Research on Calculation Method of Aerodynamic Parameters of Supersonic Probe Based on Gas Compressibility Factor

2022 ◽  
Vol 31 (1) ◽  
pp. 111-119
Author(s):  
Jingjun Zhong ◽  
Gangfeng Huang ◽  
Wanyang Wu ◽  
Xiaoxu Kan
2021 ◽  
Author(s):  
Oluwasegun Cornelious Omobolanle ◽  
Oluwatoyin Olakunle Akinsete

Abstract Accurate prediction of gas compressibility factor is essential for the evaluation of gas reserves, custody transfer and design of surface equipment. Gas compressibility factor (Z) also known as gas deviation factor can be evaluated by experimental measurement, equation of state and empirical correlation. However, these methods have been known to be expensive, complex and of limited accuracy owing to the varying operating conditions and the presence of non-hydrocarbon components in the gas stream. Recently, newer correlations with extensive application over wider range of operating conditions and crude mixtures have been developed. Also, artificial intelligence is now being deployed in the evaluation of gas compressibility factor. There is therefore a need for a holistic understanding of gas compressibility factor vis-a-vis the cause-effect relations of deviation. This paper presents a critical review of current understanding and recent efforts in the estimation of gas deviation factor.


2013 ◽  
Vol 136 (1) ◽  
Author(s):  
Mohamed Mahmoud

Gas compressibility factor or Z-factor for natural gas system can be determined from Standing-Katz charts using the pseudocritical gas pressure and temperatures. These charts give accurate values for Z-factors. Reservoir simulation softwares need accurate correlations to estimate the values of Z-factor; one of the well-known correlations is Dranchuk and Abou-Kassem (DAK) Correlation. This correlation gives large errors at high gas reservoir pressures, this error could be more than 100%. The error in estimating Z-factor will lead to big error in estimating all the other gas properties such as gas formation volume factor, gas compressibility, and gas in place. In this paper a new accurate Z-factor correlation has been developed using regression for more than 300 data points of measured Z-factor using matlab in addition to other data points at low pressure and temperature from Standing-Katz charts and DAK correlation. Old correlations give good estimation of Z-factor at low gas reservoir pressures below 41.37 MPa (6000 psia), at high pressures the error started to appear. The developed correlation is a function of pseudoreduced pressure and temperature of the gas which makes it simpler than the existing complicated correlations. The new correlation can be used to determine the gas compressibility factor at any pressure range especially for high pressures the error was less than 3% compared to the measured data. The developed correlation is very simple to be used, it just needs the gas specific gravity that can be used to determine the pseudocritical properties of the gas and at last the Z-factor can be determined. A new formula of reduced gas compressibility was developed based on the developed Z-factor correlation which in turn can be used to determine the gas compressibility.


Author(s):  
Xiaocui Tian ◽  
Xiaokai Xing ◽  
Rui Chen ◽  
Shubao Pang ◽  
Liu Yang

In the custody transfer metering of natural gas, it’s necessary to transform gas volume from metering state into standard state. Natural gas is non-ideal gas, and its compressibility factor varies with different components, temperature and pressure. So the accuracy of its calculation has direct impact on that of natural gas metering, and then affects the economic benefits of the enterprise [1]. According to related standard of China, in the custody transfer metering of natural gas, the formula stipulated by AGA NO.8 should be adopted to calculate compressibility factor. But the components of natural gas must be monitored at all times when this method is used, and the calculation process is complicated. In practical operation of natural gas trade, compressibility factor changes because of frequent adjustment of pipeline operating conditions. In order to simplify the calculation, simplified formula is applied to calculate compressibility factor generally, but it’s difficult to guarantee the accuracy at the same time. In this paper, the simplified formula, which is used for calculating natural gas compressibility factor of a joint-stock natural gas pipeline of CNPC, is modified with the standard formula stipulated by AGA NO.8. After the modification, an empirical formula of compressibility factor calculation applicable to this pipeline system is proposed, whereby the accuracy of compressibility factor calculation is improved. When the modified one is applied to natural gas trade, the accuracy of metering is improved likewise.


2021 ◽  
Vol 2(73) (2) ◽  
pp. 13-21
Author(s):  
George Iulian Oprea ◽  
◽  
Artemis Aidoni ◽  
Ioana Cornelia Mitrea ◽  
Florinel Dinu ◽  
...  

The natural gas compressibility factor indicates the compression and expansion characteristics of natural gas under different conditions. It is a thermodynamic property used to take into account the deviation of the behaviour of real natural gases from that of an ideal gas. Compressibility factor, Z, values of natural gases are necessary for most petroleum gas engineering calculations. In this study, a comparison between five different calculation methods is presented to determine this critical parameter for the same natural gas at different conditions (pressure and temperature), using Canadian Association of Petroleum Producers, Azizi, Behbahani and Isazadeh, Dranchuk- Purvis- Robinson, Dranchuk-Abu-Kassem and Standing- Katz methods. The correlations are based on the equation of state are often implicit because they require iteration. Many correlations have been derived to enhance simplicity; however, no correlation has been developed for the entire range of pseudo-reduced pressures and temperatures. Azizi, Behbahani and Isazadeh’s method was found to have the biggest error as a result obtained for T=20° C, and p=20 bar is no longer in the field of applicability.


2013 ◽  
Vol 63 ◽  
pp. 38-43 ◽  
Author(s):  
Ke-Le Yan ◽  
Huang Liu ◽  
Chang-Yu Sun ◽  
Qing-Lan Ma ◽  
Guang-Jin Chen ◽  
...  

2021 ◽  
Author(s):  
Kristian Mogensen ◽  
Robert Merrill

Abstract The gas compressibility factor is an important property in reservoir simulation studies. It is directly linked to the gas formation volume factor and the gas density thereby impacting wellhead injection pressure, reservoir voidage, injectivity, as well as the tendency for gas gravity override to occur in the reservoir. ADNOC's PVT database contains experiments on almost 2,000 samples, of which more than 100 have been subject to advanced gas injection experiments. Z-factor data have been compiled from the liberated gas during DV experiments as well as from CCE experiments on reservoir gases, injection gases, and swollen fluid mixtures. Several of these mixtures are very rich in H2S, whereas pressure and temperature are in the range of 14.7-14,500 psia and 80-365 °F, respectively. We test several different methods for predicting the Z-factor, such as the industry-standard Hall-Yarborough method, in combination with various models for pseudo-critical pressure and temperature and including correction for non-hydrocarbon components. Other methods tested include the GERG-2008 model, considered to be state-of-the-art for predicting physical properties for well-described gas mixtures, as well as the well-known Peng-Robinson cubic equation of state. Based on close to 10,000 data points in our database, the GERG-2008 model typically predicts the Z-factor to be within 2% of the measured value, which is on par with the experimental uncertainty. However, for some rich gas condensate mixtures, the model gives larger errors because its parameters are only tuned to compositions with components up to C10. This is to our knowledge the first time that the GERG-2008 EOS has been compared to standard Z-factor correlations for such a large number of data points. If compositional information is available, we recommend using either the GERG-2008 model or the Hall-Yarborough model with pseudo-critical properties provided by Kay (1936). When compositions are not available, we find that the Standing correlation is more accurate than the Sutton model, also for sour mixtures.


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