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Shale gas technology innovation rate impact on economic Base Case – Scenario model benchmarks

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  • Weijermars, Ruud

Abstract

Low gas wellhead prices in North America have put its shale gas industry under high competitive pressure. Rapid technology innovation can help companies to improve the economic performance of shale gas fields. Cash flow models are paramount for setting effective production and technology innovation targets to achieve positive returns on investment in all global shale gas plays. Future cash flow of a well (or cluster of wells) may either improve further or deteriorate, depending on: (1) the regional volatility in gas prices at the wellhead – which must pay for the gas resource extraction, and (2) the cost and effectiveness of the well technology used. Gas price is an externality and cannot be controlled by individual companies, but well technology cost can be reduced while improving production output. We assume two plausible scenarios for well technology innovation and model the return on investment while checking against sensitivity to gas price volatility. It appears well technology innovation – if paced fast enough – can fully redeem the negative impact of gas price decline on shale well profits, and the required rates are quantified in our sensitivity analysis.

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  • Weijermars, Ruud, 2015. "Shale gas technology innovation rate impact on economic Base Case – Scenario model benchmarks," Applied Energy, Elsevier, vol. 139(C), pages 398-407.
    • Handle: RePEc:eee:appene:v:139:y:2015:i:c:p:398-407
    DOI: 10.1016/j.apenergy.2014.10.059
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    References listed on IDEAS

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    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. Weijermars, Ruud, 2013. "Economic appraisal of shale gas plays in Continental Europe," Applied Energy, Elsevier, vol. 106(C), pages 100-115.
    3. Weijermars, Ruud, 2011. "Can we close Earth's sustainability gap?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4667-4672.
    4. Philipp M. Richter, 2015. "From Boom to Bust? A Critical Look at US Shale Gas Projections," Economics of Energy & Environmental Policy, International Association for Energy Economics, vol. 0(Number 1).
    5. Weijermars, Ruud, 2014. "US shale gas production outlook based on well roll-out rate scenarios," Applied Energy, Elsevier, vol. 124(C), pages 283-297.
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    Cited by:

    1. Wei, Yi-Ming & Kang, Jia-Ning & Yu, Bi-Ying & Liao, Hua & Du, Yun-Fei, 2017. "A dynamic forward-citation full path model for technology monitoring: An empirical study from shale gas industry," Applied Energy, Elsevier, vol. 205(C), pages 769-780.
    2. Zhang, Qi & Li, Zhan & Wang, Ge & Li, Hailong, 2016. "Study on the impacts of natural gas supply cost on gas flow and infrastructure deployment in China," Applied Energy, Elsevier, vol. 162(C), pages 1385-1398.
    3. Jong-Hyun Kim & Yong-Gil Lee, 2017. "Analyzing the Learning Path of US Shale Players by Using the Learning Curve Method," Sustainability, MDPI, vol. 9(12), pages 1-8, December.
    4. Niu, Wente & Lu, Jialiang & Sun, Yuping & Zhang, Xiaowei & Li, Qiaojing & Cao, Xu & Liang, Pingping & Zhan, Hongming, 2024. "Techno-economic integration evaluation in shale gas development based on ensemble learning," Applied Energy, Elsevier, vol. 357(C).
    5. Wang, Ke & Li, Haitao & Wang, Junchao & Jiang, Beibei & Bu, Chengzhong & Zhang, Qing & Luo, Wei, 2017. "Predicting production and estimated ultimate recoveries for shale gas wells: A new methodology approach," Applied Energy, Elsevier, vol. 206(C), pages 1416-1431.
    6. Zou, Youqin & Yang, Changbing & Wu, Daishe & Yan, Chun & Zeng, Masun & Lan, Yingying & Dai, Zhenxue, 2016. "Probabilistic assessment of shale gas production and water demand at Xiuwu Basin in China," Applied Energy, Elsevier, vol. 180(C), pages 185-195.
    7. Jin, Xu & Wang, Xiaoqi & Yan, Weipeng & Meng, Siwei & Liu, Xiaodan & Jiao, Hang & Su, Ling & Zhu, Rukai & Liu, He & Li, Jianming, 2019. "Exploration and casting of large scale microscopic pathways for shale using electrodeposition," Applied Energy, Elsevier, vol. 247(C), pages 32-39.
    8. Ahn, Yuchan & Kim, Junghwan & Kwon, Joseph Sang-Il, 2020. "Optimal design of supply chain network with carbon dioxide injection for enhanced shale gas recovery," Applied Energy, Elsevier, vol. 274(C).

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