摘要
水温观测数据主要反映地热场的变化,数据产品服务于安徽省及邻区中、短、临地震预测与科学研究。全面梳理和分析安徽省地下流体水温测项的观测效能,一方面为改进安徽省水温测项的观测技术、提升观测质量提供依据;另一方面为流体异常核实、异常分析和异常性质的判定提供参考,为科学研判安徽及其邻区的震情形势提供科学依据。
Seismic Subsurface Fluid Science is a science that studies the role and response characteristics of the earth's fluid layer in the processes of earthquake preparation,occurrence,tectonic movement,and earthquake disasters.The water temperature observation data mainly reflects the changes in the geothermal field,and the data products serve the prediction and scientific research of medium,short,and imminent earthquakes in Anhui Province and neighboring areas.This project is based on the basic information,observation data,and seismic examples of various observation wells,comprehensively sorting and analyzing the observation efficiency of subsurface fluid water temperature measurement items in Anhui Province.On the one hand,it provides a basis for improving the observation technology and improving the observation quality of water temperature measurement items in Anhui Province.On the other hand,it provides a reference for fluid anomaly verification,analysis,and determination of anomaly properties,and provides a scientific basis for scientifically studying the seismic situation in Anhui Province and neighboring areas.
作者
朱玉娟
车濛琪
方震
朱厚林
吴婉楠
ZHU Yujuan;CHE Mengqi;FANG Zhen;ZHU Houlin;WU Wannan(Dabie Mountain Earthquake Monitoring and Forecasting Experimental Site,Lu'an,Anhui Province,237000 China;Lu'an Earthquake Monitoring Center Station,Lu'an,Anhui Province,237000 China;Anhui Mengcheng National Field Scientific Observation and Research Station,Mengcheng,Anhui Province,233500 China;Mengcheng Earthquake Monitoring Center Station,Mengcheng,Anhui Province,233500 China;Anhui Key Laboratory of Subsurface Exploration and Earthquake Hazard Risk Prevention(in prep.),Hefei,Anhui Province,230031 China)
出处
《科技资讯》
2024年第16期225-228,共4页
Science & Technology Information
基金
安徽省地震局科研合同制课题(项目编号:2023HT01)资助。
关键词
地下流体
水温
效能评估
观测质量
Subsurface fluids
Water temperature
Efficiency evaluation
Observation quality
