Application and development trend of geostatistics in the research of spatial variation of aquifer parameters
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摘要: 科学合理评价地下水资源，对统筹规划、合理开发利用区域地下水，保障区域生态环境安全至关重要。获取含水层参数空间变异规律是解决地下水渗流、污染物运移、地下水开发利用等诸多地下水问题的重要基础。然而，受常规勘察技术所限，含水层非均质性难以直接刻画。两点地质统计学通过变异函数确定随机变量相关关系，解决地质变量空间线性估计并表征其各向异性；多点地质统计学突破了空间两点间相关关系的局限，通过多点训练图像建模，有效反映含水层参数变量空间分布特征，也更适合模拟复杂结构地质体。据此，本文对常用的两点地质统计学在含水层参数空间变异研究中的实际应用作了简述和探讨，并以含水层渗透系数为媒介，阐述了岩土电阻率和水力梯度或水头与渗透系数在地质统计学中运用的限制性协同关系。应用对比了多点地质统计建模与传统地质统计建模相比所具有的优势，并探讨了后者受自身算法、建模方法等制约现如今仍然尚未解决的问题及未来发展方向。指出在卫星、雷达及遥感技术快速发展背景下，数据同化、机器学习等手段融合、集成和尺度推绎多源、多空间、多分辨率空间数据帮助地质统计学实现数值建模是大势所趋。Abstract: Scientific and reasonable evaluation of groundwater resources is essential for overall planning, rational development and utilization of regional groundwater, and ensuring the safety of regional ecological environment.Obtaining spatial heterogeneous distribution information of aquifer characteristics is a critical first step in resolving a variety of groundwater issues, such as seepage, pollution transport, groundwater development and exploitation.The heterogeneity of aquifers, however, is difficult to properly define due to the limitations of traditional survey equipment.Two-point geostatistics determines the correlation of random variables through variogram, solves the spatial linear estimation of geological variables and characterizes their anisotropy.Multi-point geostatistics breaks through the limitation of spatial correlation between two points, and effectively reflects the spatial distribution characteristics of aquifer parameters through multi-point training image modeling, which is also more suitable for simulating complex geological bodies.Based on this, the paper briefly describes and discusses the commonly used two-point geostatistics in the assessment of the spatial variation of aquifer parameters.Furthermore, the hydraulic conductivity is utilized as a medium to summarize the restricted synergistic relationships between hydraulic conductivity and electrical resistivity, hydraulic gradient or hydraulic head in two-point geostatistics.Besides, the advantages of multi-point geostatistical modeling are summarized after being compared with traditional geostatistical modeling.The unsolved problems and future development direction by its own algorithms and modeling methods are also discussed.Meanwhile, it is also pointed out that under the background of the rapid development of satellite, radar and remote sensing technology, the arrival of geological big data era shows a general trend that multi-source, multi-spatial and multi-resolution spatial data can be integrated and scale-driven by data assimilation, machine learning and other methods to help geostatistics achieve numerical modeling.
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Key words:
- aquifer parameters /
- geostatistics /
- spatial variability /
- geological big data
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图 1 特异值出现的变异函数
γK(x, h)为区域化变量K(x)在x方向上的变异函数
Figure 1. Graph of variogram with singular values
图 2 OK法估值与观测值对比分析(据文献[63]修改)
Figure 2. Comparative and analysis of valuation and observed values with OK method
图 3 对数渗透系数OK法估值效果与观测数据累计概率分布曲线对比[64]
Figure 3. Comparison of curves of the cumalative probability distribution of valuation and observed values with logarithm permeability coefficient OK method
图 4 岩土电阻率和含水层渗透系数关系(据文献[77]修改)
Figure 4. Relationship between rock resistivity and aquifer hydraulic conductivity
图 6 不同岩性渗透系数K与水力梯度I关系曲线[83]
Figure 6. Relationship between permeability coefficient (K) and hydraulic gradient (I) of different lithologies
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