Skip to main content

Elastic Oil: A Primer on the Economics of Exploration and Production

  • Chapter
  • First Online:
Energy, Natural Resources and Environmental Economics

Part of the book series: Energy Systems ((ENERGY))

Abstract

Predictions from the original geophysical approach to oil exploration and production suggest that oil production will develop according to a predetermined and inflexible bell-shaped trajectory, quite independent of variables relating to technological development, economics, and policy. Exploring the potential sources of elasticity in oil reserves and production, this paper offers a modification to the geophysical approach. Based on economic theory and modern empirical research the results suggest that both reserve-generation and production are indeed influenced by factors and forces of technology, economics, and government regulation.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    The so-called Hubbert’s peak was (quite successfully) applied to predict that US oil production would reach its maximum around 1970. The same concept has inspired the current debate of Peak Oil, with high-spirited discussions about when the world’s oil production will peak.

  2. 2.

    A popular analogy is found in the classic board game “Battleship”. In the early phases of the game, with many ships on the board, expected rewards from bombing are high, with major learning effects involved whenever a new ship is hit. However, expected marginal gains, as well as learning effects, drop towards the end of the game, when the majority of ships have been sunk.

  3. 3.

    According to BP’s Statistical Review of World Energy 2007.

  4. 4.

    According to BP’s Statistical Review of World Energy 2007.

  5. 5.

    See Smith (2005) for a critical overview of empirical studies of OPEC behavior.

  6. 6.

    Capital requirement along the value chain include investments in exploration activities, field development, efforts to increase oil recovery, processing and transport facilities, and potentially also marketing activities.

  7. 7.

    A non-commercial discovery (Balder) was actually made by Exxon (Esso) already in 1967. However, it took 30 years of technological development to mature this discovery into a profitable field development project based on subsea templates tied back to a floating production and storage vessel. The Balder field was put on stream in 1999 and is still producing (mid 2008).

  8. 8.

    An exploration play is a geographically bounded area where a combination of geological factors suggests that producible petroleum can be discovered. The three most important factors are (1) a reservoir rock where petroleum can be preserved, (2) a tight geological structure (a trap) that covers the reservoir rock, and (3) a mature source rock containing organic material that can be converted into petroleum (:̧def :̧def Norwegian Petroleum Directorate 2007).

  9. 9.

    In testing of statistical hypotheses, the probability value (p-value) of a parameter estimate represents the likelihood of obtaining a result as extreme as the one obtained through our estimation, given that the null hypothesis is through. In our notation (p = 0. 00), the implication is not that the p-value of this parameter estimate is actually 0, but that it fails to break zero at the two-digit cutoff level of measurement.

  10. 10.

    As opposed to frontier exploration areas, mature areas are typically characterized by proven exploration models, producing fields, well-developed infrastructure, transport facilities and market access. Moreover, exploration activities in these areas are usually directed at smaller satellite fields which can be tied back to already producing facilities of larger reservoirs (in decline), without the large investments involved by stand-alone field developments in new oil and gas regions (:̧def :̧def Norwegian Petroleum Directorate 2007).

  11. 11.

    With a long-term perspective on the production process, all inputs may be seen as variable. Consequently, the capital stock can be included in both the L and the H vector, depending on the horizon of the decisions in question.

  12. 12.

    To test the validity of this assumption, a variety of interest rate and labor cost variables were included in preliminary estimations. However, plausible and robust estimates could not be established for any of their coefficients.

  13. 13.

    The error-correction specification would normally also include changes in model variables. However, these proved insignificant in preliminary estimations, and are therefore left out for simplicity of exposition. The constant term is also removed for the same reason.

  14. 14.

    Letting all changes approach zero, (4) can be solved for q t to obtain \(\alpha = -{b}_{0}/\lambda \), \(\beta = -{b}_{1}/\lambda \), \(\gamma = -{b}_{2}/\lambda \) (Bårdsen 1989).

  15. 15.

    R 2 also has a range of weaknesses with respect to model evaluation. The inclusion of additional variables will never reduce the value of R 2, and it may improve even if nonsense variables are adjoined. Moreover, R 2 also depends on the choice of transformation of the dependent variable (for example, Δy versus y). R 2 may therefore be misleading for model evaluation purposes.

References

  • Alhajji, A. F., & Huettner, D. (2000). The target revenue model and the world oil market: empirical evidence from 1974 to 1994. The Energy Journal, 21(2), 121–144.

    Article  Google Scholar 

  • Aune, F. R., Mohn, K., Osmundsen, P., & Rosendahl, K. E. (2007). Industry restructuring, OPEC response – and oil price formation. Discussion Paper 511, Research Department of Statistics, Norway.

    Google Scholar 

  • Boone, J. P. (1998). The effect of the corporate alternative minimum tax on investment in oil and gas exploration and development. Journal of Energy Finance and Development, 3(2), 101–128.

    Article  Google Scholar 

  • Bårdsen, G. (1989). Estimation of long-run coefficients in error-correction models. Oxford Bulletin of Economics and Statistics, 51, 345–350.

    Article  Google Scholar 

  • Cleveland, C. J., & Kaufmann, R. K. (1991). Forecasting ultimate oil recovery and its rate of production: incorporating economic factors into the models of M. King Hubbert. The Energy Journal, 12(2), 17–46.

    Google Scholar 

  • Cleveland, C. J., & Kaufmann, R. K. (1997). Natural gas in the U.S.: how far can technology stretch the resource base? The Energy Journal, 18(2), 89–107.

    Google Scholar 

  • Dahl, C., & Duggan, T. E. (1998). Survey of price elasticities from economic exploration models of US oil and gas supply. Journal of Energy Finance and Development, 3(2), 129–169.

    Article  Google Scholar 

  • Dornik, J. A., & Hendry, D. F. (2001). Modelling dynamic systems using PCGive 10. London: TCL.

    Google Scholar 

  • Farzin, Y. H. (2001). The impact of oil prices on additions to US proven reserves. Resource and Energy Economics, 23, 271–291.

    Article  Google Scholar 

  • Fattouh, B. (2006). OPEC pricing power. Working Paper 31, Oxford Institute for Energy Studies (http://www.oxfordenergy.org/pdfs/WPM31.pdf).

  • Fisher, F. M. (1964). Supply and costs in the U.S. oil and gas industry: two econometric studies. Baltimore: Johns Hopkins Press.

    Google Scholar 

  • Forbes, K. F., & Zampelli, E. M. (2000). Technology and the exploratory success rate in the U.S. offshore. The Energy Journal, 21(1), 109–120.

    Google Scholar 

  • Forbes, K. F., & Zampelli, E. M. (2002). Technology and the exploratory success rate in the U.S. onshore. Quarterly Journal of Economics and Finance, 42(2), 319–334.

    Google Scholar 

  • Glomsrød, S., & Osmundsen, P. (2005). Petroleum industry regulation within stable states. Aldershot: Ashgate.

    Google Scholar 

  • Hubbert, M. K. (1962). Energy resources: a report to the committee on natural resources of the National Academy of Sciences. Washington: National Research Council. Publication 1000-D. National Academy of Sciences-National Research Council.

    Google Scholar 

  • Iledare, O. O. (1995). Simulating the effect and policy incentives on natural gas drilling and gross reserve additions. Resource and Energy Economics 17, 261–279.

    Article  Google Scholar 

  • Iledare, O. O., & Pulsipher, A. (1999). Sources of change in petroleum drilling productivity in onshore Lousiana in the US, 1977–1994. Energy Economics, 21, 261–271.

    Article  Google Scholar 

  • Johansen, S. (1995). Likelihood-based inference in cointegrated vector auto-regressive models. Oxford: Oxford University Press.

    Book  Google Scholar 

  • Kaufmann, R. K. (1991). Oil production in the lower 48 states: reconciling curve fitting and econometric models. Resources and Energy, 13, 111–127.

    Article  Google Scholar 

  • Kaufmann, R. K., & Cleveland, C. J. (2001). Oil production in the lower 48 states: economic, geological, and institutional determinants. The Energy Journal, 22(1), 27–49.

    Article  Google Scholar 

  • Krautkraemer, J. A. (1998). Nonrenewable resource scarcity. Journal of Economic Literature, 36, 2065–2107.

    Google Scholar 

  • Lynch, M. (2002). Forecasting oil supply: theory and practice. The Quarterly Review of Economic and Finance, 42, 373–389.

    Article  Google Scholar 

  • Managi, S., Opaluch, J. J., Jin, D., & Grigalunas, T. A. (2005). Technological change and petroleum exploration in the Gulf of Mexico. Energy Policy, 33(5), 619–632.

    Article  Google Scholar 

  • Ministry of Petroleum and Energy. (2008). Facts 2008: The Norwegian petroleum sector (http://www.petrofacts.no).

  • Mohn, K., & Osmundsen, P. (2008). Exploration economics in a regulated petroleum province: the case of the Norwegian Continental Shelf. Energy Economics, 30(2), 303–320.

    Article  Google Scholar 

  • Mohn, K. (2008). Efforts and efficiency in oil exploration: a vector error-correction approach. The Energy Journal, 29(4), 53–78.

    Article  Google Scholar 

  • Moroney, J. R., & Berg, M. D. (1999). An integrated model of oil production. The Energy Journal, 20(1), 105–124.

    Article  Google Scholar 

  • Norwegian Petroleum Directorate. (2007). The petroleum resources on the NCS 2007 (http://www.npd.no/English/Frontpage.htm).

  • Osmundsen, P., Mohn, K., Misund, B., & Asche, F. (2007). Is oil supply choked by financial markets? Energy Policy 35, 467–474.

    Article  Google Scholar 

  • Pesaran, M. H., & Samiei, H. (1995). Forecasting ultimate resource recovery. International Journal of Forecasting, 11, 543–555.

    Article  Google Scholar 

  • Quyen, N. V. (1991). Exhaustible resources: a theory of exploration. Review of Economic Studies, 58, 777–789.

    Article  Google Scholar 

  • Ramcharran, H. (2002). Oil production responses to price changes: an empirical application of the competitive model to OPEC and non-OPEC countries. Energy Economics, 24, 97–106.

    Article  Google Scholar 

  • Reiss, P. C. (1990). Economic and financial determinants of oil and gas exploration. In M. K. Hubbard, & R. Glenn (Eds.), Asymmetric information, corporate finance and investment. Chicago: University of Chicago.

    Google Scholar 

  • Reynolds, D. B. (2002). Using non-time series to determine supply elasticity: how far do prices change the Hubbert curve? OPEC Review, 26(2), 147–167.

    Article  Google Scholar 

  • Ringlund, G. B., Rosendahl, K. E., & Skjerpen, T. (2008). Does oilrig activity react to oil price changes? – An empirical investigation. Energy Economics, 30(2), 371–396.

    Article  Google Scholar 

  • Smith, J. L. (2005). Inscrutable OPEC? Behavioral tests of the cartel hypothesis. Energy Journal, 26(1), 51–82.

    Google Scholar 

  • Watkins, G. C. (2002). Characteristics of North Sea oil reserve appreciation. The Quarterly Review of Economics and Finance, 22, 335–372.

    Article  Google Scholar 

  • Watkins, G. C. (2006). Oil scarcity: what have the past three decades revealed? Energy Policy, 34, 508–514.

    Article  Google Scholar 

  • Watkins, C. J., & Streifel, S. S. (1998). World crude oil supply: evidence from estimating supply functions by country. Journal of Energy Finance and Development, 3(1), 23–48.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Klaus Mohn .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Mohn, K. (2010). Elastic Oil: A Primer on the Economics of Exploration and Production. In: Bjørndal, E., Bjørndal, M., Pardalos, P., Rönnqvist, M. (eds) Energy, Natural Resources and Environmental Economics. Energy Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12067-1_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-12067-1_3

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12066-4

  • Online ISBN: 978-3-642-12067-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics