Error analysis and visualization of 3D geological models of mineral deposits

被引:1
作者
Chen, Yingxian [1 ]
Ma, Huiru [1 ]
Zhu, Zhe [1 ]
Fu, Jiepeng [1 ]
机构
[1] Liaoning Tech Univ, Coll Mines, Fuxin 123000, Peoples R China
基金
中国国家自然科学基金;
关键词
Error; Geological model; Mineral deposits; Kriging interpolation; Visualization; UNCERTAINTY;
D O I
10.1016/j.oregeorev.2024.106366
中图分类号
P5 [地质学];
学科分类号
0709 ; 081803 ;
摘要
The accuracy of 3D geological models of mineral deposits has a significant impact on the precision and reliability of mining production decisions. High-precision 3D geological models can provide more accurate geological information of mineral deposits. A scientific error analysis method is proposed to quantify the errors in geological models and visualize these errors by assigning them to geological model entities. The errors in 3D geological models of mineral deposits mainly originate from modeling data and interpolation methods. By analyzing the generation and processing of modeling data, an error model for the modeling data is established. The Kriging interpolation method is used to quantitatively describe the errors in the modeling methods, and these errors are integrated into the 3D geological model. By using Boolean operations, the 3D geological model is combined with the open-pit mine entity model to generate an error-containing mining site model and mined rock model, and to calculate their mining and stripping volumes and errors, achieving error visualization. Using an open-pit coal mine in Inner Mongolia as a case study, the construction of its 3D mineral deposit and mining field models demonstrates the effectiveness and superiority of the proposed method in practical applications, highlighting its importance in improving the accuracy and reliability of mining production decisions.
引用
收藏
页数:11
相关论文
共 46 条
[31]   Uncertainty assessment in 3-D geological models of increasing complexity [J].
Schweizer, Daniel ;
Blum, Philipp ;
Butscher, Christoph .
SOLID EARTH, 2017, 8 (02) :515-530
[32]   Random Forest Spatial Interpolation [J].
Sekulic, Aleksandar ;
Kilibarda, Milan ;
Heuvelink, Gerard B. M. ;
Nikolic, Mladen ;
Bajat, Branislav .
REMOTE SENSING, 2020, 12 (10)
[33]  
Shi W, 2010, PRINCIPLES OF MODELING UNCERTAINTIES IN SPATIAL DATA AND SPATIAL ANALYSES, P1
[34]  
State Administration of Work Safety of the People's Republic of China, 2007, The Greater Mekong Subregion includes Cambodia, Lao PDR, Myanmar, Thailand, Vietnam and Yunnan Province of the People's Republic of China.
[35]  
Turner A.K., 2021, Applied Multidimensional Geological Modeling: Informing sustainable human interactions with the shallow subsurface
[36]  
[王新苗 Wang Xinmiao], 2021, [煤田地质与勘探, Coal Geology & Exploration], V49, P93
[37]   3-D Structural geological models: Concepts, methods, and uncertainties [J].
Wellmann, Florian ;
Caumon, Guillaume .
ADVANCES IN GEOPHYSICS, VOL 59, 2018, 59 :1-121
[38]   Towards incorporating uncertainty of structural data in 3D geological inversion [J].
Wellmann, J. Florian ;
Horowitz, Franklin G. ;
Schill, Eva ;
Regenauer-Lieb, Klaus .
TECTONOPHYSICS, 2010, 490 (3-4) :141-151
[39]   Three-dimensional geological modeling and its application in Digital Mine [J].
Wu Qiang ;
Xu Hua .
SCIENCE CHINA-EARTH SCIENCES, 2014, 57 (03) :491-502
[40]   Post-processing for uncertainty reduction in computed 3D geological models [J].
Yamamoto, Jorge Kazuo ;
Koike, Katsuaki ;
Kikuda, Antonio Tadashi ;
da Cruz Campanha, Ginaldo Ademar ;
Endlen, Arthur .
TECTONOPHYSICS, 2014, 633 :232-245