SPE Economics & Management
Volume 2, Number 1, April 2010, pp. 19-31

SPE-95974-PA

Practical Application of a Probabilistic Approach to Estimate Reserves Using Production Decline Data

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DOI  More information 10.2118/95974-PA http://dx.doi.org/10.2118/95974-PA

Citation

  • Cheng, Y., Wang, Y., McVay, D.A., and Lee, W.J. 2010. Practical Application of a Probabilistic Approach to Estimate Reserves Using Production Decline Data. SPE Econ & Mgmt  2 (1): 19-31. SPE-95974-PA. doi: 10.2118/95974-PA.

Discipline Categories

  • 6.8 Fundamental Research in Reservoir Description and Dynamics
  • 6.7 Reserves Evaluation
  • 6.7.4 Probabilistic Methods
  • 3.7.1 Resource Potential
  • 3.2 Risk Management and Decision-Making

Keywords

  • Economics and Management, Probabilistic Method, Reserves Estimation, Production Forecast, Decline Curve Analysis

Summary

Analysts have increasingly used probabilistic approaches to evaluate the uncertainty in reserves estimates based on decline-curve analysis (DCA). This is because the results represent statistical analysis of historical data that usually possess significant amounts of noise. Probabilistic approaches usually provide a distribution of reserves estimates with three confidence levels (P10, P50, and P90) and a corresponding 80% confidence interval (CI). The question arises: How reliable is this 80% CI? In other words, in a large set of analyses, is the true value of reserves contained within this interval 80% of the time? Our investigation indicates that it is common in practice for true values of reserves to lie outside 80% CIs much more than 20% of the time using traditional statistical analyses. This indicates that uncertainty is being underestimated, often significantly. Thus, the challenge in probabilistic reserves estimation using DCA is not only how to appropriately characterize probabilistic properties of complex production-data sets, but also how to determine and then improve the reliability of the uncertainty quantifications.

This paper presents an improved methodology for probabilistic quantification of reserves estimates using DCA and practical application of the methodology to actual individual-well decline curves. Application of our proposed new method to 100 oil and gas wells demonstrates that it provides much wider 80% CIs than methods previously presented, and these CIs contain the true values approximately 80% of the time. In addition, the method yields more-accurate P50 values than previously published methods do. Thus, the new methodology provides more-reliable probabilistic reserves estimation, which has important impacts on economic risk analysis and reservoir management.

© 2010. Society of Petroleum Engineers

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History

  • Original manuscript received: 19 August 2009
  • Meeting paper published: 10 October 2005
  • Manuscript approved: 16 February 2010
  • Published online: 27 April 2010
  • Version of record: 27 April 2010