多源异构数据协同约束的贵州道坨超大型隐伏锰矿床三维地质建模技术

蔡国荣; 张夏林; 沈红钱; 田宜平; 刘健; 刘明民; 杨承梅; 刘润琴; 韩姚飞; 蒋天锐; 姚希财

doi:10.19509/j.cnki.dzkq.tb202605025

多源异构数据协同约束的贵州道坨超大型隐伏锰矿床三维地质建模技术

doi: 10.19509/j.cnki.dzkq.tb202605025

蔡国荣^{1, 2, 3, 4,},
张夏林^{1, 2, 3},
沈红钱^{1, 2, 4, ,},
田宜平^{1, 2, 3},
刘健⁴,
刘明民⁴,
杨承梅⁴,
刘润琴⁴,
韩姚飞⁴,
蒋天锐⁴,
姚希财⁴

贵州省智能找矿勘查实验室，贵阳 550081
自然资源部基岩区矿产资源勘查工程技术创新中心，贵阳 550081
中国地质大学（武汉）计算机学院，武汉 430078
贵州省地质矿产勘查开发局一〇三地质大队，贵州铜仁 554300

基金项目: 贵州省科技计划项目（黔科合重大[2025]016）；贵州省科技创新人才团队建设项目（黔科合人才CXTD[2025]026；创新平台建设计划-定向支持贵州省实验室重大科研项目（黔科合平台SSYS[2026]重大023）；铜仁市科技计划项目（铜市科研[2024]97号）；铜仁市碳酸锰矿资源综合利用实验室项目（铜碳实验室〔2025〕2号）；贵州省科技计划项目（黔科合基础QN[2026]069-01）

详细信息

作者简介:
蔡国荣：E-mail：grcai103@163.com

通讯作者:
E-mail：1024583324@qq.com

计量
- 文章访问数: 98
- PDF下载量: 7
- 被引次数: 0
出版历程
- 收稿日期: 2026-05-12
- 录用日期: 2026-07-06
- 修回日期: 2026-06-26
- 网络出版日期: 2026-07-13

3D geological modeling technology for super-large concealed Daotuo manganese deposit in Guizhou based on synergistic constraints from multi-source heterogeneous data

CAI Guorong^{1, 2, 3, 4
,},
ZHANG Xialin^{1, 2, 3},
SHEN Hongqian^{1, 2, 4
, ,},
TIAN Yiping^{1, 2, 3},
LIU Jian⁴,
LIU Mingmin⁴,
YANG Chengmei⁴,
LIU Runqin⁴,
HAN Yaofei⁴,
JIANG Tianrui⁴,
YAO Xicai⁴

Guizhou Provincial Laboratory of Intelligent Prospecting and Exploration, Guiyang 550081, China
Engineering Technology Innovation Center of Mineral Resource Exploration in Bedrock Zones, Ministry of Natural Resources, Guiyang 550081, China
School of Computer Science, China University of Geosciences (Wuhan), Wuhan 430078, China
Geology Team 103, Bureau of Geology and Mineral Exploration and Development of Guizhou Province, Tongren Guizhou 554300, China

More Information

Author Bio:
E-mail：grcai103@163.com

Corresponding author: E-mail：1024583324@qq.com

摘要

摘要:
目的
深部隐伏锰矿三维地质建模普遍存在多源勘查数据融合程度低、多类信息协同约束机制缺失、超薄层状矿体精细刻画难度大等问题。贵州道坨为超大型全隐伏喷溢沉积型锰矿床，矿体埋深大、厚度薄、成矿地质结构复杂，传统二维图件难以反映矿体真实三维赋存状态。以该矿床为研究对象，融合数字高程模型（DEM）、地质填图、钻探编录、勘查线剖面、遥感影像、音频大地电磁测深（AMT）多源异构勘查数据，构建地表−地层−构造−矿体一体化三维地质模型，为深部隐伏锰矿数字化勘查与资源定量评价提供技术支撑。
方法
建立多源异构数据标准化处理、三重一致性校验、多源信息协同约束、超薄矿体增量模拟的完整技术流程；划分 18 个地质建模单元，采用曲面拟合、拓扑推理、克里金插值完成地质体实体构建；结合 67 个钻孔、722 件有效品位样品开展品位归一化预处理，实施模型剖面解析、虚拟钻孔分析、模型拆解，基于地质统计学块体克里金法开展资源−储量估算。
结果
该模型完整复现研究区−2000 m 至地表的三维地质空间结构，清晰揭示南华系大塘坡组含锰岩系、F₃ 浅表正断层与缓倾斜层状锰矿体的空间展布规律；经多源数据一致性校验，数据源综合合格率达 97.2%；地质统计学估算结果与传统块段法资源量误差仅 0.9%，锰平均品位误差 0.31%，可有效校验原始勘查数据可靠性，厘清构造与矿体的空间耦合关系。
结论
多源异构数据协同约束建模技术能够有效解决超薄隐伏矿体建模失真难题，显著提高深部找矿工程部署与矿产资源评价精度；形成的成套技术范式，可为黔东乃至扬子地区大塘坡式隐伏锰矿深部找矿突破与矿山数字化建设提供参考。
- 三维地质建模 /
- 多源异构数据 /
- 隐伏锰矿床 /
- 地质统计学 /
- 资源评价精度
Abstract:
Objective
Deep concealed mineral exploration is a critical direction for implementing China’s new-round prospecting breakthrough strategy and securing domestic mineral resource supply. Nevertheless, three-dimensional (3D) geological modeling for deep concealed manganese deposits still faces prominent bottlenecks: low integration of multi-source exploration datasets, insufficient synergistic constraint mechanisms among multi-type geological information, and technical obstacles for fine characterization of ultra-thin stratiform ore bodies. The Daotuo deposit in Guizhou represents a typical super-large fully concealed exhalative-sedimentary manganese deposit of the Datangpo-type within the Yangtze Block. It is characterized by great burial depth, ultra-thin ore bodies, and complicated geological architectures, which cannot be adequately depicted by conventional two-dimensional geological maps. This study aims to construct an integrated 3D geological model of surface–strata–structure–ore body constrained by multi-source heterogeneous data, so as to provide technical support for digital exploration and quantitative resource assessment of deep concealed manganese ore bodies.
Methods
Multi-source heterogeneous datasets including a digital elevation model (DEM), geological mapping results, drilling logs, exploration profile data, remote sensing imagery, and audio magnetotelluric (AMT) sounding data were comprehensively integrated. A complete technical workflow was established, covering standardized multi-source data preprocessing, three-fold consistency verification, multi-information synergistic constraint, and incremental simulation for ultra-thin ore bodies. A total of 18 geological modeling units were delineated. Surface fitting, topological reasoning, and Kriging interpolation were adopted to construct solid geological bodies. Based on 67 boreholes and 971 grade samples, 722 valid samples were retained after outlier elimination and grade normalization via log-Z-score transformation. The normalized samples passed the Shapiro-Wilk normality test. Model cross-section interpretation, virtual borehole analysis, and model decomposition were implemented, and the block Kriging geostatistical method was applied for resource–reserve calculation.
Results
The established model fully reconstructed the 3D geological structure of the study area from the ground surface down to −2 000 m elevation, and clearly revealed the spatial distribution of the manganese-bearing rock series of Nanhua Series Datangpo Formation, the shallow F3 normal fault, and the gently dipping stratiform manganese ore bodies. After three-fold multi-source consistency verification, the comprehensive qualification rate of the data sources reached 97.2 %. Geostatistical resource estimation showed only 0.9 % relative discrepancy compared with the traditional block-segment method, and the error of average manganese grade was merely 0.31 %. Modeling results confirmed that the F3 fault only affected shallow strata and did not damage deep manganese ore bodies. The integrated model could effectively validate the reliability of original exploration data and clarify the spatial coupling relationships between geological structures and ore bodies.
Conclusion
The modeling technique based on synergistic constraints from multi-source heterogeneous data can effectively solve the problem of distortion frequently encountered in modeling ultra-thin concealed ore bodies, and significantly improve the precision of deep-prospecting engineering deployment and mineral resource evaluation. The formed complete technical paradigm can provide references for deep prospecting breakthroughs of Datangpo-type concealed manganese deposits and mine digital construction in eastern Guizhou and even the broader Yangtze Block.
- 3D geological modeling /
- multi-source heterogeneous data /
- concealed manganese deposit /
- geostatistics /
- resource evaluation accuracy

HTML全文

图 1 道坨锰矿床地质简图

1. 清虚洞组第二段；2. 清虚洞组第一段；3. 杷榔组；4. 变马冲组第二段；5. 变马冲组第一段；6. 九门冲组；7. 钻孔位置；8. 正断层

Figure 1. Geological map of Daotuo manganese deposit

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图 2 道坨锰矿三维建模流程图

Figure 2. Flowchart of 3D geological modeling of Daotuo manganese deposit

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图 3 道坨锰矿钻孔−勘查剖面三维数据可视化

Figure 3. 3D visualization of borehole–exploration profile data for Daotuo manganese deposit

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图 4 研究区地表三维模型

Figure 4. 3D surface model of study area

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图 5 F3 断层三维地质模型

Figure 5. 3D geological model of fault F3

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图 6 研究区地层三维地质模型

Figure 6. 3D geological stratigraphic model of study area

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图 7 道坨锰矿床锰矿体三维模型

Figure 7. 3D model of manganese ore bodies of Daotuo manganese deposit

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图 8 道坨锰矿床地表−地层−构造−矿体一体化三维地质模型

Figure 8. Integrated 3D geological model of surface-strata-structure-ore body for Daotuo manganese deposit

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表 1 锰品位预处理前后统计特征

Table 1. Statistical characteristics of manganese grade before and after preprocessing

数据分组	有效样品数/件	均值/%	标准差/%	偏度	峰度	Shapiro- Wilk P值
原始全部样品	971	16.741	7.391	0.153	1.770	0.000
数据剔除后原始样品	722	20.175	5.149	−0.210	2.203	0.000
对数-Zscore归一化样品	722	0	1	0.138	2.701	0.062
注：Shapiro-Wilk检验显著性水平α=0.05，P>0.05认为数据服从正态分布。

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表 2 多源数据一致性校验量化结果

Table 2. Quantitative results of multi-source data consistency validation

校验类型	校验样本	偏差评价指标	平均偏差
地表地质界线与 DEM匹配校验	12 km²填图区与22条界线	平面坐标偏差≤2 m	1.12
钻探分层与AMT反演界面深度对比校验	2条AMT剖面与 67个钻孔矿层界面	高程与地层深度偏差≤5 m	2.87
相邻勘查线剖面间地层与矿体空间交叉验证	10条勘探剖面与18组地层−矿体对比单元	地层厚度相对偏差≤3%	1.64
注：AMT为音频大地电磁测深；DEM为数字高程模型；下同。

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表 3 道坨锰矿床建模单元

Table 3. Modeling units of Daotuo manganese deposit

名称		代号	厚度范围/m	主要特性
地层建模单元	第四系	Q	0～36.75	地表腐植土、黏土、粉质黏土、砂、砾等
	清虚洞组二段	∈₂q²	108.56～180.56	浅灰色、灰色块状泥粉晶灰岩等
	清虚洞组一段	∈₂q¹	16.54～53.95	灰色、深灰色薄层条带状泥粉晶灰岩夹深色中层泥粉晶灰岩等
	杷榔组	∈₂p	206.91～470.88	深灰色薄层粉砂质页岩偶夹灰白色薄层粉砂岩，上部含钙质扁豆体，地表多溶蚀空洞，底部为黑色碳质页岩
	变马冲组二段	∈₂b²	133.65～357.18	灰、深灰色薄−厚层砂岩、粉砂岩、石英砂岩夹黑色碳质页岩
	变马冲组一段	∈₂b²	1.44～75.04	黑色碳质页岩、碳质黏土岩间夹粉砂质页岩
	九门冲组	∈₂jm	16.48～81.83	下部为灰黑色薄至中层含碳质泥粉−细晶灰岩与黑色碳质页岩互层，上部为灰色中厚层细晶灰岩间夹黑色碳质页岩，灰岩中方解石细脉发育
	牛蹄塘组	∈₁₋₂n	8.11～47.10	下部为黑色碳质页岩（含镍、钼、钒多金属），底部偶见豆状磷质结核，上部为灰黑色含碳质的粉砂质页岩
	老堡组	Z∈l	0.35～19.70	灰黑色薄层状硅质岩夹黑色碳质页岩，顶部见少量黑色豆状磷质结核
	陡山坨组	Z₁d	19.43～63.72	灰、深灰色薄层−厚层块状泥粉−细晶白云岩，间夹灰色薄层黏土岩及灰黑色粉砂质碳质页岩，局部可见硅化、方解石化等
	南沱组	Nh₃n	170.52～280.93	灰、深灰色块状含砾粉砂岩、含砾黏土岩、黏土岩，分选性差，间夹灰绿、黄灰色粉砂质黏土岩，中下部偶见灰色透镜状白云岩
	大塘坡组二段	Nh₂d²	108.22～312.15	灰黑色、深灰色含碳质粉砂质页岩等
	大塘坡组一段	Nh₂d¹	6.51～68.63	“含锰岩系”，全隐伏地下，岩性为灰黑色、钢灰色条带状等菱锰矿夹黑色碳质页岩等
	铁丝坳组	Nh₂t	10.65～32.09	深灰色块状含砾杂砂岩，偶夹黑色薄层含锰碳质页岩，砾石成分杂、分选性差，星点状黄铁矿发育
	两界河组	Nh₂l	21.69～67.71	上部为灰色、灰绿色厚层−块状长石岩屑杂砂岩等，下部为灰褐色、浅灰绿色中厚层−块状含砾砂质黏土岩等
	清水江组	Qbq	＞75.99	灰、灰绿色中−厚层变质粉砂岩、变质砂岩等
矿体建模单元	锰矿体	Mn	0.87～11.75	菱锰矿，伴生星点状、断线状黄铁矿，局部见石英、方解石细脉穿插
矿体建模单元	断层	F₃	—	走向NE，倾向SE，倾角58°～62°，断距小于50 m，上盘相对下降，正断层性质，发育劈理化带，仅影响浅表地层，未破坏深部锰矿体

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表 4 道坨锰矿资源量估算结果对比

Table 4. Comparison of resource estimation results for Daotuo manganese deposit

资源量类别	误差率/%	相似率/%	dn平均品位误差/%
探明资源量	0.70	99.30	0.14
控制资源量	0.62	99.38	0.26
推断资源量	1.20	98.80	0.43
整体	0.90	99.10	0.31
注：本表为地质统计学法与地质块段法资源量估算结果对比。

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