
科学技术与工程

中国技术经济学会
Experimental Characterization of Typical Reservoirs in Deep Carbonate Gas Formations Using Tracer Technology
Rui-duo ZHANG , Yong HU , Xian PENG , Lian-jin ZHANG , Tao LI , Dong HUI , Long-xin LI
Science Technology and Engineering ›› 2025, Vol. 25 ›› Issue (35) : 15080 -15087.
The high temperatures and pressures in deep carbonate reservoirs, coupled with well-developed pore-seam structures and diverse reservoir types, result in significant variations in production capacities among gas wells. Identifying reservoir types using conventional production dynamic monitoring techniques presents certain challenges. Therefore, based on the characteristic seam structure of the Gaoshiti-Moxi block, a quasi-three-dimensional physical model of the fracture-slit type typical seam structure has been designed and etched. Gas tracer flowback migration experiments were conducted to elucidate the gas tracer flowback concentration curve characteristics under different conditions of shut-in time, flow direction, and gas tracer concentration. The results reveal that for the Fracture fracture-cavity type with a porosity of 5.93%, the concentration curve exhibits a single peak with an intensity of 17.13%. The tailing time is 3 615 s, indicating a prominent single dominant channel. The cavity structure effectively delays the reduction trend of gas tracer concentration. Increasing shut-in time expands the diffusion range of the gas tracer, reduces its peak concentration, and prolongs its effective duration. Some of the gas tracer diffuses into deeper pore structures, yet the overall peak characteristics remain unchanged. In the case of Class I reservoirs with better pore-permeability conditions in fracture fracture-cavity type, changes in tracer flow direction do not alter their specific peak characteristics significantly. However, variations in tracer amounts lead to substantial differences in the peak concentration of the SF6 concentration curve.
carbonate reservoirs / gas tracer / flowback migration experiments / flowback concentration curve characteristics
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