Prediction of Gas Hydrate Formation Conditions in the Presence of Methanol, Glycerol, Ethylene Glycol, and Triethylene Glycol with the Statistical Associating Fluid Theory Equation of State

2006 ◽  
Vol 45 (6) ◽  
pp. 2131-2137 ◽  
Author(s):  
Xiao-Sen Li ◽  
Hui-Jie Wu ◽  
Peter Englezos
SPE Journal ◽  
2006 ◽  
Vol 11 (02) ◽  
pp. 248-258 ◽  
Author(s):  
Mason B. Tomson ◽  
Amy T. Kan ◽  
Gongmin Fu ◽  
Musaed Al-Thubaiti ◽  
Dong Shen ◽  
...  

Summary There is no accepted methodology to correlate the effects of hydrate inhibitors on scale formation as there is for electrolytes. Similarly, the effect of hydrate inhibitor on scale inhibition with common inhibitors is not well known. In this paper, a semi-empirical approach is proposed to correlate the effect of hydrate inhibitors on scale formation from experimental solubility measurements of halite, barite, gypsum, calcite, and carbonate equilibrium chemistry. The ion-cosolvent activity coefficients can be used directly in any solution speciation code to evaluate the effect of cosolvent on mineral scale formation. The validity of the equation has been tested between 4 and 50°C as well as between 1 and 6 M ionic strength. Working equations that can be used in gas and oil production to calculate the effect of cosolvents on scale formation are presented. Details about how to predict hydrate-inhibitor-induced scale formation and case studies that demonstrate the severity of methanol on scaling tendency are also discussed. Finally, barite nucleation and kinetics are studied in the presence and absence of methanol. A semi-empirical equation to predict the nucleation time is proposed. Preliminary studies of scale-inhibitor efficiency in the presence of methanol are also discussed. At high methanol concentration, scale inhibition may not be possible because of precipitation of metal-inhibitor salt. Glycols have a less adverse effect than methanol on both mineral scale formation and inhibition. Introduction Methanol, ethylene glycol, and triethylene glycol are industrial solvents and raw materials for a variety of processes. In the oil and gas industries, methanol, ethylene glycol, and triethylene glycol are often used to inhibit gas-hydrate formation during production. Gas hydrate is a crystalline solid consisting of a gas molecule surrounded by a cage of water molecules, which forms at certain high-pressure and low-temperature regimes. Gas-hydrate formation is particularly troublesome for offshore gas wells, where the producing temperature is low because of both adiabatic expansion of gas and seawater cooling. Once gas hydrate forms, it can plug up the well and prevent gas production. One economic solution to prevent hydrate formation is to inject a large quantity of methanol, ethylene glycol, or triethylene glycol. These organic solvents are thermodynamic inhibitors (i.e., they increase the thermodynamic solubility of gas hydrate). This type of inhibitor is only effective at high cosolvent concentrations. Unfortunately, the use of high cosolvent concentration has an adverse effect on scale formation. because the mineral salts are generally less soluble in the cosolvent. Production from reservoir oilfield brines are often close to saturation as they enter a well; therefore, even a small amount of added methanol or ethanol is often sufficient to induce various minerals to precipitate. The scaling tendency of sparingly soluble mineral salts (e.g., calcite and barite) in methanol/brine and ethanol/brine solutions is observed to be orders of magnitude larger than in the brine alone. Halite scaling is also severely affected in the presence of methanol or ethanol. Ethylene glycol and triethylene glycol have less adverse effect on mineral-salt-scaling tendency.


Processes ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 519
Author(s):  
Jie Cao ◽  
Shijie Zhu ◽  
Chao Li ◽  
Bing Han

To predict the natural gas hydrate formation conditions quickly and accurately, a novel hybrid genetic algorithm–support vector machine (GA-SVM) model was developed. The input variables of the model are the relative molecular weight of the natural gas (M) and the hydrate formation pressure (P). The output variable is the hydrate formation temperature (T). Among 10 gas samples, 457 of 688 data points were used for training to identify the optimal support vector machine (SVM) model structure. The remaining 231 data points were used to evaluate the generalisation capability of the best trained SVM model. Comparisons with nine other models and analysis of the outlier detection revealed that the GA-SVM model had the smallest average absolute relative deviation (0.04%). Additionally, the proposed GA-SVM model had the smallest amount of outlier data and the best stability in predicting the gas hydrate formation conditions in the gas relative molecular weight range of 15.64–28.97 g/mol and the natural gas pressure range of 367.65–33,948.90 kPa. The present study provides a new approach for accurately predicting the gas hydrate formation conditions.


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