Remote Prediction Of Geothermal Resource Potential In The Changbai Mountain Area

Remote sensing data has an advantage with macro, get short cycle and capacity to represent the real landscape, the thematic information(land surface temperature, hydrothermal alteration, faults) based on remote sensing data is a reference factors indicating the occurrence of geothermal resources, which can be regarded as model features variable to forecast distribution of geothermal resources, combined with geophysical data and hydrological survey data, exploratory research about regional geothermal resource potential prediction can be made.The number of hot springs in the Changbai Mountain area is big, and extensional fracture is well-developed, creating very favorable conditions for geothermal occurrence. This paper focuses on the Changbai Mountain and the surrounding region in China to expand research, using remote sensing images to interpret faults in the study area, making the Euclidean distance as a carrier to achieve a conversion of qualitative interpretation results to quantitative model feature variables, thereby obtaining fracture factor layer. Si and hydroxyl alteration information can be extracted by remote sensing images, hydrothermal alteration factor layer of the study area is formed after fusion of Si and hydroxyl alteration information. We use radiative transfer equation to achieve land surface temperature of study area as land surface temperature factor layer; in combination with aeromagnetic data, Bouguer gravity data and hydrogeological survey point data, introducing the Logistic binary variable regression analysis to construct geothermal resource potential prediction model of the study area, and finally the model is applied to the entire study area, form the map of geothermal resource potential prediction tendency, and make analysis of the tendency map above. We achieve the following key results:1.The land surface temperature data obtained by the remote sensing inversion intuitively displays the distribution of land surface temperature field of the study area, the land surface temperature distribution characteristics and the distribution of known geothermal resource exists a significant correlation.2.Hydroxyl and Si alteration integrated information obtained by remote sensing inversion can be regarded as hydrothermal alteration information layer to the geothermal potential prediction model, whether this independent variable factor joins and not joins the model building, the model predicts similar results, indicating that the water thermal alteration factor has no significant impact on the geothermal resources potential prediction of the study area. This matches that high vegetation cover and thickness of basalt and other land surface environment in the study area will be a greater degree of influence of hydrothermal alteration information extraction results.3.The paper applies remote sensing data, introducing aeromagnetic, gravity, and hydrographic survey data, by a dichotomous Logistic regression equation, this paper tries to build a geothermal quantitative prediction model for the study area, establishes a new forecast model about the geothermal resources of the area, designs primary, secondary and tertiary prospect of geothermal survey.4.Through remote sensing interpretation of the faults structure in the area, the paper gives a complete system summarizes about the overall pattern of the region’s geological structure environment, Euclidean distance as the quantitative indicators of faults factor has been well applied. Regional geological structure and hydrology survey data both give a good validation about the geothermal resource potential prediction map of study area, proving that geothermal resource potential prediction of study area has a high reliability as a whole, can provide valuable reference information for the further investigation of regional geothermal resources.