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Comparison and application of different empirical correlations for estimating the hydrate safety margin of oil-based drilling fluids containing ethylene glycol
Authors:Fulong Ning  Ling Zhang  Guosheng Jiang  Yunzhong Tu  Xiang Wu  Yibing Yu
Institution:1. Faculty of Engineering, China University of Geosciences, Wuhan 430074, Hubei, China; 2. Department of Chemistry, Norwegian University of Science and Technology, Trondheim NO-7491, Norway; 3. National Laboratory on Scientific Drilling, China University of Geosciences at Beijing, Beijing 100083, China
Abstract:As the oil and gas industries continue to increase their activity in deep water, gas hydrate hazards will become more serious and challenging, both at present and in the future. Accurate predictions of the hydrate-free zone and the suitable addition of salts and/or alcohols in preparing drilling fluids are particularly important both in preventing hydrate problems and decreasing the cost of drilling operations. In this paper, we compared several empirical correlations commonly used to estimate the hydrate inhibition effect of aqueous organic and electrolyte solutions using experiments with ethylene glycol (EG) as a hydrate inhibitor. The results show that the Najibi et al. correlation (for single and mixed thermodynamic inhibitors) and the Ostergaard et al. empirical correlation (for single thermodynamic inhibitors) are suitable for estimating the hydrate safety margin of oil-based drilling fluids (OBDFs) in the presence of thermodynamic hydrate inhibitors. According to the two correlations, the OBDF, composed of 1.6 L vaporizing oil, 2% emulsifying agent, 1% organobentonite, 0.5% SP-1, 1% LP-1, 10% water and 40% EG, can be safely used at a water depth of up to 1900 m. However, for more accurate predictions for drilling fluids, the effects of the solid phase, especially bentonite, on hydrate inhibition need to be considered and included in the application of these two empirical correlations.
Keywords:oil-based drilling fluid  gas hydrates  ethylene glycol  inhibition prediction
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