Bayesian Approach to the Assessment of Geological Risk in Oil and Gas Exploration

Authors

  • Dr. Bruno Lucena Federal University of Pará
  • Dr. Leonardo Lustosa Pontifical University of Rio de Janeiro

DOI:

https://doi.org/10.31686/ijier.vol8.iss7.2469

Keywords:

Undiscovered Oil Resources, Risk Analisys, Geological Risk, Bayesian Approach

Abstract

When assessing undiscovered oil resources, an important step is the assessment of geological risk, which is usually defined as the probability that there will be no accumulation of hydrocarbons. Some important authors have traditional ways of obtaining this probability, but these classic models are not developed on a rigorous basis. Therefore, they may present conflicting results, which are not always compatible with reality and are not able to take into account historical data from similar situations already studied. This article aims to propose a Bayesian approach to the determination of geological risk with advantages over classical approaches. The positive aspects and limitations of the Bayesian approach are discussed and an illustrative application using fictitious data is presented.

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References

Clemen, R., & Winkler, R. (1999). Combining Probability Distributions From Experts in Risk Analysis. Risk Analysis, 19(2), 187-203. DOI: https://doi.org/10.1111/j.1539-6924.1999.tb00399.x

Daneshkhah, A. (2004). Psychological Aspects Influencing Elicitation of Subjective Probability. Technical Report, The University of Sheffield, Sheffield. Access in 05/052020, available on https://www.researchgate.net/profile/Alireza_Daneshkhah/publication/255574139_Psychological_Aspects_Influencing_Elicitation_of_Subjective_Probability/links/0046353b6c3434cf93000000/Psychological-Aspects-Influencing-Elicitation-of-Subjective-Probability.pd

Hora, S. (May de 2004). Probability Judgments for Continuous Quantities: Linear Combinations and Calibration. Management Science, 50(5), 597-604. DOI: https://doi.org/10.1287/mnsc.1040.0205

Hyne, J. P. (2001). Nontechnical Guide to Petroleum Geology, Exploration, Drilling, and Production (2ª ed.). Tulsa: Pen Well Corporation.

Jones, C. (2018). The Oil e Gas Industry Must Break the Paradigm of Current Exploration Model. Journal of Petroleum Exploration and Production Technology, 8, 131-142. DOI: https://doi.org/10.1007/s13202-017-0395-2

Kahneman, D., Slovic, P., & Tversky, A. (1982). Judgment under Uncertainty: Heuristics and Biases. Cambridge: Cambridge University Press. DOI: https://doi.org/10.1017/CBO9780511809477

Li, J., Yun, P., Dufen, S., Jiexin, Y., & Tao, W. K. (2016). Deep Water Oil & Gas: New Opportunities and Suggestions for Chinese Oil Companies. IOP Conf. Series: Earth and Environmental Science (pp. 1-6). Chongqing: IOP Publish.

Lucena, B. R. (2006). Avaliação de Recursos de Petróleo Não Descobertos: Metodologias e Métodos de Eliciação de Informações Subjetivas. PUC-Rio, Rio de Janeiro.

Otis, R., & Schneiderman, N. (1997). A Process for Evaluating Exploration Process. AAPG Bulletin, 81(7), 1087-1109.

Ribeiro, C., Inacio Jr., E., Ly, Y., Furtado, A., & Gardin, N. (2020). The influence of user-supplier relationship on innovation dynamics of Oil & Gas industry. Technology Analysis & Strategic Management, 32(2), 119-132. DOI: https://doi.org/10.1080/09537325.2019.1641193

Rose, P. (2004). Risk Analysis and Management of Petroleum Exploration Ventures (Vol. 12). Tulsa: AAPG.

Rose, P. (2017). Evolution of E & P Risk Analysis (1960-2017)*. AAPG 100th Annual Convention and Exhibition. Houston: AAPG Datapages.

Schuenemeyer, J. (2002). A Framework for Expert Judgment to Assess Oil and Gas Resources. Natural Resources Research, 11(2), 97-107. DOI: https://doi.org/10.1023/A:1015512002249

Spetzler, C., & Stäel von Holstein, C. (1975). Probability Encoding in Decision Analysis. Management Science, 22(3), 340-357. DOI: https://doi.org/10.1287/mnsc.22.3.340

Stabell, C., & Sheehan, N. (April de 2001). Competitive Advantage in Petroleum Exploration. Oil & Gas Journal, 99(17), 30-36. Access in April, 2020

Zhu, Z., Lin, C., Zhang, X., Wang, K., Xie, J., & Wei, S. (2018). Evaluation of Geological Risk of Hydrocarbon Favorability Using Logistic Regression Model with Case Study. Marine and Petroleum Geology, 92, 65-77. DOI: https://doi.org/10.1016/j.marpetgeo.2018.02.012

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Published

2020-07-01

How to Cite

Dias de Lucena, B. R., & Junqueira Lustosa, L. (2020). Bayesian Approach to the Assessment of Geological Risk in Oil and Gas Exploration. International Journal for Innovation Education and Research, 8(7), 203-210. https://doi.org/10.31686/ijier.vol8.iss7.2469
Received 2020-06-14
Accepted 2020-06-22
Published 2020-07-01