基于参数辨识的典型区地热资源量研究:以银川平原西部斜坡区为例
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本文为中国地质调查项目(编号 DD20190555)资助成果。


Calculation of geothermal resources based on parameter identification——a case study from the western slope of the Yinchuan plain
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    摘要:

    通过地温监测、含水层结构和岩性构造辨识,剖析了银川平原西部斜坡区地热田的地温场特征和热储层分布规律,确定了热储随机变量,并分别利用随机变量频率分布和三角分布等蒙特卡罗统计手段识别了随机变量参数,结合热储法计算了典型区地热资源量。研究结果表明:银川平原地热田属深循环中低温传导型地热系统,共分为5个构造分区(西部斜坡区、中部深陷区、东部斜坡凹陷区、东部斜坡隆起区和南部斜坡区)和4个热储层(新近系干沟河组、新近系红柳沟组、古近系清水营组和奥陶系马家沟组)。研究区地热资源储量丰富,垂直地温场温度与地层深度呈正相关关系,主要热储层位于400~800m的渐新统清水营组;研究区热储随机变量包括热储温度、岩石孔隙率、岩石比热容和岩石密度等参数,热储温度随机分布频率为25%、50%、75%、97. 5%的西部斜坡区地热资源量在175. 56×10↑14~230. 04×10↑14 kJ之间,其中,75%的热储温度随机分布频率可作为研究区热储温度随机变量的优选频率,该频率下地热资源储量与热储法分层计算结果标准差仅为4. 21%;利用热储特征分析和蒙特卡洛法的参数识别,能够克服热储层参数的强烈空间变异,为快速精准评价区域地热资源量和科学开发利用地热资源提供新途径。

    Abstract:

    Through ground temperature monitoring, identification of aquifer structures and lithologic structures, this paper analyzes the characteristics of ground temperature field and the distribution law of thermal reservoirs in the western slope region of the Yinchuan plain, determines the random variables of thermal storage, and uses Monte Carlo statistical means such as the frequency distribution and the triangular distribution to identify the parameters of random variables, and calculates the amount of geothermal resources in typical areas by means of thermal storage method. The research results show that the geothermal field of the Yinchuan plain is a deep- cycle low- temperature and low- temperature conductive geothermal system, which is divided into 5 tectonic zones (Western Slope Area, Central Deep Area, Eastern Slope Depression Area, Eastern Slope Rise Area and Southern Slope Area) and 4 thermal reservoirs (the Neogene Gangouhe Formation and the Hongliugou Formation, the Paleogene Qingshuiying Formation, the Ordovician Majiagou Formation). There is a positive correlation between the temperature of vertical ground temperature field and the depth of formations in the study area. The geothermal resources are abundant in this area, and the main thermal reservoirs are located at the 400~800m. The random variables are thermal storage temperature, rock porosity, rock specific heat capacity and rock density. The geothermal resources of western slope with temperature random frequency of 25%, 50%, 75% and 97. 5% range from 175. 56×10↑14 kJ to 230. 04×10↑14 kJ, among which the frequency of 75% can be selected as the optimal choice for the temperature random variable in the study area. The standard deviation between the geothermal resources reserves and the thermal storage method stratification calculation results is only 4. 21%. The strong spatial variation of thermal reservoir parameters can be overcome by using thermal storage characteristic analysis and Monte Carlo method parameter identification, which provides a novel method for rapid and accurate evaluation, scientific exploitation and utilization of the geothermal resources.

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引用本文

何雨江,丁祥.2020.基于参数辨识的典型区地热资源量研究:以银川平原西部斜坡区为例[J].地质学报,94(7):2131-2138.
HE Yujiang, DING Xiang.2020. Calculation of geothermal resources based on parameter identification——a case study from the western slope of the Yinchuan plain[J]. Acta Geologica Sinica,94(7):2131-2138.

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  • 收稿日期:2020-05-11
  • 最后修改日期:2020-06-04
  • 录用日期:2020-06-06
  • 在线发布日期: 2020-06-09
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