Practical Application of a Probabilistic Approach to Estimate Reserves Using Production Decline Data
- Yueming Cheng (West Virginia University) | Yuhong Wang (Texas A&M University) | Duane McVay (Texas A&M University) | W. John Lee (Texas A&M University)
- Document ID
- Society of Petroleum Engineers
- SPE Economics & Management
- Publication Date
- April 2010
- Document Type
- Journal Paper
- 19 - 31
- 2010. Society of Petroleum Engineers
- 5.7 Reserves Evaluation, 4.6 Natural Gas, 3.2.3 Hydraulic Fracturing Design, Implementation and Optimisation, 7.2.1 Risk, Uncertainty and Risk Assessment, 5.6.3 Deterministic Methods, 5.7.3 Deterministic Methods, 5.6.9 Production Forecasting, 5.5 Reservoir Simulation
- Production Forecast, Reserves Estimation, Economics and Management, Decline Curve Analysis, Probabilistic Method
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- 1,896 since 2007
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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.
|File Size||1 MB||Number of Pages||13|
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