Coupled modeling between geological structure fields and property parameter fields in 3D engineering geological space

Abstract 3D geological modeling is becoming ubiquitous in the visualization and analysis of the subsurface geological characterization that involves both geometrical structure and various properties. The engineering geological space consists of two types of data fields: one is the geological structure field and the other is the property parameter field. There are two kinds of relationships, i.e. superposition and coupling, between property parameter fields and geological structure fields. While many of the current modeling techniques have proven to be quite useful for modeling and visualization of geological structures or property parameters independently, they were never designed for the purpose of handling the coupling relationship among different data fields. This shortcoming seriously limits the reliability and practicality of the computer models, and there is a pressing need to build a meaningful 3D spatial model that involves both geometry and properties. In this paper, we present a novel modeling framework for the coupled modeling and analysis of geo-objects in 3D engineering geological space. There are three innovative improvements in this framework. First, a mixed 3D spatial data model, which is a combination of boundary representation and Geocellular, is designed to address the need for the unified description of geometry and topology of geo-objects as well as their internal properties. And then, in order to obtain geologically reasonable property models controlled by geological constraints, the qualitative geological constraints are converted into quantitative control parameters in data preprocessing stage, and different property interpolation schemes are used respectively to handle different types of geo-objects. And finally, in order to gradually refine 3D geological models, the iterative modeling technique is imported, and an efficient mechanism for information feedback and error correction is set up. This coupled modeling framework is well-suited to produce detailed 3D geological models attributed with physical, chemical, engineering or hydrogeological parameters, and intuitively analyze property characteristics within each modeled unit and their spatial relationships in 3D.

[1]  X. Emery.  Properties and limitations of sequential indicator simulation , 2004 .

[2]  Robert Hack,et al.  Three and more dimensional modelling in geo-engineering , 2006 .

[3]  Hyeong-Dong Park,et al.  Development of a web-based Geographic Information System for the management of borehole and geological data , 2004, Comput. Geosci..

[4]  Zixin Zhang,et al.  Object-oriented modeling for three-dimensional multi-block systems , 2013 .

[5]  Andrew Hughes,et al.  THREE-DIMENSIONAL GEOLOGIC MAPPING FOR GROUNDWATER APPLICATIONS , 2007 .

[6]  Liang-feng Zhu,et al.  Building 3D solid models of sedimentary stratigraphic systems from borehole data: An automatic method and case studies , 2012 .

[7]  John James Quinn.  Geostatistical approaches to characterizing the hydrogeology of glacial drift. , 2009 .

[8]  Martin G. Culshaw,et al.  From concept towards reality: developing the attributed 3D geological model of the shallow subsurface , 2005, Quarterly Journal of Engineering Geology and Hydrogeology.

[9]  Hua Xu,et al.  On three-dimensional geological modeling and visualization , 2004 .

[10]  Nengxiong Xu,et al.  Building a three dimensional sealed geological model to use in numerical stress analysis software: A case study for a dam site , 2011 .

[11]  Liangfeng Zhu,et al.  Framework system and research flow of uncertainty in 3D geological structure models , 2010 .

[12]  Steven F. Carle,et al.  CONDITIONAL SIMULATION OF HYDROFACIES ARCHITECTURE: A TRANSITION PROBABILITY/MARKOV APPROACH1 , 1998 .

[13]  Arie E. Kaufman,et al.  Fundamentals of Surface Voxelization , 1995, CVGIP Graph. Model. Image Process..

[14]  David Entwisle,et al.  Benefits of a 3D geological model for major tunnelling works: an example from Farringdon, east–central London, UK , 2012 .

[15]  K. Juang,et al.  Using sequential indicator simulation to assess the uncertainty of delineating heavy-metal contaminated soils. , 2004, Environmental pollution.

[16]  L. E. Denver,et al.  Stratigraphic geocellular modeling , 1990 .

[17]  Jesús Carrera,et al.  Groundwater inflow prediction in urban tunneling with a tunnel boring machine (TBM) , 2011 .

[18]  D. Entwisle,et al.  Property attribution of 3D geological models in the Thames Gateway, London: new ways of visualising geoscientific information , 2009 .

[19]  Lixin Wu,et al.  Topological relations embodied in a generalized tri-prism (GTP) model for a 3D geoscience modeling system , 2004, Comput. Geosci..

[20]  G. Fogg,et al.  Transition probability-based indicator geostatistics , 1996 .

[21]  Holger Kessler,et al.  Unlocking the potential of digital 3D geological subsurface models for geotechnical engineers , 2008 .

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

[23]  René Therrien,et al.  Coupling geological and numerical models to simulate groundwater flow and contaminant transport in fractured media , 2009, Comput. Geosci..

[24]  Carl W. Gable,et al.  A REVIEW OF GEOLOGICAL MODELING , 2007 .

[25]  Graham E. Fogg,et al.  Multi-scale alluvial fan heterogeneity modeled with transition probability geostatistics in a sequence stratigraphic framework , 1999 .

[26]  A. Keith Turner,et al.  Challenges and trends for geological modelling and visualisation , 2006 .

[27]  Xukai Zou,et al.  An effective method for 3D geological modeling with multi-source data integration , 2005, Comput. Geosci..

[28]  G. McMechan,et al.  Building 2-D stratigraphic and structure models from well log data and control horizons , 2003 .

[29]  Laurie G. Baise,et al.  Liquefaction Hazard Mapping—Statistical and Spatial Characterization of Susceptible Units , 2006 .

[30]  Leila De Floriani,et al.  A hierarchical boundary model for solid object representation , 1988, TOGS.

[31]  Clayton V. Deutsch,et al.  GSLIB: Geostatistical Software Library and User's Guide , 1993 .

[32]  G. Fogg,et al.  Modeling Spatial Variability with One and Multidimensional Continuous-Lag Markov Chains , 1997 .

[33]  Graham E Fogg,et al.  River‐Aquifer Interactions, Geologic Heterogeneity, and Low‐Flow Management , 2006, Ground water.

[34]  Christopher B. Jones.  Data structures for three-dimensional spatial information systems in geology , 1989, Int. J. Geogr. Inf. Sci..

[35]  Steven F. Carle,et al.  Three‐dimensional hydrofacies modeling based on soil surveys and transition probability geostatistics , 1999 .

[36]  L. Jones,et al.  Engineering geology of British rocks and soils : mudstones of the Mercia Mudstone Group , 2002 .

[37]  Lewis Edgers,et al.  Three-Dimensional Characterization and Visualization of Till in Boston, Massachusetts , 2005 .

[38]  N. Jones,et al.  Building solid models from boreholes and user-defined cross-sections , 2003 .

[39]  J. Malet,et al.  Characterization of the 3D geometry of flow-like landslides: A methodology based on the integration of heterogeneous multi-source data , 2012 .