addressing uncertainty in oil and natural gas industry greenhouse

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occurred as a result of changes in the methodology, corrections, or as a result of new data. In this case, it is the standard deviation of the sample set that is appropriate and not the standard deviation of the mean. t× s( x) U( rel)( x) = × 100% (Equation 4-9) x where U(Rel)(x) = the relative expanded uncertainty in the data set (%); t = a value based on Student’s t-distribution with n-1 degrees of freedom which gives a 95% confidence interval; x = is the mean for the set of data calculated in Equation 4-3; and s( x ) = the standard deviation of the data set calculated in Equation 4-2. Continuing with the decision tree from Figure 4-4, uncertainty from other parameters may also require consideration, despite the fact that the standard deviation of a statistical sample of observations accounts for the measurement uncertainty and variability. Are the data based on a single point measurement or multiple measurements? Multiple points Do the measurements represent a sampling of the measured parameter? No Yes Apply Equations 4-1 through 4-3 to calculate the mean and standard deviation, respectively. Apply Equation 4-8 to estimate the uncertainty based on the measured data, OR apply Equation 4-9 to estimate uncertainty for a single observed estimate where other data is used for to quantify the uncertainty. Determine what (additional) parameters contribute to uncertainty. Note that bias may be one of the parameters. Are the errors in the measurements independent? (See text for guidance) No Yes Apply Equation 4-4 to aggregate uncertainty for addition/ subtraction of data. Apply Equation 4-6 to aggregate uncertainty for multiplication/ division of data. Apply Equation 4-5 to aggregate uncertainty for addition/ subtraction of data. Apply Equation 4-7 to aggregate uncertainty for multiplication/ division of data. Aggregate the uncertainty parameters by applying the “Square root of the sum of the squares.” (Equation 4-4) Where multiple uncertainty parameters apply, selection of the equation to aggregate uncertainty parameters depends on whether the uncertainties are independent. In addition, the activity value may be based on the product or sum of multiple data or variables. The decision diagram references the appropriate equation based on these criteria. Example – Statistical Sampling Uncertainty For this example, natural gas samples are collected to calculate the CO 2 emission factor associated with combusting the gas. (Note: this example would also apply to composition data for a flared gas stream.) Pilot Version, September 2009 4-23
Two methods are compared. The first calculates an annual average CO 2 emission factor based on monthly natural gas composition measurements and an annual summation of daily flow rates. The second determines monthly CO 2 emission factors based on monthly natural gas composition samples and applies a monthly summation of daily flow rates. Although this example is examining uncertainty associated with an emission factor, the decision tree provided in Figure 4-3 references the figure above (derived from Figure 4-4) for quantifying emission factor uncertainty where the emission factor is based on multiple measurements from a statistical sample. EXHIBIT 4-6: Uncertainty Example for Statistical Sampling Annual Composition Data o The facility collected 12 natural gas composition samples throughout the year in order to quantify the CO 2 content of the gas (expressed as tonnes CO 2 /MMscf), as shown in Table 4-9. o Since the data are based on a statistical sample, the uncertainty of the average composition is estimated using the sample standard deviation for each compound in the natural gas. The standard deviation will account for the uncertainty due to measurement error and the natural variability of the sampled values. Sampling procedures, maintenance activities, and equipment calibration are assumed to eliminate bias. Equation 4-7 was used to calculate the uncertainty. The calculation is shown for CH 4 . t 0.05, df 12 1 s( x)/ n 2.201 1.529369 / 12 Urel ( )( x) 100% × α = = − × = × = 100% × = 1.04% x 93.11333 The molecular weight of the average composition is calculated by applying the following equation: MW Mixture = 1 100 × # compounds ∑( Mole% i × MWi ) i= 1 resulting in 17.25045 lb/lbmole, as shown in Table 4-10. Pilot Version, September 2009 4-24
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Prepared by the LEVON Group, LLC an
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Table of Contents SECTION Page FORE
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List of Tables SECTION Page 2-1 Ove
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FOREWORD The global oil and natural
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DOCUMENT AT A GLANCE This document
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1.0 INTRODUCTION Policymakers use e
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The Intergovernmental Panel on Clim
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2.0 SOURCES OF UNCERTAINTY There ar
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Table 2-1. Overview of Methods Used
Page 19 and 20: the uncertainty associated with cur
Page 21 and 22: d. Data processing uncertainty Typi
Page 23 and 24: d. Material Balance For some emissi
Page 25 and 26: 3.0 OVERVIEW OF MEASUREMENT PRACTIC
Page 27 and 28: 3.1 Flow Measurement Practices Cont
Page 29 and 30: All these factors should be assesse
Page 31 and 32: Table 3-1. Example of FFMS Combined
Page 33 and 34: 3.2 Uncertainties of Flow Measureme
Page 35 and 36: Table 3-3. Compilation of Specifica
Page 37 and 38: EXHIBIT 3-3: FACTORS TO CONSIDER WH
Page 39 and 40: 3.3.2 Quantifying Sampling Precisio
Page 41 and 42: Table 3-4. Summary of Selected Carb
Page 43 and 44: 3.5 Heat Content Determination The
Page 45 and 46: 3.5.2 Computational Methods Heating
Page 47 and 48: using standard methods, non-standar
Page 49 and 50: 0.6 0.4 0.2 Error 0 -0.2 -0.4 -0.6
Page 51 and 52: s ± t × (Equation 4-1) n where s
Page 53 and 54: 4.2.1 Propagation Equations There a
Page 55 and 56: For two terms that might be correla
Page 57 and 58: EXHIBIT 4-1: Uncertainty Example fo
Page 61 and 62: Further guidance for assigning unce
Page 63 and 64: 4.4 Quantifying Measurement Uncerta
Page 69: Are the data based on a single poin
Page 73 and 74: . EXHIBIT 4-6: Uncertainty Example
Page 77 and 78: Table 4-13 shows the uncertainty in
Page 79 and 80: Table 4-13. Comparison of Annual Em
Page 81 and 82: • The evolution of activity and e
Page 83 and 84: These guidelines concentrate solely
Page 85 and 86: (Reprinted from the API Compendium)
Page 87 and 88: Table 5-2. Onshore Oil Field (High
Page 89 and 90: associated with them are assigned b
Page 91 and 92: Table 5-4. Onshore Oil Field (High
Page 93 and 94: 5.2.4 Propagating Assymetric Uncert
Page 95 and 96: U( rel) = U( rel) + U( rel) + U( re
Page 97 and 98: Coke burn rate approach (Equation 5
Page 99 and 100: Wt% C ∑ lbmole x lbmole C 12 lb C
Page 101 and 102: The CO 2 emissions are calculated u
Page 103 and 104: GHG Emissions, tonnes/yr 60,000 50,
Page 105 and 106: vast majority of the uncertainty fo
Page 107 and 108: 6.0 REFERENCES AGA, 2008, Greenhous
Page 109 and 110: The Alberta Energy and Utilities Bo
Page 111 and 112: Appendix A GLOSSARY OF STATISTICAL
Page 117 and 118: APPENDIX B LIST OF INDUSTRY MEASURE
Page 119 and 120: Chapter 2.8B Establishment of the L
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Chapter 11.5.3 Chapter 12.1.1 Chapt
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Chapter 19.4 Chapter 20.1 RP 85 RP
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ISO 8222:2002 ISO 8697:1999 ISO 902
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ISO 7194:2008 Measurement of fluid
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ASTM D4292 ASTM D4892 ASTM D5002 AS
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APPENDIX C OPERATING CONDITIONS, IN
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Appendix C OPERATING CONDITIONS, IN
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Appendix D SELECT MEASUREMENT METHO
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c. ASTM UOP539-97, Refinery Gas Ana
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interference between known componen
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maintained over the room temperatur
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APPENDIX E UNITS CONVERSION
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− Gasoline density (average) = 0.
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Appendix F UNCERTAINTY ESTIMATION D
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The uncertainty for the heaters/reb
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∑ 2 U ( abs) = U( abs) ∑(Wt%C)
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Combining the fuel usage for the tw
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Uncertainty Estimate of CO 2 e Emis
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U ( abs) = ( U ( abs) + U ( abs) +
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E E CO2e 219 tonne CO ⎛ 2 0.0108
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E CO 2 6 500× 10 scf gas lbmole ga
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• Fuel Economy (miles per gallon)
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Upper: U ( abs) = (U( abs) +U( abs)
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default CH 4 content is 5.53% from
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Uncertainty Estimate of CO 2 e Emis
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( ) Urel ( ) = Urel ( ) = Urel ( )
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Uncertainty Estimate for CH 4 and C
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specific mole % for CH 4 and CO 2 i
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E CO2 0.07239 tonne CH 4 tonne mole
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U ( rel) = U( rel) +U( rel) +U( rel
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Table F-14. Fugitive Emission and U
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U ( abs) = (U( abs) +U( abs) +U( ab
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Table F-15. Onshore Oil Field (High
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