Multiple-point statistical simulation of the ore boundaries for a lateritic bauxite deposit

被引:18
|
作者
Dagasan, Y. [1 ]
Erten, O. [2 ]
Renard, P. [1 ]
Straubhaar, J. [1 ]
Topal, E. [2 ]
机构
[1] Univ Neuchatel, Ctr Hydrogeol & Geotherm, Rue Emile Argand 11, CH-2000 Neuchatel, Switzerland
[2] Curtin Univ, Western Australian Sch Mines, Dept Min & Met Engn, Kalgoorlie, WA 6430, Australia
关键词
Multiple-point statistics; Direct sampling; Bauxite mining; Stratified; Laterite; Geostatistics; Resource estimation; GROUND-PENETRATING RADAR; CONDITIONAL SIMULATION; STOCHASTIC SIMULATION; UNCERTAINTY; PATTERNS;
D O I
10.1007/s00477-019-01660-8
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Resource estimation of mineral deposits requires spatial modelling of orebody boundaries based on a set of exploration borehole data. Given lateritic bauxite deposits, the spacing between the boreholes is often determined based on the grade continuity. As a result, the selected drill spacing might not capture the underlying (true) lateral variability apparent in the orebody boundaries. The purpose of this study is to investigate and address the limitations imposed by such problems in lateritic metal deposits through multiple-point statistics (MPS) framework. Rather than relying on a semivariogram model, we obtain the required structural information from the footwall topographies exposed after previous mining operations. The investigation utilising the MPS was carried out using the Direct Sampling (DS) MPS algorithm. Two historical mine areas along with their mined-out surfaces and ground penetrating radar surveys were incorporated as a bivariate training image to perform the MPS simulations. In addition, geostatistical simulations using the Turning Bands method were also performed to make the comparison against the MPS results. The performances were assessed using several statistical indicators including higher-order spatial cumulants. The results have shown that the DS can satisfactorily simulate the orebody boundaries by using prior information from the previously mined-out areas.
引用
收藏
页码:865 / 878
页数:14
相关论文
共 50 条
  • [1] Multiple-point statistical simulation of the ore boundaries for a lateritic bauxite deposit
    Y. Dagasan
    O. Erten
    P. Renard
    J. Straubhaar
    E. Topal
    [J]. Stochastic Environmental Research and Risk Assessment, 2019, 33 : 865 - 878
  • [2] Automatic Parameter Tuning of Multiple-Point Statistical Simulations for Lateritic Bauxite Deposits
    Dagasan, Yasin
    Renard, Philippe
    Straubhaar, Julien
    Erten, Oktay
    Topal, Erkan
    [J]. MINERALS, 2018, 8 (05)
  • [3] Using the Snesim program for multiple-point statistical simulation
    Liu, Yuhong
    [J]. COMPUTERS & GEOSCIENCES, 2006, 32 (10) : 1544 - 1563
  • [4] Reconstruction of Missing GPR Data Using Multiple-Point Statistical Simulation
    Zhang, Chongmin
    Gravey, Mathieu
    Mariethoz, Gregoire
    Irving, James
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2024, 62 : 1 - 17
  • [5] GPU-based SNESIM implementation for multiple-point statistical simulation
    Huang, Tao
    Lu, De-Tang
    Li, Xue
    Wang, Lei
    [J]. COMPUTERS & GEOSCIENCES, 2013, 54 : 75 - 87
  • [6] Hierarchical multiple-point simulation of multiple facies
    Maharaja, A
    [J]. GIS and Spatial Analysis, Vol 1and 2, 2005, : 737 - 742
  • [7] GPU-accelerated Direct Sampling method for multiple-point statistical simulation
    Huang, Tao
    Li, Xue
    Zhang, Ting
    Lu, De-Tang
    [J]. COMPUTERS & GEOSCIENCES, 2013, 57 : 13 - 23
  • [8] Modelling a complex gold deposit with multiple-point statistics
    van der Grijp, Yelena
    Minnitt, Richard
    Rose, David
    [J]. ORE GEOLOGY REVIEWS, 2021, 139
  • [9] A workflow for multiple-point geostatistical simulation
    Liu, YH
    Harding, A
    Gilbert, R
    Journel, A
    [J]. Geostatistics Banff 2004, Vols 1 and 2, 2005, 14 : 245 - 254
  • [10] Pilot points method for conditioning multiple-point statistical facies simulation on flow data
    Ma, Wei
    Jafarpour, Behnam
    [J]. ADVANCES IN WATER RESOURCES, 2018, 115 : 219 - 233