chain and Network Assessments

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Abstract

The current expansion of natural gas (NG) development in the United States requires an understanding of how this change will affect the natural gas industry, downstream consumers, and economic growth in order to promote effective planning and policy development. The impact of this expansion may propagate through the NG system and US economy via changes in manufacturing, electric power generation, transportation, commerce, and increased exports of liquefied natural gas. We conceptualize this problem as supply shock propagation that pushes the NG system and the economy away from its current state of infrastructure development and level of natural gas use. To illustrate this, the project developed two core modeling approaches. The first is an Agent-Based Modeling (ABM) approach which addresses shock propagation throughout the existing natural gas distribution system. The second approach uses a System Dynamics-based model to illustrate the feedback mechanisms related to finding new supplies of natural gas - notably shale gas - and how those mechanisms affect exploration investments in the natural gas market with respect to proven reserves. The ABM illustrates several stylized scenarios of large liquefied natural gas (LNG) exports from the U.S. The ABM preliminary results demonstrate that such scenario is likely to have substantialmore »« less

Authors:

Kobos, Peter H. ^[1]; Outkin, Alexander V. ^[1]; Beyeler, Walter E. ^[1]; Walker, LaTonya Nicole ^[1]; Malczynski, Leonard A. ^[1]; Myerly, Melissa M. ^[1]; Vargas, Vanessa N. ^[1]; Tenney, Craig M. ^[1]; Borns, David J. ^[1]

Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

Publication Date:: Tue Sep 01 00:00:00 EDT 2015

Research Org.:: Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

Sponsoring Org.:: USDOE National Nuclear Security Administration (NNSA)

OSTI Identifier:: 1221180

Report Number(s):: SAND2015-7915
603831

DOE Contract Number:: AC04-94AL85000

Resource Type:: Technical Report

Country of Publication:: United States

Language:: English

Citation Formats


                    Kobos, Peter H., Outkin, Alexander V., Beyeler, Walter E., Walker, LaTonya Nicole, Malczynski, Leonard A., Myerly, Melissa M., Vargas, Vanessa N., Tenney, Craig M., and Borns, David J. Natural Gas Value-Chain and Network Assessments.  United States: N. p., 2015. 
        Web.  doi:10.2172/1221180.

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                    Kobos, Peter H., Outkin, Alexander V., Beyeler, Walter E., Walker, LaTonya Nicole, Malczynski, Leonard A., Myerly, Melissa M., Vargas, Vanessa N., Tenney, Craig M., & Borns, David J. Natural Gas Value-Chain and Network Assessments.  United States.  https://doi.org/10.2172/1221180

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                    Kobos, Peter H., Outkin, Alexander V., Beyeler, Walter E., Walker, LaTonya Nicole, Malczynski, Leonard A., Myerly, Melissa M., Vargas, Vanessa N., Tenney, Craig M., and Borns, David J. 2015.  
        "Natural Gas Value-Chain and Network Assessments".  United States.  https://doi.org/10.2172/1221180.  https://www.osti.gov/servlets/purl/1221180.

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@article{osti_1221180,

  title        = {Natural Gas Value-Chain and Network Assessments},

  author       = {Kobos, Peter H. and Outkin, Alexander V. and Beyeler, Walter E. and Walker, LaTonya Nicole and Malczynski, Leonard A. and Myerly, Melissa M. and Vargas, Vanessa N. and Tenney, Craig M. and Borns, David J.},

  abstractNote = {The current expansion of natural gas (NG) development in the United States requires an understanding of how this change will affect the natural gas industry, downstream consumers, and economic growth in order to promote effective planning and policy development. The impact of this expansion may propagate through the NG system and US economy via changes in manufacturing, electric power generation, transportation, commerce, and increased exports of liquefied natural gas. We conceptualize this problem as supply shock propagation that pushes the NG system and the economy away from its current state of infrastructure development and level of natural gas use. To illustrate this, the project developed two core modeling approaches. The first is an Agent-Based Modeling (ABM) approach which addresses shock propagation throughout the existing natural gas distribution system. The second approach uses a System Dynamics-based model to illustrate the feedback mechanisms related to finding new supplies of natural gas - notably shale gas - and how those mechanisms affect exploration investments in the natural gas market with respect to proven reserves. The ABM illustrates several stylized scenarios of large liquefied natural gas (LNG) exports from the U.S. The ABM preliminary results demonstrate that such scenario is likely to have substantial effects on NG prices and on pipeline capacity utilization. Our preliminary results indicate that the price of natural gas in the U.S. may rise by about 50% when the LNG exports represent 15% of the system-wide demand. The main findings of the System Dynamics model indicate that proven reserves for coalbed methane, conventional gas and now shale gas can be adequately modeled based on a combination of geologic, economic and technology-based variables. A base case scenario matches historical proven reserves data for these three types of natural gas. An environmental scenario, based on implementing a $50/tonne CO 2 tax results in less proven reserves being developed in the coming years while demand may decrease in the absence of acceptable substitutes, incentives or changes in consumer behavior. An increase in demand of 25% increases proven reserves being developed by a very small amount by the end of the forecast period of 2025.},

  doi          = {10.2172/1221180},

  url          = {https://www.osti.gov/biblio/1221180},
  journal      = {},
number       = ,

  volume       = ,

  place        = {United States},

  year         = {Tue Sep 01 00:00:00 EDT 2015},

  month        = {Tue Sep 01 00:00:00 EDT 2015}

}

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