基于转移概率地质统计的淮南顾桥矿区松散层含水介质刻画

doi:10.19657/j.geoscience.1000-8527.2022.003

现代地质 ›› 2022, Vol. 36 ›› Issue (02): 602-609.DOI: 10.19657/j.geoscience.1000-8527.2022.003

基于转移概率地质统计的淮南顾桥矿区松散层含水介质刻画

邓辉(), 马雷(), 高迪, 赵卫东, 杨曼

合肥工业大学资源与环境工程学院,安徽合肥 230009

收稿日期:2021-09-05 修回日期:2022-02-20 出版日期:2022-04-10 发布日期:2022-06-01
通讯作者: 马雷
作者简介:马雷,男,博士,副教授,硕士生导师,1985年出生,地质学专业,主要从事裂隙水运移多尺度模拟方面的研究。Email:Lei8505@hfut.edu.cn。
邓辉,男,硕士研究生,1997年出生,地质工程专业,主要从事水文地质与工程地质方面的研究。Email: 2019170679@mail.hfut.edu.cn。
基金资助:
国家自然科学基金项目(41831289);国家自然科学基金项目(42072276);国家自然科学基金项目(41972278)

Aquifer Medium Characterization of Unconsolidated Deposit in Guqiao Mining Area of Anhui Province, Based on Transition Probability Geostatistics

DENG Hui(), MA Lei(), GAO Di, ZHAO Weidong, YANG Man

School of Resources and Environmental Engineering, Hefei University of Technology, Hefei, Anhui 230009, China

Received:2021-09-05 Revised:2022-02-20 Online:2022-04-10 Published:2022-06-01
Contact: MA Lei

摘要/Abstract

摘要：

含水介质的空间分布及其非均质性对地下水流和溶质运移有着重要的影响。以淮南顾桥矿区作为研究对象,为了刻画矿区松散层含水介质的空间分布,使用转移概率地质统计方法建立含水介质的随机模型,对矿区水文地质结构的空间连续性和空间变异性进行表征;并将随机模拟得到的顾桥矿区含水介质剖面图与矿区原始水文地质剖面进行对比。结果表明,基于转移概率地质统计模拟方法可以比较准确地刻画矿区的水文地质结构;模拟剖面与原始水文地质剖面的比较显示模拟结果与实际含水介质空间分布情况有较好的一致性,转移概率地质统计方法在对含水介质非均质性刻画中具有较好的适用性。

关键词: 转移概率地质统计, 马尔可夫链, 随机模拟, 顾桥矿区, 含水介质

Abstract:

Spatial distribution and heterogeneity of aquifer medium have critical influence on groundwater flow and solute transport. To characterize the spatial distribution of aquifer medium, the Guqiao mining area in Anhui Province was investigated, and the stochastic model of aquifer medium was established through transition probability geostatistics. We characterize the spatial continuity and variability of the hydrogeological structure of the mining area. Moreover, the local simulated profiles obtained by stochastic simulation were compared with the original hydrogeological profiles. Our results show that the conditional simulation method based on transition probabilities can accurately depict the local hydrogeological structure. Comparing the simulated profiles with the original ones, we found that the simulated results are consistent with the actual spatial distribution of the aquifer medium. This shows that the transition probability geostatistics approach can well adapt to characterize the he-terogeneity of aquifer medium.

Key words: transition probability geostatistics, Markov chain, stochastic simulation, Guqiao mine, aquifermedium

中图分类号:

P641.4

邓辉, 马雷, 高迪, 赵卫东, 杨曼. 基于转移概率地质统计的淮南顾桥矿区松散层含水介质刻画[J]. 现代地质, 2022, 36(02): 602-609.

DENG Hui, MA Lei, GAO Di, ZHAO Weidong, YANG Man. Aquifer Medium Characterization of Unconsolidated Deposit in Guqiao Mining Area of Anhui Province, Based on Transition Probability Geostatistics[J]. Geoscience, 2022, 36(02): 602-609.

图/表 6

图1 研究区范围与钻孔分布信息

Fig.1 Location of the study area and borehole locations

图2 顾桥矿区松散层含水介质转移概率模型模拟结果

Fig.2 Simulated aquifer medium model of the unconsolidated formation in the Guqiao mine with transition probability geostatistics

图3 三线模拟剖面(a)与原始水文地质剖面(b)对比图(剖面位置见图1)

Fig.3 Comparison of the simulated profile (a) with the original hydrogeological profile (b) of Line 3 (profile’s location denoted in Fig.1)

图4 十三线模拟剖面(a)与原始水文地质剖面(b)对比图(剖面位置见图1)

Fig.4 Comparison of the simulated profile (a) with original hydrogeological profile (b) of Line 13 (profile’s location denoted in Fig.1)

图5 十五线模拟剖面(a)与原始水文地质剖面(b)对比图(剖面位置见图1)

Fig.5 Comparison of the simulated profile (a) with the original hydrogeological profile (b) of Line 15 (profile’s location denoted in Fig.1)

图6 二十线模拟剖面(a)与原始水文地质剖面(b)对比图(剖面位置见图1)

Fig.6 Comparison of the simulated profile (a) with the original hydrogeological profile (b) of Line 20 (profile’s location denoted in Fig.1)

参考文献 27

[1]	张人权, 梁杏, 靳孟贵, 等. 水文地质学基础[M]. 北京: 地质出版社, 2011: 1-2.
[2]	CARLE S F, FOGG G E. Transition probability-based indicator geostatistics[J]. Mathematical Geology, 1996, 28: 453-476.
[3]	DEUTSCH C V, COCKERHAM P W. Practical considerations in the application of simulated annealing to stochastic simulation[J]. Mathematical Geology, 1994, 26(1): 67-82.
[4]	STREBELLE S, PAYRAZYAN K, CAERS J. Modeling of a deepwater turbidite reservoir conditional to seismic data using multiple-point geostatistics[J]. SPE Journal, 2002, 8: 227-235.
[5]	DELL’ARCIPRETE D, BERSEZIO R, FELLETTI F, et al. Comparison of three geostatistical methods for hydrofacies simulation: a test on alluvial sediments[J]. Hydrogeology Journal, 2012, 20(2): 299-311.
[6]	DALL’ALBA V, RENARD P, STRAUBHAAR J, et al. 3D multiple-point statistics simulations of the roussillon continental pliocene aquifer using DeeSse[J]. Hydrology and Earth System Sciences, 2020, 24(10): 4997-5013.
[7]	何芳, 吴吉春. 基于马尔可夫链的多元指示地质统计模型[J]. 水文地质工程地质, 2003, 30(5): 28-32.
[8]	LEE S Y, CARLE S F, FOGG G E. Geologic heterogeneity and a comparison of two geostatistical models: Sequential Gaussian and transition probability-based geostatistical simulation[J]. Advances in Water Resources, 2007, 30(9): 1914-1932.
[9]	吴诚云. 基于有限钻孔的三维地层结构模拟研究[D]. 哈尔滨: 哈尔滨工业大学, 2019.
[10]	刘景兰, 李立伟. 基于转移概率的三维水文地质结构划分[J]. 矿产勘查, 2020, 11(8): 1754-1758.
[11]	孙倩, 邵景力, 崔亚莉, 等. 基于三维随机水文地质结构模型的地下水流数值模拟: 以西辽河平原为例[J]. 现代地质, 2019, 33(2): 451-460.
[12]	马雷. 非均质多孔介质多尺度模型及其在地下水模拟中的应用[D]. 合肥: 合肥工业大学, 2013.
[13]	SONG X, CHEN X, YE M, et al. Delineating facies spatial distribution by integrating ensemble data assimilation and indicator geostatistics with level-set transformation[J]. Water Resources Research, 2019, 55: 2652-2671.
[14]	曾献奎. 地下水流数值模拟不确定性分析与评价[D]. 南京: 南京大学, 2012.
[15]	陈自然. 小滦河上游地区地下水流数值模拟[D]. 北京: 中国地质大学(北京), 2020.
[16]	吴乐, 张有全, 宫辉力, 等. 北京市西山地区地下水数值模拟及预测[J]. 水文地质工程地质, 2016, 43(3): 29-36.
[17]	孙倩. 基于T-PROGS的地下水流随机模拟方法改进和应用[D]. 北京: 中国地质大学(北京), 2019.
[18]	HE X, KOCH J, SONNENBORG T O, et al. Transition probability-based stochastic geological modeling using airborne geophysical data and borehole data[J]. Water Resources Research, 2014, 50(4): 3147-3169.
[19]	CHRISTENSEN N K, MINSLEY B J, CHRISTENSEN S. Generation of 3-D hydrostratigraphic zones from dense airborne electromagnetic data to assess groundwater model prediction error[J]. Water Resources Research, 2017, 53: 1019-1038.
[20]	蔡永敏. 基于有限钻孔的土体成层结构及空间变异性研究[D]. 哈尔滨: 哈尔滨工业大学, 2017.
[21]	程利力, 陈健, 陈睿, 等. 基于二维马尔可夫链的武汉长江公铁隧道地层识别[J]. 土木工程与管理学报, 2021, 38(1):169-174.
[22]	祁小辉, 李典庆, 周创兵, 等. 基于钻孔资料的耦合马尔可夫链水平方向转移概率矩阵估计[J]. 应用基础与工程科学学报, 2017, 25(5): 967-984.
[23]	邓志平, 李典庆, 祁小辉, 等. 基于广义耦合马尔可夫链的地层变异性模拟方法[J]. 岩土工程学报, 2018, 40(11): 2041-2050.
[24]	HE X, HOJBERG A L, JORGENSEN F, et al. Assessing hydrological model predictive uncertainty using stochastically generated geological models[J]. Hydrological Processes, 2015, 29: 4293-4311.
[25]	张东明, 代鉷锋, 王慧, 等. 考虑地层变异的浅基础承载力分析[J]. 地下空间与工程学报, 2020, 16(5): 1412-1419.
[26]	DEUTSCH C V, JOURNEL A G. GSLIB, Geostatistical Software Library and User’s Guide[M]. New York: Oxford University Press, 1992.
[27]	CARLE S F. Implementation schemes for avoiding artifact discontinuities in simulated annealing[J]. Mathematical Geology, 1997, 29(2): 231-244.

基于转移概率地质统计的淮南顾桥矿区松散层含水介质刻画

Aquifer Medium Characterization of Unconsolidated Deposit in Guqiao Mining Area of Anhui Province, Based on Transition Probability Geostatistics

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