Analysis Of Glycol Circulation System And Optimization Of Process Parameters In YAHA Natural Gas Treatment Plant

Tarim YAHA condensate gas field is a high-yielding condensate gas field with large reserves and high pressure.According to gas field conditions,Low temperature separation technology is adopted in Yaha operation area,and dehydration is done by high-pressure throttling method.Through field investigation,it is found that the loss of inhibitor glycol is increasing year by year,the energy consumption of ethylene glycol regeneration system is high,low concentration of regenerated poor liquid and so on.For these above problems,this paper uses the HYSYS software to simulate the field process,find out the reason of glycol loss by analyzing the key parameters,andUse HYSYS optimizer to optimize the optimal process parameters.Combined with the BP neural network to optimize and obtain the optimal operating parameters.The main contents are as follows:1.Through the investigation of glycol circulation process parameters and existing problems in Yaha area,Tarim oilfield,summarize the rules and formulate the corresponding scientific research program.2.Using HYSYS to build the ethylene glycol cycle process device model in YAHA operation area,through the error analysis and correction of the simulation model,the precision simulation of most of the error less than 10% is realized,and the reliability of the model is verified.3.Based on the HYSYS model,the rationality of ethylene glycol injection under the current operation parameters of Yaha operation area is analyzed,and the reason for the large loss of ethylene glycol is summarized.By adjusting the parameters,the optimum range of some process parameters is determined.4.Based on the HYSYS simulation model,to optimize the goal of reducing the energy consumption of the glycol and the regeneration system,optimize the glycol recycling process and formulate an optimal process operation plan.5.By analyzing the insufficiency of HYSYS optimization,it is necessary to use BP neural network to perform prediction and optimization.Using a large number of HYSYS operating data,the BP neural network was repeatedly trained and adjusted to obtain more accurate operational prediction data.Through the Matlab programming to find the optimal parameters of the prediction data,using neural network to simplify the prediction of process operation parameters.