基于大数据分析的地热勘探潜力区预测方法的新进展

地质、地球物理、地球化学等数据信息资料是预测地热系统的关键。热源、流体或热量的运移途径、地热储层、盖层和保温条件对一个有效的地热系统的形成和保存至关重要。同时,地热勘探应考虑地形、地震活动、野生动物保护、环境敏感区和基础设施等因素。全球地热数据库调研分析表明:目前只有以美国为代表的少数国家整合了不同的地热数据库中历史积累的数据,能够初步用于地热勘探潜力区预测。大多数其他国家和地区的地热数据库数据缺乏统一的数据组织方式,查询和分析功能不完善,无法进行深层次的数据挖潜及有效使用。地理信息系统工具和数学方法的引入,有可能是解决这一问题的途径,可以整合不同属性的数据,运用模糊逻辑方法或机器学习方法方法,叠加潜力区带分析思想,从而预测隐藏式地热系统。

Recent Advances in the Data-driven Play Fairway Analysis for Geothermal Exploration

Geological, geophysical and geochemical data, as well as data from other related areas, are key elements to predict a geothermal system. Heat source, migration pathways for fluids or heat, geothermal reservoir, cap rock, and heat preservation conditions are all critical for the formation and preservation of a working geothermal system. At the same time, the topography, seismicity, wildlife protection, environmentally sensitive area and infrastructure all should be evaluated for geothermal exploration. Our survey on geothermal databases showed that the historically accumulated data have been organized in different geothermal databases under different formats. These databases belong to only a few countries and as a result accumulate data mainly from their area. Large amount of data from other regions is still scattered and in an unorganized condition. Geographic Information System tools and mathematical methods might be helpful to solve this problem. Play fairway analysis with fuzzy logic technique or machine learning approach could be used to analyse the different types of data, and then predict the hidden geothermal system.