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深部水热型地热潜力区的GIS预测模型——以土耳其西安纳托利亚地区为例
引用本文:张延军,余海,李建明,于子望,张佳宁.深部水热型地热潜力区的GIS预测模型——以土耳其西安纳托利亚地区为例[J].吉林大学学报(地球科学版),2016,46(3):855-864.
作者姓名:张延军  余海  李建明  于子望  张佳宁
作者单位:1. 吉林大学建设工程学院, 长春 130026; 2. 吉林大学地下水资源与环境教育部重点实验室, 长春 130026
基金项目:国家高技术研究发展计划(国家“863”计划)项目(2012AA052801),国家自然科学基金项目(41372239),高等学校博士学科点专项科研基金(20110061110055)Supported by National High-Tech R & D Program of China("863" Program)(2012AA052801)
摘    要:开发地热资源有着很大的不确定性和很高的经济风险,需要建立可靠的数学预测模型以确定潜在地热区。通过对地震震中、断层、布格重力异常、磁异常和红外遥感5个与地热密切相关的因素进行整合,建立了地热潜力区的数学预测模型;并以土耳其西安纳托利亚地区为例,对模型的优劣性进行分析评价。运用指数叠加模型和证据权重模型分别建立地热潜力区图,预测成功指数表明证据权重模型的预测结果更为准确。其中,中高潜力区总面积为26 529 km2,占总面积的31.14%,包含39个地热点,占总地热点的50.65%。预测结果显示潜在地热区位于Ayd?n,Denizli,Manisa和Bal?kesir,其中前2个地区的地热已经被开发利用。本研究可以在地热勘探阶段确定潜在地热区,降低经济风险。

关 键 词:水热型地热资源潜力  地球物理特征  多准则决策分析  GIS预测模型  
收稿时间:2015-10-11

Prediction Models of Deep Hydrothemal Geothermal Potential Areas Based on GIS:A Case Study of Western Anatolia,Turkey
Zhang Yanjun,Yu Hai,Li Jianming,Yu Ziwang,Zhang jianing.Prediction Models of Deep Hydrothemal Geothermal Potential Areas Based on GIS:A Case Study of Western Anatolia,Turkey[J].Journal of Jilin Unviersity:Earth Science Edition,2016,46(3):855-864.
Authors:Zhang Yanjun  Yu Hai  Li Jianming  Yu Ziwang  Zhang jianing
Institution:1. College of Construction Engineering, Jilin University, Changchun 130026, China;
2. Key Lab of Groundwater Resource and Environment Ministry of Education, Jilin University, Changchun 130026, China
Abstract:Geothermal exploration involves a high degree of uncertainty and financial risk, and requires reliable prediction model to identify geothermal potential areas. Mathematical prediction models were established by integrating five factors that closely related to geothermal, including earthquake epicenter, lineament, Bouger gravity anomaly, magnetic anomaly and infrared remote sensing; and the advantages and disadvantages of models were compared by an example of western Anatolia, Turkey. Index overlay(IO) and weights of evidence(WofE) were applied to establish geothermal resource potential maps, respectively. Success indices suggest that the predicting outcomes of WofE are more reliable than IO. The very favorable area and the favorable area are about 26 529 km2, accounting for 31.14% of total area, including 39 geothermal resource potential sites, which is 50.65% of the total sites.The potential areas in the WofE map are Ayd?n, Denizli, Manisa and Bal?kesir, of which the former two have been explored and exploited. This study is helpful to locate geothermal potential areas and reduce financial risk in the process of geothermal exploration.
Keywords:hydrothemal geothermal resource potential  geophysical characteristics  multicriteria decision analysis  prediction models based on GIS
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