1、CORRELATION EQUATIONS TO PREDICT REID VAPOR PRESSURE AND PROPERTIES OF GASEOUS EMISSIONS FOR EXPLORATION STD.API/PETRO PUBL 4683-ENGL 1998 0732290 ObL5307 T7q American Petroleum Institute American Petroleum Institute Environmental, Health, and Safety Mission and Guiding Principles MISSION The member
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9、ment. o To promote these principles and practices by sharing experiences and offering assistance to others who produce, handle, use, transport or dispose of similar raw materials, petroleum products and wastes. STD.API/PETRO PUBL 4b83-ENGL 1998 0732290 Ob15308 900 m Correlation Equations to Predict
10、Reid Vapor Pressure and Properties of Gaseous Emissions for Exploration and Production Facilities Health and Environmental Sciences Department API PUBLICATION NUMBER 4683 PREPARED UNDER CONTRACT BY: PAT RYAN LYLE R. CHINKIN PETALUMA, CALIFORNIA DANA L. COE SONOMA TECHNOLOGY, INC. NOVEMBER 1998 Ameri
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15、, Washington. D.C. 20005. Copyright O 1998 American Petroleum institute iii ACKNOWLEDGMENTS THE FOLLOWING PEOPLE ARE RECOGNIZED FOR THEIR CONTRIBUTIONS OF TIME AND EXPERTISE DURING THIS STUDY AND IN THE PREPARATION OF THIS REPORT API STAFF CONTACT Paul Martino, Health and Environmental Sciences Depa
16、rtment MEMBERS OF THE EXPLORATION AND PRODUCTION EMISSION CALCULATION PROJECT GROUP Jim Collins, Arco William Fishback, Mobil Exploration e EXECUTIVE SUMMARY . e5-1 1 . INTRODUCTION 1 . 1 OVERVIEW OF THE VARIABLES AND THEORETICAL CONTEXT . 1-2 APPROACH . 1-4 2 . REVIEW OF THE DATA 2-1 3 . ANALYSIS O
17、F REID VAPOR PRESSURE 3-1 UNDERLYING THEORY . 3-1 EXPECTED EMPIRICAL RELATIONSHIPS . 3-2 DESCRIPTIVE STATISTICS . 3-2 REGRESSION ANALYSIS . 3-4 4 . ANALYSES OF GAS MOLECULAR WEIGHTS . 4-1 UNDERLYING THEORY AND EXPECTED PREDICTORS 4-1 DESCRIPTIVE STATISTICS . 4-2 REGRESSION ANALYSIS . 4-4 5 . ANALYSE
18、S OF MOLE FRACTIONAL CONTRIBUTIONS OF HAZARDOUS AIR POLLUTANTS TO HYDROCARBON EMISSIONS 5-1 SUMMARY OF RESULTS . 5-1 6 . ANALYSIS OF SEPARATOR GAS SPECIFIC GRAVITY 6-1 DESCRIPTIVE STATISTICS . 6.1 REGRESSION ANALYSIS . 6-2 7 . COMPARATIVE EVALUATION OF ALTERNATIVE MODELS AND INPUTS . 7-1 COMPARISON
19、OF FLASH EMISSION ESTIMATES . 7-3 COMPARISON OF W only one of the repeated cases was retained. Ninety-four storage tanks remained in the data set for analysis. Excluded. Excluded. Table 2-1. Results of an initial examination of E ln(G0R) vs. sales oil APIG). 2-2 STD*API/PETRO PUBL 4683-ENGL 3998 m 0
20、732290 0635325 T9T SP Y “t RVP Measured Parameters SP = Separator pressure (psig) ST = Separator temperature (“Rankine) APIG = Sales oil APIG (OAPI) RVP = Sales oil RVP ia) BP = Sales oil bubble point (psia) SG, = Specific gravity of the separator gas c. c 3 O o ST BP FGMWT WSGMWT WIG Y S 3 O o GOR
21、Y c 3 O o Modeled Parameters GOR = Gas-to41 ratio of the sales oil (scfhbl) FGMWT = Flash gas total molecular weight (1bAb-mol) MWT, = Molecular weight of the THC fraction of the flash gas ObAb-mol) %nonHC, = Sum mole fraction of the non-hydrocarbon species in the total vent gas (%); tota) vent gas
22、= W total vent gas = W x-axis variables are below. A scatter plot matrix is a visual aid to identify correlations; units of measure are unnecessary for this purpose. 2-4 STD.API/PETRO PUBL 4b83-ENGL 1998 m 0732290 Ob15327 8b2 Section 3 ANALYSIS OF REID VAPOR PRESSURE The purpose of this section is t
23、o establish a correlation equation that predicts the sales oil RVP. Several measured parameters are discussed, including sales oil RVP, sales oil APIG, sales oil bubble point, separator temperature, and separator pressure. UNDERLYING THEORY RVP is a composite value of the vapor pressures exerted by
24、individual components in a gas phase that is in equilibrium with a liquid mixture. For a simpler scenario, that of a pure liquid, the Antoine equation correlates pure substance vapor pressure (p*) with temperature (Felder and Rousseau, 1978). log, p“ = A - B/(T + C) (Equation 3-1) A, B, and C are co
25、nstants determined from a least squares fit of measured data. The RVP of a mixture may be estimated by combining the contributions of individual species to the total vapor pressure. This requires an assumption that species individual contributions may be predicted fi-om their behaviors as pure subst
26、ances. This assumption often introduces a large degree of error. RVP = yi lo* Bfl+c)l (Equation 3-2) where yi is the mole fraction of component i in the gas phase. A, By and C are constants that are species dependent. Protocol calls for measurements of RVP to be reported at a constant temperature of
27、 560“ Rankine (OR); therefore, Equation 3-2 may be simplified as RVP = C yi a, (Equation 3 -3) where a, is a species-specific constant defined by lotA B(560R+C)1. Equation 3-3 indicates that RVP is related to the mole fractions and species-specific constants of each gas phase component. Although Tre
28、ybal(l980) cautions against models that treat mixtures as though they were analogous to pure substances, this equation (3-3) represents the best simplified theory currently available. 3-1 EXPECTED EMPIRICAL RELATIONSHIPS Predictors of sales oil RVP are expected to directly relate to the volatility o
29、f the sales oil or the conditions of the storage tank (such as sales oil APIG and bubble point). (Measurements of separator pressure and temperature are collected in a vessel external to the sales oil tank, and therefore, are not expected to correlate well with the RVP of the sales oil.) The bubble
30、point pressure is defined as the pressure at which the first bubble of vapor will form in a liquid that is held in a closed container at a constant temperature. The bubble point pressure of the sales oil is very likely to correlate well with the RVP since (1) both variables represent a pressure meas
31、urement of the gas phase in equilibrium with the sales oil, and (2) the bubble point pressure represents the theoretical upper limit to RVP. Figure 3- 1 illustrates the relationship between sales oil bubble point and RVP for 94 E the symbol, oc, denotes a modeling approximation. 4- 1 STD.API/PETRO P
32、UBL Yb83-ENGL 1798 0732270 Ob15334 TT2 Equation 4-3a approximates the molecular weight of hydrocarbons as the ratio of a temperature function to pressure. This model indicates that the separator temperature and pressure may be predictors of the THC molecular weight. In Equation 4-3b, the mole fracti
33、on of methane (ymethane) was selected as a surrogate species to describe changes in the THC molecular weight. Methane is similar in molecular structure and flash point to other light-end hydrocarbons (such as ethane and propane), which comprise the bulk of the flash gas stream (on a molar basis). Th
34、us, the amount of methane in fresh crude extract is expected to be a good predictor of the quantities of lightend hydrocarbons. Additionally, E&P site operators tend to be more familiar with methane contents of gas streams than other light-end hydrocarbons. Therefore, the mole fraction of methane (y
35、mern was selected as the surrogate species best suited to predict the THC molecular weight. As shown in Figure 4-1, the mole fraction (percent) of methane acts as a good linear predictor of THC molecular weights, and a weak linear predictor of the non-methane HC molecular weights predicted by E&P TA
36、NK. (Note that in Figure 4-1, the mole percent of methane represents a percentage of the entire flash gas phase, and not just the THC portion.) DESCRIPTIVE STATISTICS Table 4-1 lists the key descriptive statistics for the parameters discussed in this analysis. Note that the average molecular weights
37、 of THC in the flash gas and W&S gas are 37 lb/lb-mole and 42 lb/lb-mole, which are 25 percent and 15 percent less than the default values (50 lb/lb-mole for both). This finding suggests that the default value for the flash gas should at least be altered. The average molecular weight of the W&S gas
38、agrees reasonably well with MIS past research, but still suggests some difference. It is interesting to note that the average fiactional contribution of non-hydrocarbons to the total vented gas is 10 percent (not O percent), and was modeled to be as high as 95 percent. 4-2 STD-API/PETRO PUBL 4b83-EN
39、GL 1998 = 0732290 OLL5335 939 Statistic Min MU Mean SD r = 0.90 APIG MWT, MWT, SP ST (OAR 1OOOF) (Ibhb-mole) (IbAb-mole) (psig) h(SP)“ (OF) 19.0 19.1 4.0 1.39 40 15.0 72.4 63.9 870 6.77 180 66.0 42.2 36.8 122 3.90 87 40.6 10.5 9.7 221 1.16 26 13.1 aa %nonHC, (W 0.0 95.3 O h(%nonHoT) * -1.9 4.6 10 0
40、10 20 30 40 50 60 70 80 90 18.2 Mole % Methane in Total Vented Gas 1.6 - r = 0.53 o 0 10 20 30 40 50 60 70 80 90 c - O Mole % Methane in Total Vented Gas (b) Figure 4-1. Relationships between the mole fraction of methane and flash gas molecular weights. (a) Average molecular weight of total hydrocarbons. () Average molecular weight of non-methane hydrocarbons. Table 4- 1. Descriptive statistics of variables used to predict gas molecular weights. 4-3
