IDEAS home Printed from https://ideas.repec.org/a/igg/jban00/v9y2022i1p1-22.html

Applications of System Dynamics and Big Data to Oil and Gas Production Dynamics in the Permian Basin

Author

Listed:
  • James R. Burns

    (Texas Tech University, USA)

  • Pinyarat Sirisomboonsuk

    (The University of Texas Permian Basin, USA)

Abstract

In this paper, the authors create, justify, and document a system dynamics model of the oil and gas production within the Permian Basin of Texas. Then the researchers show how to fit the model to historical time series data (big data). The authors use the model to better understand the process structure, the production dynamics, and to explore the deleterious consequences of limited pipeline capacity in the Permian Basin. The model is also employed to better understand how to increase revenues derived from the basin. From this model, numerous suggestions are made as to how to improve the overall revenue and profitability coming from the Permian Basin. The model's ultimate purposes and its associated big data are to foster a basic appreciation of the causality inherent in the ‘system' and how basic model parameters affect and influence measures of model performance.

Suggested Citation

  • James R. Burns & Pinyarat Sirisomboonsuk, 2022. "Applications of System Dynamics and Big Data to Oil and Gas Production Dynamics in the Permian Basin," International Journal of Business Analytics (IJBAN), IGI Global Scientific Publishing, vol. 9(1), pages 1-22, January.
    • Handle: RePEc:igg:jban00:v:9:y:2022:i:1:p:1-22
    as

    Download full text from publisher

    File URL: https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijban.314223
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ron Alquist & Lutz Kilian, 2010. "What do we learn from the price of crude oil futures?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 539-573.
    2. Kartik Modi & Harshal Lowalekar & N.M.K. Bhatta, 2019. "Revolutionizing supply chain management the theory of constraints way: a case study," International Journal of Production Research, Taylor & Francis Journals, vol. 57(11), pages 3335-3361, June.
    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. Gary Stading & Maryam Kheirandish & Fred Norton, 2026. "Should the red river be developed: examining this policy question through a bayesian hierarchical model," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 28(1), pages 188-206, March.

    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. Alessandro Paolo Rigamonti & Giulio Greco & Mariarita Pierotti & Alessandro Capocchi, 2024. "Macroeconomic uncertainty and earnings management: evidence from commodity firms," Review of Quantitative Finance and Accounting, Springer, vol. 62(4), pages 1615-1649, May.
    2. Pham T. T. Trinh & Bui T. T. My, 2023. "The impact of world oil price shocks on macroeconomic variables in Vietnam: the transmission through domestic oil price," Asian-Pacific Economic Literature, The Crawford School, The Australian National University, vol. 37(1), pages 67-87, May.
    3. Lutz Kilian, 2010. "Oil Price Shocks, Monetary Policy and Stagflation," RBA Annual Conference Volume (Discontinued), in: Renée Fry & Callum Jones & Christopher Kent (ed.),Inflation in an Era of Relative Price Shocks, Reserve Bank of Australia.
    4. Bouoiyour, Jamal & Selmi, Refk & Tiwari, Aviral Kumar & Shahbaz, Muhammad, 2015. "The nexus between oil price and Russia's real exchange rate: Better paths via unconditional vs conditional analysis," Energy Economics, Elsevier, vol. 51(C), pages 54-66.
    5. Olivier Rousse & Benoît Sévi, 2017. "Informed Trading in Oil-Futures Market," Working Papers hal-01460186, HAL.
    6. Naser, Hanan, 2016. "Estimating and forecasting the real prices of crude oil: A data rich model using a dynamic model averaging (DMA) approach," Energy Economics, Elsevier, vol. 56(C), pages 75-87.
    7. Kyritsis, Evangelos & Serletis, Apostolos, 2018. "The zero lower bound and market spillovers: Evidence from the G7 and Norway," Research in International Business and Finance, Elsevier, vol. 44(C), pages 100-123.
    8. Gilles Dufrénot & William Ginn & Marc Pourroy, 2023. "ENSO Climate Patterns on Global Economic Conditions," AMSE Working Papers 2308, Aix-Marseille School of Economics, France.
    9. Kilian, Lutz & Lee, Thomas K., 2014. "Quantifying the speculative component in the real price of oil: The role of global oil inventories," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 71-87.
    10. Christiane Baumeister & Lutz Kilian, 2015. "Forecasting the Real Price of Oil in a Changing World: A Forecast Combination Approach," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(3), pages 338-351, July.
    11. Guglielmo Maria Caporale & Davide Ciferri & Alessandro Girardi, 2014. "Time-Varying Spot and Futures Oil Price Dynamics," Scottish Journal of Political Economy, Scottish Economic Society, vol. 61(1), pages 78-97, February.
    12. Sallee, James M. & West, Sarah E. & Fan, Wei, 2016. "Do consumers recognize the value of fuel economy? Evidence from used car prices and gasoline price fluctuations," Journal of Public Economics, Elsevier, vol. 135(C), pages 61-73.
    13. A. Anzuini & M. J. Lombardi & P. Pagano, 2013. "The Impact of Monetary Policy Shocks on Commodity Prices," International Journal of Central Banking, International Journal of Central Banking, vol. 9(3), pages 125-150, September.
    14. Degiannakis, Stavros & Filis, George, 2018. "Forecasting oil prices: High-frequency financial data are indeed useful," Energy Economics, Elsevier, vol. 76(C), pages 388-402.
    15. Liu, Yang & Han, Liyan & Xu, Yang, 2021. "The impact of geopolitical uncertainty on energy volatility," International Review of Financial Analysis, Elsevier, vol. 75(C).
    16. Francesco Ravazzolo & Joaquin L. Vespignani, 2015. "A new monthly indicator of global real economic activity," Globalization Institute Working Papers 244, Federal Reserve Bank of Dallas.
    17. Delle Chiaie, S., 2013. "Pétrole et macroéconomie - Synthèse de l’atelier Banque de France du 14 novembre 2012," Bulletin de la Banque de France, Banque de France, issue 192, pages 111-116.
    18. Baumeister, Christiane & Guérin, Pierre & Kilian, Lutz, 2015. "Do high-frequency financial data help forecast oil prices? The MIDAS touch at work," International Journal of Forecasting, Elsevier, vol. 31(2), pages 238-252.
    19. Valenti, Daniele & Bastianin, Andrea & Manera, Matteo, 2023. "A weekly structural VAR model of the US crude oil market," Energy Economics, Elsevier, vol. 121(C).
    20. Christiane Baumeister & Lutz Kilian, 2014. "What Central Bankers Need To Know About Forecasting Oil Prices," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 55(3), pages 869-889, August.

    More about this item

    Statistics

    Access and download statistics

    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:igg:jban00:v:9:y:2022:i:1:p:1-22. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    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.