Abstract
In the long-term, changes in oil prices will certainly have an impact on the estimate of the project income, investment and costs, the variables are not mutually independent, but there is a correlation. Traditional economic evaluation methods tend to ignore the influence of parameter correlation, resulting in project evaluation deviations. In this article, we assume that oil prices obey geometric Brownian motion and mean-reverting stochastic process separately, taking into account the correlation between oil prices and operational costs, using the Monte Carlo model to simulate the project value and risk under different probability. The results show that if the linkage mechanism of the oil prices and operational costs is not considered, it is easy to overestimate the risk of the project, which leads to some feasible projects excluded.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Dixit, A., Pindyck, R. S., & Sødal, S. (1999). A markup interpretation of optimal investment rules. The Economic Journal, 109(455), 179–189.
Willigers, B. J., Begg, S., & Bratvold, R. B. (2014). Combining geostatistics with bayesian updating to continually optimize drilling strategy in shale-gas plays. SPE Reservoir Evaluation & Engineering, 17(04), 507–519.
Zhu, L., Zhang, Z., & Fan, Y. (2015). Overseas oil investment projects under uncertainty: How to make informed decisions? Journal of Policy Modeling, 37(5), 742–762.
Willigers, B. J. (2009). Enhanced economic modeling by correlated stochastic models of E&P costs and hydrocarbon prices: The limitations of fixed price decks and the versatility of least-squares Monte Carlo simulation. In EUROPEC/EAGE Conference and Exhibition. Society of Petroleum Engineers.
Hurst, A., Brown, G. C., & Swanson, R. I. (2000). Swanson’s 30-40-30 rule. AAPG Bulletin, 84(12), 1883–1891.
Acknowledgments
Funding for this work was supported by International Science and technology support program (2014BAC01B02).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Zhu, L., Luo, D., Wang, X., Guo, R. (2018). The Impact of the Relationship Between Operational Cost and Oil Prices on Economic Assessment in Oil and Gas Industry. In: Tavana, M., Patnaik, S. (eds) Recent Developments in Data Science and Business Analytics. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-319-72745-5_9
Download citation
DOI: https://doi.org/10.1007/978-3-319-72745-5_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-72744-8
Online ISBN: 978-3-319-72745-5
eBook Packages: Business and ManagementBusiness and Management (R0)