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Iterative Bass Model forecasts for unconventional oil production in the Eagle Ford Shale


  • Tunstall, Thomas


Developing long-term forecasts for unconventional oil, gas and condensate production has challenged both analysts and academics because the shale revolution is still in its relatively early stages. Initial estimates of URR (ultimately recoverable reserves) in the Eagle Ford appear to have been too low. In this paper, forecast accuracy using limited early data of oil and condensate production in the Eagle Ford has been improved over OLS (ordinary least squares) methods using a Bass Diffusion Model that could be applicable to other shale field developments in the U.S., and eventually in other countries as well. Using only preliminary production data from 2006 through 2010, a Bass Model yields more accurate early predictions than conventional, bottom-up, data/labor-intensive OLS regression approaches. Further, the Bass Model suggests that in the absence of the recent oil price decline, the Eagle Ford oil and condensate production could have reached as high as 2.6 million barrels per day by 2020, significantly above a recent energy industry analyst prediction of 2 million barrels, and far higher than OLS regression forecasts that ranged from between 450,000 and 1.4 million barrels per day.

Suggested Citation

  • Tunstall, Thomas, 2015. "Iterative Bass Model forecasts for unconventional oil production in the Eagle Ford Shale," Energy, Elsevier, vol. 93(P1), pages 580-588.
  • Handle: RePEc:eee:energy:v:93:y:2015:i:p1:p:580-588
    DOI: 10.1016/

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    References listed on IDEAS

    1. Kinnaman, Thomas C., 2011. "The economic impact of shale gas extraction: A review of existing studies," Ecological Economics, Elsevier, vol. 70(7), pages 1243-1249, May.
    2. Tunstall, Thomas, 2015. "Recent Economic and Community Impact of Unconventional Oil and Gas Exploration and Production on South Texas Counties in the Eagle Ford Shale Area," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 45(1).
    3. David C. Schmittlein & Vijay Mahajan, 1982. "Maximum Likelihood Estimation for an Innovation Diffusion Model of New Product Acceptance," Marketing Science, INFORMS, vol. 1(1), pages 57-78.
    4. Frank M. Bass & Trichy V. Krishnan & Dipak C. Jain, 1994. "Why the Bass Model Fits without Decision Variables," Marketing Science, INFORMS, vol. 13(3), pages 203-223.
    5. McGlade, Christophe & Speirs, Jamie & Sorrell, Steve, 2013. "Unconventional gas – A review of regional and global resource estimates," Energy, Elsevier, vol. 55(C), pages 571-584.
    6. 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.
    7. McGlade, Christophe & Speirs, Jamie & Sorrell, Steve, 2013. "Methods of estimating shale gas resources – Comparison, evaluation and implications," Energy, Elsevier, vol. 59(C), pages 116-125.
    8. 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.
    9. Roger Bentley & Godfrey Boyle, 2008. "Global Oil Production: Forecasts and Methodologies," Environment and Planning B, , vol. 35(4), pages 609-626, August.
    10. Gracceva, Francesco & Zeniewski, Peter, 2013. "Exploring the uncertainty around potential shale gas development – A global energy system analysis based on TIAM (TIMES Integrated Assessment Model)," Energy, Elsevier, vol. 57(C), pages 443-457.
    11. Ren, Jingzheng & Tan, Shiyu & Goodsite, Michael Evan & Sovacool, Benjamin K. & Dong, Lichun, 2015. "Sustainability, shale gas, and energy transition in China: Assessing barriers and prioritizing strategic measures," Energy, Elsevier, vol. 84(C), pages 551-562.
    12. V. Srinivasan & Charlotte H. Mason, 1986. "Technical Note—Nonlinear Least Squares Estimation of New Product Diffusion Models," Marketing Science, INFORMS, vol. 5(2), pages 169-178.
    13. Brandt, Adam R., 2010. "Review of mathematical models of future oil supply: Historical overview and synthesizing critique," Energy, Elsevier, vol. 35(9), pages 3958-3974.
    14. Weber, Jeremy G., 2012. "The effects of a natural gas boom on employment and income in Colorado, Texas, and Wyoming," Energy Economics, Elsevier, vol. 34(5), pages 1580-1588.
    15. 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.
    16. Roger Bentley & Godfrey Boyle, 2008. "Global oil production: forecasts and methodologies," Environment and Planning B: Planning and Design, Pion Ltd, London, vol. 35(4), pages 609-626, July.
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