Highly sour gas production plays an important role in China's natural gas industry. Highly sour gas reservoirs have been discovered widely in Sichuan Basin, such as Luojiazhai Gas Reservoir and Puguang Gas Reservoir. Due to extreme poison, strong corrosion, and complex precipitation and deposition of H2S in the reservoir, it is very difficult and risky to investigate and explore drilling, completion, production, workover, and gas transportation. Meanwhile, varying phase behavior and sulfur deposition cause the complicated fluid flow in porous medium and consequently challenge reservoir management. This paper focuses on sour gas phase behavior and sulfur deposition through laboratory experiment and numerical simulation. The carbonate cores are obtained from real field with permeability ranges from 0.85md to 20md. The fluid injection rates are 0.82cm3/minute, 1.25cm3/minute, and 3.50cm3/minute, respectively. Scanning Electro Microscope (SEM) is used to quantify sulfur deposition in the core. On the basis of experimental work, three-dimensional multi-component mathematical model for sour gas reservoir is developed. Gas flow rate and sulfur deposition impacted by initial H2S concentration and formation permeability are further simulated. Experimental study on phase behavior demonstrates that Z factor of sour gas firstly decreases and then increase when pressure continuously increases. Experiment illustrates that high gas flow rate reduces sulfur deposition while high H2S concentration generates severe sulfur deposition. In addition, sulfur depositionspeeds up with the reduction of rock permeability. Finally, sulfur deposition is predicted in Gaoqiao Gas Reservoir located in Sichuan Basin using the developed mathematical model in this paper. The simulation results show that sulfur start precipitating once reservoir pressure drops. At low gas flow rate, the deposited sulfur particles occur in the pores. The deposition severely impedes production. However, the main damage area is near wellbore. Our study is helpful for predicting production performance in the sour gas reservoir.
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