Analysis of the reasons for the recovery of thermal reservoir pressure in the geothermal concentrated mining area of Tianjin Guantao Formation
This paper is the result of geothermal geology.Geothermal is a clean energy source,and local concentrated extraction of geothermal fluid will cause a pressure depression cones.[Objective]Due to the long history of geothermal development,multiple large-scale pressure depression cones have been formed in the Tianjin area.Since 2018,the water level in the center of the cones began to rise rapidly and the thermal reservoir pressure began to recover after the gradual reduction of mining output.However,there are few studies on the correlation between the water level rise and the change of mining output,and what changes will happen to the cone shape,and the understanding of the evolution law is not clear enough.[Methods]This article takes the dynamic changes of water level in the Guantao Formation of the Neogene in Tianjin as an example,analyzes the correlation between extraction and reinjection volume and water level,studies the dynamic evolution law of water level in the cone area,analyzes the cause for pressure recovery,and provides reasonable suggestions for evaluating geothermal recoverable amount in the depression cones.[Results]The study suggests that the continuous"insufficient inflow"of thermal reservoir water is the fundamental cause for the formation of a pressure depression cone,while the combined effect of group wells pumping leads to synchronous fluctuations in thermal reservoir pressure,a sharp decrease in consumption,and the flattening effect of the cone causing the water level in the central area of the cone to rise.[Conclusions]Geothermal evaluation and management should be based on the real-time dynamics of thermal reservoir pressure in the cone area,and reasonable control of consumption and maintenance of water balance are effective ways for the sustainable utilization of geothermal resources.
geothermal resourcesgroundwater depression conesplanationTianjin city
万方数据
维普
