High Pressure Gas-Liquid Separation: An Experimental Study on Separator Performance of Natural Gas Streams at Elevated Pressures

Author(s):  
Adam Bymaster ◽  
Michael Olson ◽  
Ed Grave ◽  
Steve J. Svedeman ◽  
Flavia Viana ◽  
...  
Author(s):  
William Lowry ◽  
Jaap de Vries ◽  
Michael Krejci ◽  
Eric Petersen ◽  
Zeynep Serinyel ◽  
...  

Alkanes such as methane, ethane, and propane make up a large portion of most natural gas fuels. Natural gas is the primary fuel used in industrial gas turbines for power generation. Because of this, a fundamental understanding of the physical characteristics such as the laminar flame speed is necessary. Most importantly, this information is needed at elevated pressures to have the most relevance to the gas turbine industry for engine design. This study includes experiments performed at elevated pressures, up to 10 atm initial pressure, and investigates the fuels in a pure form as well as in binary blends. Flame speed modeling was done using an improved version of the kinetics model that the authors have been developing over the past few years. Modeling was performed for a wide range of conditions, including elevated pressures. Experimental conditions include pure methane, pure ethane, 80/20 mixtures of methane/ethane, and 60/40 mixtures of methane/ethane at initial pressures of 1 atm, 5 atm, and 10 atm. Also included in this study are pure propane and 80/20 methane/propane mixtures at 1 atm and 5 atm. The laminar flame speed and Markstein length measurements were obtained from a high-pressure flame speed facility using a constant-volume vessel. The facility includes optical access, a high-speed camera, a schlieren optical setup, a mixing manifold, and an isolated control room. The experiments were performed at room temperature, and the resulting images were analyzed using linear regression. The experimental and modeling results are presented and compared with previously published data. The data herein agree well with the published data. In addition, a hybrid correlation was created to perform a rigorous uncertainty analysis. This correlation gives the total uncertainty of the experiment with respect to the true value rather than reporting the standard deviation of a repeated experiment. Included in the data set are high-pressure results at conditions where in many cases for the single-component fuels few data existed and for the binary blends no data existed prior to this study. Overall, the agreement between the model and data is excellent.


2015 ◽  
Vol 280 ◽  
pp. 486-493 ◽  
Author(s):  
David Danaci ◽  
Ranjeet Singh ◽  
Penny Xiao ◽  
Paul A. Webley

Fuel ◽  
2019 ◽  
Vol 256 ◽  
pp. 115950 ◽  
Author(s):  
Pengliang Li ◽  
Zhenyi Liu ◽  
Mingzhi Li ◽  
Ping Huang ◽  
Yao Zhao ◽  
...  

2021 ◽  
Vol 2108 (1) ◽  
pp. 012094
Author(s):  
Zijian Dai ◽  
Hualin Liao ◽  
Ke Yang ◽  
Feng Sun

Abstract Natural gas hydrate is a research hotspot at present. However, the current exploitation technology can’t meet the demand of commercial exploitation of natural gas hydrate. In order to improve the efficiency of hydrate production, this paper believes that the idea of using high-pressure water jets for sandblasting perforation is expected to constitute an effective way to extract natural gas hydrates. The experimental study on sandblasting perforation and hydraulic slitting of simulated reservoirs was carried out by using large-scale ground fracturing equipment and full-scale hydraulic blasting perforating equipment. The driving pressure is analysed under the action of high-pressure water jet. The influence of diameter on the effect of simulated reservoir fracture. The results show that the diameter of the perforation increases with the increase of pressure; This experimental study can provide an experimental basis for the use of abrasive jet blasting perforating technology to improve the efficiency of natural gas hydrate production.


Author(s):  
William Lowry ◽  
Jaap de Vries ◽  
Michael Krejci ◽  
Eric Petersen ◽  
Zeynep Serinyel ◽  
...  

Alkanes such as methane, ethane, and propane make up a large portion of most natural gas fuels. Natural gas is the primary fuel used in industrial gas turbines for power generation. Because of this, a fundamental understanding of the physical characteristics such as the laminar flame speed is necessary. Most importantly, this information is needed at elevated pressures to have the most relevance to the gas turbine industry for engine design. This study includes experiments performed at elevated pressures, up to 10-atm initial pressure, and investigates the fuels in a pure form as well as in binary blends. Flame speed modeling was done using an improved version of the kinetics model that the authors have been developing over the past few years. Modeling was performed for a wide range of conditions, including elevated pressures. Experimental conditions include pure methane, pure ethane, 80/20 mixtures of methane/ethane, and 60/40 mixtures of methane/ethane at initial pressures of 1, 5, and 10 atm. Also included in this study are pure propane and 80/20 methane/propane mixtures at 1 and 5 atm. The laminar flame speed and Markstein Length measurements were obtained from a high-pressure flame speed facility using a constant-volume vessel. The facility includes optical access, a high-speed camera, a schlieren optical setup, a mixing manifold, and an isolated control room. The experiments were performed at room temperature, and the resulting images were analyzed using linear regression. The experimental and modeling results are presented and compared to previously published data. The data herein agree well with the published data. In addition, a hybrid correlation was created to perform a rigorous uncertainty analysis. This correlation gives the total uncertainty of the experiment with respect to the true value rather than reporting the standard deviation of a repeated experiment. Included in the data set are high-pressure results at conditions where in many cases for the single-component fuels few data existed and for the binary blends no data existed prior to this study. Overall, the agreement between the model and data is excellent.


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