IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v93y2015ip2p1581-1594.html
   My bibliography  Save this article

Optimal dynamic allocation of mobile plants to monetize associated or stranded natural gas, part I: Bakken shale play case study

Author

Listed:
  • Tan, Siah Hong
  • Barton, Paul I.

Abstract

Associated or stranded natural gas presents a challenge to monetize due to its low volume and lack of supporting infrastructure. Recent proposals for deploying mobile, modular plants, such as those which perform GTL (gas-to-liquids) conversion or produce LNG (liquefied natural gas) on a small scale, have been identified as possible attractive routes to gas monetization. However, such technologies are yet unproven in the marketplace. To assess their potential, we propose a multi-period optimization framework which determines the optimal dynamic allocation and operating decisions for a decision maker who utilizes mobile plants to monetize associated or stranded gas. We then apply this framework to a case study of the Bakken shale play. Our framework is implemented to determine the optimal NPV (net present value) which would be realized over a twenty-year time frame. Sensitivity studies on the technology costs and conversion inputs conclude that the profitability and viability of mobile technologies remain valid for a wide range of possible inputs.

Suggested Citation

  • Tan, Siah Hong & Barton, Paul I., 2015. "Optimal dynamic allocation of mobile plants to monetize associated or stranded natural gas, part I: Bakken shale play case study," Energy, Elsevier, vol. 93(P2), pages 1581-1594.
    • Handle: RePEc:eee:energy:v:93:y:2015:i:p2:p:1581-1594
    DOI: 10.1016/j.energy.2015.10.043
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544215014115
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2015.10.043?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Gülen, Gürcan & Browning, John & Ikonnikova, Svetlana & Tinker, Scott W., 2013. "Well economics across ten tiers in low and high Btu (British thermal unit) areas, Barnett Shale, Texas," Energy, Elsevier, vol. 60(C), pages 302-315.
    2. Martín, Mariano & Grossmann, Ignacio E., 2013. "Optimal use of hybrid feedstock, switchgrass and shale gas for the simultaneous production of hydrogen and liquid fuels," Energy, Elsevier, vol. 55(C), pages 378-391.
    3. Ikonnikova, Svetlana & Gülen, Gürcan & Browning, John & Tinker, Scott W., 2015. "Profitability of shale gas drilling: A case study of the Fayetteville shale play," Energy, Elsevier, vol. 81(C), pages 382-393.
    4. Bischi, Aldo & Taccari, Leonardo & Martelli, Emanuele & Amaldi, Edoardo & Manzolini, Giampaolo & Silva, Paolo & Campanari, Stefano & Macchi, Ennio, 2014. "A detailed MILP optimization model for combined cooling, heat and power system operation planning," Energy, Elsevier, vol. 74(C), pages 12-26.
    5. Ashouri, Araz & Fux, Samuel S. & Benz, Michael J. & Guzzella, Lino, 2013. "Optimal design and operation of building services using mixed-integer linear programming techniques," Energy, Elsevier, vol. 59(C), pages 365-376.
    6. Kim, Jong Suk & Edgar, Thomas F., 2014. "Optimal scheduling of combined heat and power plants using mixed-integer nonlinear programming," Energy, Elsevier, vol. 77(C), pages 675-690.
    7. Rieder, Andreas & Christidis, Andreas & Tsatsaronis, George, 2014. "Multi criteria dynamic design optimization of a small scale distributed energy system," Energy, Elsevier, vol. 74(C), pages 230-239.
    8. Knudsen, Brage Rugstad & Whitson, Curtis H. & Foss, Bjarne, 2014. "Shale-gas scheduling for natural-gas supply in electric power production," Energy, Elsevier, vol. 78(C), pages 165-182.
    9. Pousinho, H.M.I. & Silva, H. & Mendes, V.M.F. & Collares-Pereira, M. & Pereira Cabrita, C., 2014. "Self-scheduling for energy and spinning reserve of wind/CSP plants by a MILP approach," Energy, Elsevier, vol. 78(C), pages 524-534.
    10. Kaiser, Mark J., 2012. "Profitability assessment of Haynesville shale gas wells," Energy, Elsevier, vol. 38(1), pages 315-330.
    11. Madzharov, D. & Delarue, E. & D'haeseleer, W., 2014. "Integrating electric vehicles as flexible load in unit commitment modeling," Energy, Elsevier, vol. 65(C), pages 285-294.
    12. Cristóbal, Jorge & Guillén-Gosálbez, Gonzalo & Kraslawski, Andrzej & Irabien, Angel, 2013. "Stochastic MILP model for optimal timing of investments in CO2 capture technologies under uncertainty in prices," Energy, Elsevier, vol. 54(C), pages 343-351.
    13. Ommen, Torben & Markussen, Wiebke Brix & Elmegaard, Brian, 2014. "Comparison of linear, mixed integer and non-linear programming methods in energy system dispatch modelling," Energy, Elsevier, vol. 74(C), pages 109-118.
    14. Mitra, Sumit & Sun, Lige & Grossmann, Ignacio E., 2013. "Optimal scheduling of industrial combined heat and power plants under time-sensitive electricity prices," Energy, Elsevier, vol. 54(C), pages 194-211.
    15. J. David Hughes, 2013. "A reality check on the shale revolution," Nature, Nature, vol. 494(7437), pages 307-308, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hong, Bingyuan & Cui, Xuemeng & Peng, Donghua & Zhou, Mengxi & He, Zhouying & Yao, Hanze & Xu, Yupeng & Gong, Jing & Zhang, Hongyu & Li, Xiaoping, 2024. "Distributed or centralized? Long-term dynamic allocation and maintenance planning of modular equipment to produce multi-product natural gas based on life cycle thinking," Energy, Elsevier, vol. 288(C).
    2. Kim, Juwon & Seo, Youngkyun & Chang, Daejun, 2016. "Economic evaluation of a new small-scale LNG supply chain using liquid nitrogen for natural-gas liquefaction," Applied Energy, Elsevier, vol. 182(C), pages 154-163.
    3. Eduardo Alarcon-Gerbier & Zarina Chokparova & Nassim Ghondaghsaz & Wanqi Zhao & Hani Shahmoradi-Moghadam & Uwe Aßmann & Orçun Oruç, 2022. "Software-Defined Mobile Supply Chains: Rebalancing Resilience and Efficiency in Production Systems," Sustainability, MDPI, vol. 14(5), pages 1-21, February.
    4. Allman, Andrew & Zhang, Qi, 2020. "Dynamic location of modular manufacturing facilities with relocation of individual modules," European Journal of Operational Research, Elsevier, vol. 286(2), pages 494-507.
    5. Crow, Daniel J.G. & Giarola, Sara & Hawkes, Adam D., 2018. "A dynamic model of global natural gas supply," Applied Energy, Elsevier, vol. 218(C), pages 452-469.
    6. Tan, Siah Hong & Barton, Paul I., 2017. "Optimal shale oil and gas investments in the United States," Energy, Elsevier, vol. 141(C), pages 398-422.
    7. Hong, Bingyuan & Li, Xiaoping & Song, Shangfei & Chen, Shilin & Zhao, Changlong & Gong, Jing, 2020. "Optimal planning and modular infrastructure dynamic allocation for shale gas production," Applied Energy, Elsevier, vol. 261(C).
    8. Tan, Siah Hong & Barton, Paul I., 2016. "Optimal dynamic allocation of mobile plants to monetize associated or stranded natural gas, part II: Dealing with uncertainty," Energy, Elsevier, vol. 96(C), pages 461-467.
    9. Hong, Bingyuan & Cui, Xuemeng & Wang, Bohong & Fan, Di & Li, Xiaoping & Gong, Jing, 2022. "Long-term dynamic allocation and maintenance planning of modular equipment to enhance gas field production flexibility," Energy, Elsevier, vol. 252(C).
    10. Wen, Kai & Lu, Yangfan & Lu, Meitong & Zhang, Wenwei & Zhu, Ming & Qiao, Dan & Meng, Fanpeng & Zhang, Jing & Gong, Jing & Hong, Bingyuan, 2022. "Multi-period optimal infrastructure planning of natural gas pipeline network system integrating flowrate allocation," Energy, Elsevier, vol. 257(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Santos, Maria Izabel & Uturbey, Wadaed, 2018. "A practical model for energy dispatch in cogeneration plants," Energy, Elsevier, vol. 151(C), pages 144-159.
    2. Tunstall, Thomas, 2015. "Iterative Bass Model forecasts for unconventional oil production in the Eagle Ford Shale," Energy, Elsevier, vol. 93(P1), pages 580-588.
    3. Svetlana Ikonnikova and Gürcan Gülen, 2015. "Impact of low prices on shale gas production strategies," The Energy Journal, International Association for Energy Economics, vol. 0(Adelman S).
    4. Mikkola, Jani & Lund, Peter D., 2016. "Modeling flexibility and optimal use of existing power plants with large-scale variable renewable power schemes," Energy, Elsevier, vol. 112(C), pages 364-375.
    5. Qin, Chun & Wang, Linqing & Han, Zhongyang & Zhao, Jun & Liu, Quanli, 2021. "Weighted directed graph based matrix modeling of integrated energy systems," Energy, Elsevier, vol. 214(C).
    6. Zeng, Yujiao & Xiao, Xin & Li, Jie & Sun, Li & Floudas, Christodoulos A. & Li, Hechang, 2018. "A novel multi-period mixed-integer linear optimization model for optimal distribution of byproduct gases, steam and power in an iron and steel plant," Energy, Elsevier, vol. 143(C), pages 881-899.
    7. Moradi, Saeed & Khanmohammadi, Sohrab & Hagh, Mehrdad Tarafdar & Mohammadi-ivatloo, Behnam, 2015. "A semi-analytical non-iterative primary approach based on priority list to solve unit commitment problem," Energy, Elsevier, vol. 88(C), pages 244-259.
    8. Shang, Ce & Srinivasan, Dipti & Reindl, Thomas, 2017. "Generation and storage scheduling of combined heat and power," Energy, Elsevier, vol. 124(C), pages 693-705.
    9. Nwulu, Nnamdi I. & Xia, Xiaohua, 2015. "Implementing a model predictive control strategy on the dynamic economic emission dispatch problem with game theory based demand response programs," Energy, Elsevier, vol. 91(C), pages 404-419.
    10. Bai, Yang & Zhong, Haiwang & Xia, Qing & Kang, Chongqing & Xie, Le, 2015. "A decomposition method for network-constrained unit commitment with AC power flow constraints," Energy, Elsevier, vol. 88(C), pages 595-603.
    11. Muhammad Ahmed & Sina Rezaei-Gomari, 2018. "Economic Feasibility Analysis of Shale Gas Extraction from UK’s Carboniferous Bowland-Hodder Shale Unit," Resources, MDPI, vol. 8(1), pages 1-17, December.
    12. Montgomery, J.B. & O’Sullivan, F.M., 2017. "Spatial variability of tight oil well productivity and the impact of technology," Applied Energy, Elsevier, vol. 195(C), pages 344-355.
    13. Capone, Martina & Guelpa, Elisa & Verda, Vittorio, 2021. "Multi-objective optimization of district energy systems with demand response," Energy, Elsevier, vol. 227(C).
    14. Ikonnikova, Svetlana & Gülen, Gürcan & Browning, John & Tinker, Scott W., 2015. "Profitability of shale gas drilling: A case study of the Fayetteville shale play," Energy, Elsevier, vol. 81(C), pages 382-393.
    15. Ferrari, Lorenzo & Esposito, Fabio & Becciani, Michele & Ferrara, Giovanni & Magnani, Sandro & Andreini, Mirko & Bellissima, Alessandro & Cantù, Matteo & Petretto, Giacomo & Pentolini, Massimo, 2017. "Development of an optimization algorithm for the energy management of an industrial Smart User," Applied Energy, Elsevier, vol. 208(C), pages 1468-1486.
    16. Wu, Chenyu & Gu, Wei & Xu, Yinliang & Jiang, Ping & Lu, Shuai & Zhao, Bo, 2018. "Bi-level optimization model for integrated energy system considering the thermal comfort of heat customers," Applied Energy, Elsevier, vol. 232(C), pages 607-616.
    17. Saussay, Aurélien, 2018. "Can the US shale revolution be duplicated in continental Europe? An economic analysis of European shale gas resources," Energy Economics, Elsevier, vol. 69(C), pages 295-306.
    18. Arsalan Najafi & Mousa Marzband & Behnam Mohamadi-Ivatloo & Javier Contreras & Mahdi Pourakbari-Kasmaei & Matti Lehtonen & Radu Godina, 2019. "Uncertainty-Based Models for Optimal Management of Energy Hubs Considering Demand Response," Energies, MDPI, vol. 12(8), pages 1-20, April.
    19. Berrada, Asmae & Loudiyi, Khalid & Zorkani, Izeddine, 2016. "Valuation of energy storage in energy and regulation markets," Energy, Elsevier, vol. 115(P1), pages 1109-1118.
    20. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "A review of uncertainty characterisation approaches for the optimal design of distributed energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 258-277.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:93:y:2015:i:p2:p:1581-1594. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.