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基于蒙特卡罗法的地热资源评价——以河北省雄县地热田为例
引用本文:韩征,崔一娇,王树芳,李潇,孙颖.基于蒙特卡罗法的地热资源评价——以河北省雄县地热田为例[J].城市地质,2015(4):58-62.
作者姓名:韩征  崔一娇  王树芳  李潇  孙颖
作者单位:1. 北京市地勘局信息中心,北京,100195;2. 北京市水文地质工程地质大队,北京,100195
摘    要:蒙特卡罗方法也称为统计模拟方法,是一种以概率统计理论为指导的数值计算方法,被广泛的应用于金融工程学、宏观经济学、计算物理学等领域,取得了良好的应用效果。本文介绍了蒙特卡罗法的基本数学原理及在地热资源评价中的应用方法,结合河北省雄县地热田,阐述了地热资源评价过程中蒙特卡罗计算模型的建构方法,随机变量经验分布函数的构造、抽样方法,以及资源量分布函数的建立方法。评价结果显示,在回收率为0.1%~1%的条件下,热储100年内可开采热能位于1.53×10~(17)J~9.49×10~(17)J之间的概率为90%,平均可开采热能值为5×10~(17)J,100年内可开采的热能大于2.39×10~(17)J的可能性为90%,评价结果可为雄县地热资源开发利用的未来规划提供科学依据。

关 键 词:地热  蒙特卡罗  热储  分布函数  随机数

Geothermal Resource Assessment based on Monte-Carlo Method-A Case Study of Geothermal Field in Xiong County of Hebei Province
Abstract:The Monte Carlo method is also known as a statistical simulation method. It is a very important calculation method based on the theory of probability and statistics, and widely used in the fields of financial engineering, macroeconomics, computational physics and so on. Its application effects show obviously. This paper introduced the mathematical principle of Monte Carlo method and its application in the evaluation of geothermal resources. Combined with an example of Xiongxian geothermal ifeld, this paper expounds the construction method of Monte Carlo calculation model, the construction and sampling method of empirical distribution function, and the establishment method of the resource distribution function. The assessment results show that on the conditions of recovery factor ranges from 0.1% to 1%;reservoir system possess of 5×1017J thermal energy on average for the next 100 years, and the probability can be up to 90% with the thermal energy storage from 1.53×1017J to 9.49×1017J. The cumulative distribution shows that the thermal energy storage is greater than 2.39×1017J with the probability of 90%for the next 100 years. The evaluation results can provide a scientiifc basis for the future planning of the development and utilization of geothermal resources in Xiong County.
Keywords:Geothermal energy  Monte Carlo method  Thermal energy storage  Distribution function  Random number
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