Effective coal seam surface modeling with an improved anisotropy-based, multiscale interpolation method

Abstract A reliable coal seam model is highly significant for mining design and resource assessment. However, due to the anisotropic nature of geological attributes, accurately modeling the surface using existing interpolation methods is difficult. Here, we propose a new method for coal seam surface modeling. First, we introduce a multiscale interpolation method using compactly supported radial basis functions (CSRBFs) and improve the modeling accuracy by anisotropy calculations using the raw mine data set. Then a fault modeling method is provided to simulate faults intersecting with coal seams. This method consists of three main parts: (1) anisotropy calculation to alleviate the effects of global anisotropy; (2) rapid coal seam surface modeling of large amounts of nonuniform data through an anisotropic multiscale CSRBF method and then visualization and organization of the surface into a triangulated irregular network (TIN); and (3) local reconstruction of the coal seam surface according to the faults. A prototype system was developed based on this method to build a coal seam model from the collected multisource coal seam data. A comparison with three existing interpolation methods shows that this method is feasible and time efficient and achieves higher accuracy than previous methods. We anticipate that the method can provide a reference for advances in digital and smart mines as well as 3D geological modeling.

[1]  R. Franke Scattered data interpolation: tests of some methods , 1982 .

[2]  Cheng-Tiao Hsieh An efficient development of 3D surface registration by Point Cloud Library (PCL) , 2012, 2012 International Symposium on Intelligent Signal Processing and Communications Systems.

[3]  Olivier Kaufmann,et al.  3D geological modelling from boreholes, cross-sections and geological maps, application over former natural gas storages in coal mines , 2008, Comput. Geosci..

[4]  Jeff B. Boisvert,et al.  Iterative refinement of implicit boundary models for improved geological feature reproduction , 2017, Comput. Geosci..

[5]  James F. O'Brien,et al.  Modelling with implicit surfaces that interpolate , 2002, TOGS.

[6]  A. Cruden,et al.  Regional dome evolution and its control on ore-grade distribution: Insights from 3D implicit modelling of the Navachab gold deposit, Namibia , 2015 .

[7]  Richard K. Beatson,et al.  Reconstruction and representation of 3D objects with radial basis functions , 2001, SIGGRAPH.

[8]  S. Pelizza,et al.  Subsurface geological-geotechnical modelling to sustain underground civil planning , 2008 .

[9]  Lixin Wu,et al.  Towards Automatic and Topologically Consistent 3D Regional Geological Modeling from Boundaries and Attitudes , 2016, ISPRS Int. J. Geo Inf..

[10]  Guillaume Caumon,et al.  3D geomodelling combining implicit surfaces and Voronoi-based remeshing: A case study in the Lorraine Coal Basin (France) , 2015, Comput. Geosci..

[11]  G. Caumon,et al.  Surface-Based 3D Modeling of Geological Structures , 2009 .

[12]  Bing Zhang,et al.  Coupled modeling between geological structure fields and property parameter fields in 3D engineering geological space , 2013 .

[13]  Victor J. D. Tsai,et al.  Delaunay Triangulations in TIN Creation: An Overview and a Linear-Time Algorithm , 1993, Int. J. Geogr. Inf. Sci..

[14]  C. Lawson Software for C1 Surface Interpolation , 1977 .

[15]  Clayton V. Deutsch,et al.  Programs for kriging and sequential Gaussian simulation with locally varying anisotropy using non-Euclidean distances , 2011, Comput. Geosci..

[16]  Xiaojun Li,et al.  Coal seam surface modeling and updating with multi-source data integration using Bayesian Geostatistics , 2013 .

[17]  Olivier Kaufmann,et al.  Reprint of "3D geological modelling from boreholes, cross-sections and geological maps, application over former natural gas storages in coal mines" [Computers & Geosciences 34 (2008) 278-290] , 2009, Comput. Geosci..

[18]  M. Jessell,et al.  Locating and quantifying geological uncertainty in three-dimensional models: Analysis of the Gippsland Basin, southeastern Australia , 2012 .

[19]  Jules Bloomenthal,et al.  Polygonization of implicit surfaces , 1988, Comput. Aided Geom. Des..

[20]  Hans-Peter Seidel,et al.  A multi-scale approach to 3D scattered data interpolation with compactly supported basis functions , 2003, 2003 Shape Modeling International..

[21]  Radu Bogdan Rusu,et al.  3D is here: Point Cloud Library (PCL) , 2011, 2011 IEEE International Conference on Robotics and Automation.

[22]  Z. Shipton,et al.  Fault tip displacement gradients and process zone dimensions , 1998 .

[23]  Holger Wendland,et al.  Piecewise polynomial, positive definite and compactly supported radial functions of minimal degree , 1995, Adv. Comput. Math..

[24]  Pieter Abbeel,et al.  Range sensor and silhouette fusion for high-quality 3D Scanning , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[25]  Clayton V. Deutsch,et al.  Kriging and Simulation in Presence of Stationary Domains: Developments in Boundary Modeling , 2012 .

[26]  Tomas Akenine-Möller,et al.  Fast, minimum storage ray/triangle intersection , 1997, J. Graphics, GPU, & Game Tools.

[27]  Rachida Bouhlila,et al.  3D geological modeling of the Kasserine Aquifer System, Central Tunisia: New insights into aquifer-geometry and interconnections for a better assessment of groundwater resources , 2016 .

[28]  E. Cardarelli,et al.  Underground cavity investigation within the city of Rome (Italy): A multi-disciplinary approach combining geological and geophysical data , 2013 .

[29]  E. Schetselaar,et al.  Three-Dimensional Modelling of Geological Surfaces Using Generalized Interpolation with Radial Basis Functions , 2014, Mathematical Geosciences.