An Overview 3-D Geological Modelling Part I-Basics of 3-D Geological Modelling

International Journal of Latest Engineering and Management Research (IJLEMR)
ISSN: 2455-4847
www.ijlemr.com || Volume 02 - Issue 11 || November 2017 || PP. 01-14
An Overview 3-D Geological Modelling Part I- Basics of 3-D

Geological Modelling
Prof. D. S. Aswar 1, Dr. P. B. Ullagaddi 2
1(Department of Civil Engineering, Sinhgad College of Engineering, Pune / SPPU, India)
2(Department of Civil Engineering, S.G.G.S. Institute of Engineering & Technology, Nanded., / SRTMU
Nanded, India)
Abstract: The paper present an overview of the Basics of 3-D Geological Modelling in the context of research
and modelling practices. It highlighted the basic of modelling, model types, its representation, diverse fields of
applications and the Limitations of 3-D Geological Modelling. Various types of modelling data, the needs and
the process of data pre-processing (data consistency & validation), are discussed in detail. The different
modelling approaches to accomplish the modelling task, and the corresponding thought process involved in the
approaches is elaborated. The different software available and their modelling and functional capabilities are
overviewed.
Keywords: Data preprocessing, Geological Models, modelling approach, Modelling Software.
I. Introduction to Geologic Models

The heterogeneous data gathered during site investigations, is not a straightforward information pool
for decision makers and the other end-users, as it needs to be reinterpreted by experts for specific purposes. The
homogenization of multiple, mostly analogous, data sets, and their subsequent integration into the modelling
process to form a 3-D structure model, adds value to the existing database information. One of the advantages
in a 3-D modelling system is the common visualization of multidisciplinary information sets and their spatial
relation in three dimensions, allowing new insights into the nature of the subsurface. It enables to visualize the
geological subsurface in terms of the lateral distribution and thickness of each geological unit as well as the
succession of the geological units. [17].
As per the Commission of the International Association for Engineering Geology and the Environment
(IAEG) working on the 'Use of Engineering Geological Models' (C25), the engineering geological models for
geotechnical project are an essential tool for engineering quality control and provide a reliable means of
identifying project-specific, critical geological issues and parameters. Models should form the basis for
designing the scope, method and assessing the effectiveness of site investigations.According to C25 the term
model in engineering geology is hypothesized as an approximation of reality created for the purpose of solving
a problem. It is an approximation of the geological conditions, at varying scales, created for the purpose of
solving an engineering problem. C25 considers that engineering geological models encompass both “geological
models” and “geotechnical models”; they involve understanding geological concepts as well as defined
geotechnical data and engineering requirements [19].According to C25 the different fundamental methodologies
used for the generation of these model types are:
a) The conceptual approach is based on understanding the relationships between engineering geological
units, their likely geometry, and anticipated distribution. This approach, is based on concepts
formulated from knowledge, experience, and are not related to real three-dimensional (3-D) space or
time. A fundamental purpose of the conceptual model is to identify the credible engineering geological
unknowns present, which can be targeted for investigation, to assess their potential hazard to the
project. The success of this approach is strongly dependent on the knowledge and experience of experts
involved in creating the models.
b. The observational engineering geological approach is based on observations and data from project-
specific ground investigations. These ground investigations should be designed using conceptual
models and should target the uncertainties identified by them. The observational engineering geological
model is created from the site-specific ground investigation information, are constrained by
observational and measured data, and should present geological information in space or time. They
should verify or refine the conceptual engineering geological model. In particular, they should focus on
potential engineering issues identified in the conceptual engineering geological model. Observational
engineering geological models are particularly relevant at the engineering design stage. The
observational engineering geological models can take a wide variety of forms: graphical borehole logs
(one-dimensional), engineering geological cross sections and maps (two dimensional) and spatial
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engineering geological models (three dimensional) either as solid models (e.g. [26]) or, increasingly,
digital models [6].
c. The Analytical Model -The analytical model requires considerable simplification of the observational
model and, therefore, significant engineering geological judgment is required to ensure that
representative ground conditions, including geotechnical parameters and boundaries, are adopted. The
aim should be to focus on a model that captures the essence of the engineering design issues, but is still
robust enough to illustrate the inherent engineering geological variability.
II. Geological Modelling Process

The spatial data are used to create a 3-D geometry model, Geometry modelling involves two steps –
first the development of a suitable geometric representation of the fundamental geological “framework,” and
subsequently the subdivision, or “discretization” of this framework to provide control for the analytical
computations within the numerical models used in the predictive modelling. Geometrical representation of the
geological framework, define and control the spatial distribution and propagation of rock-properties required by
modelling [24]. Framework definition is accomplished by applying a variety of data types, including,
i. Borehole and isolated sample data,
ii. Surfaces (Triangle, Quadrilateral, NURB- non-uniform rational B-splines),
iii. 2-D grids and meshes, and
iv. A variety of iso-volumetric models created from multiple surfaces, cross-sections, and grids and,
meshes.
2.1 Stratigraphic Models

Sedimentary geologic environments is modelled by creating surfaces defining the strata interfaces,
stacking the surfaces in stratigraphic succession, and subsequently defining the zones between surfaces as
geologic units. Careful review and editing of all surfaces is required to allow for areas of erosion or non-
deposition & mutual intersection. The Construction of individual surfaces generally proceeds by one of three
methods:
i. Using the borehole observations to create a triangles defining a surface,
ii. Applying surface generation and contouring procedures to borehole observations, or
iii. Developing a series of interpretive cross-sections between boreholes.
2.3 Non-stratigraphic models

Regions with complex geological structures, or without layered sequences, are developed by a series of
complex shapes enclosing volumes derived from a series of interpreted cross-sections with common bounding
surfaces. An alternative approach begins with an entire regional volume and then progressively subdivides it
into regions with a series of intersecting surfaces that represent major discontinuities such as shear zones or
faults. A limitation of this approach is that all geometry must define closed, solid volumes. Non-manifold
geometry, such as a fault plane that terminates within a volume or a well bore, which is a zero volume line,
cannot be represented. Faults add anisotropy to property distributions required by the numerical models.
Vertical, or nearly vertical, faults and nearly horizontal thrust zones can be defined by adding additional
surfaces to the existing stratigraphic models
2.4 Surface-based approaches

Geomodelling methods with Surface-based approacheshave the ability to compactly represent complex
shapes in 3-D. From a mathematical standpoint, two main types of surface representations,viz. Parametric
Surfaces and Polygonal Surfaces.
The classically used representation in Computer Aided Design allowing convenient user interaction is
parametric surfaces, which use polynomial or rational equations describing the surface geometry using
parametric coordinates. In these approaches, discontinuities are addressed using one parametric patch per
connected component (fault segment or continuous horizon inside a fault block). These surfaces need then to be
truncated along discontinuities for graphical display and structural model queries.
Polygonal surfaces consist of a network of nodes connected by polygons. Mathematically Triangular
surfaces have the properties of simplified meshes and conforms geological requirement without degeneracy to
all types of geometry and topology (densely faulted domains, complex intrusive or erosive contacts, etc.), and
can be adaptively refined where needed. Whatever the mathematical model retained, surfaces should honour
representational validity rules (finite extension, orientability, non-intersection and geological validity rules non-
intersection of rock boundaries, absence of dangling surface edges except for laterally dying and synsedimentary
faults.) [5].
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2.5 Volume-Based Approaches
Isolated surfaces are the 3-D counterpart of the spaghetti format in GIS; they do not necessarily bound
well-defined volumes. The simplest volume model is a Cartesian grid whose blocks are flagged depending on
the geological unit they belongs. Geological interfaces if stair-stepped increases model resolution helps in
improving model accuracy and increases the number of model parameters. Adaptive Cartesian grids such as
octrees may be used to more compactly represent structures by using local refinement in areas of high geometric
complexity. However, such Cartesian representations do not directly represent fault offset nor locally varying
anisotropy related to rock deformations.
Stratigraphic (corner-point) grids address both problems by conforming grid blocks to most structural
interfaces. Construction is often achieved by extrusion of a 2D grid vertically or along so-called pillars, which
define a direction field tangent to the main faults. Alternatively, grids may be warped to conform to structural
interfaces. These grids have become standard in the modelling of underground reservoirs. They approximate the
coordinate transform to apply geostatistical methods in depositional space, thereby accounting for depositional
heterogeneities. In addition, they offer a support to finite-volume based flow simulation. However, conforming
to geological structures generally yields non-orthogonal grids, which may introduce distortions in geostatistical
models and discretization errors in flow simulation. Moreover, from a practical standpoint, these grids are very
difficult to create in the presence of low-angle faults and sub horizontal fault contacts and hence only covers a
subset of the volume of study. These shortcomings make corner-point grids difficult to apply at basin scale and
to igneous and metamorphic formations.
Boundary representations, or sealed geological models, stitch surfaces together to define rock volumes.
The full structural complexity can therefore be captured by these models, which have been widely used in
geomodelling. Analytical properties may be defined within each region to support numerical integration with the
boundary element method. When a higher level of detail is needed, conformable meshes are generated within
each region. Among these, tetrahedral meshes are simple and can in principle adapt to complex boundary
geometries; as for triangulated surfaces, tetrahedral level of detail can be variable in space to honor data or
geological features. In spite of recent advances in mesh generation, accounting for complex constraints such as
sharp geological contacts, thin layers or fracture networks is difficult to represent.
One way to address these mesh generation problems is to use implicit surfaces or level sets to represent
geological structures. In this representation, some structural interfaces are equipotential surfaces of some 3-D
scalar field f(x,y,z). Several approaches have been described to build the 3-D scalar field f(x,y,z) from a set of
data points, using radial basis functions, dual kriging with polynomial drift, or discrete interpolation on
Cartesian grids or tetrahedral meshes. As compared to surface-based structural modelling, implicit methods are
preferred because they provide some built-in model consistency rules, and do not rely on data-to-surface
projections, which raise a number of problems in classical approaches [5].
The conventional 3-D volumetric data models include constructive solid geometry (CSG), 3-D-raster,
Octree, Tetrahedral Network (TEN), Tri-Prism (TP), Generalized Tri-Prism (GTP), Geocellular, etc. [23], [25].
3-D vector data models, which describe solid volumes in terms of their enclosing surfaces, emphasize on the
surface representation for the spatial objects. The conventional 3-D vector data models include Boundary
Representation (BRep); Wire Framework and Non-Uniform Rational B-splines (NURBS). 3-D mixed data
models use two or more vector/volumetric data models to describe one geo-object at the same time. The
conventional 3-D mixed data models include BRep-CSG (Constructive solid geometry), GTP-TEN and BRep-
GTP-TEN. 3-D integrated data models firstly apply various single data models to describe different types of
spatial objects respectively, and then integrated them into a unified 3-D space to fully represent multiple types
of spatial objects. The conventional 3-D integrated data models include CSG+ TIN (Triangulated Irregular Net)
+ GTP, BRep + TEN + GTP and object-oriented data model [31].
III. Applications Of 3-D Geologic Models

3.1 Geological understanding
One of the major application is geological understanding of the local geological structure, was not
possible using other commonly used methods. The modelling is Preference for highly variable subsurface
conditions at the project site [8], and the site characteristics with geologically complex area / faulted Ground /
not well-understood geology [1].3-D geological models can express, verify and modify conventional geological
cognition/judgment/knowledge. It explain and portray complex geology in understandable formats [2]. 3-D
lithologic, stratigraphic, and textural models can be constructed which resulted in several new interpretations
regarding the thickness, extent, and spatial 3-D distribution of the important geologic units in the Basins [7].
The area and volume of each defined geological body can be calculated and further analytical functions allow
integrating and visualizing hydro-geological, engineering properties and physical or other parameters for each
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mapped units. 3-D model of geometrical bodies can be produce representing different lithologies by a
geostatistical interpolation of the input data [15].
3-D geological modelling is being used for analysis of the subsurface geological characterization
involving both geometrical structure and various parametric properties [31]. The digital 3-D attributed model are
created by rigorous use of geological, geotechnical and geophysical data, geological knowledge and statistical
methods [2]. Attribution of physical parameters (density, magnetic susceptibility) to each representative
lithology of the model can be used for computation of the 3-D gravity or magnetic contributions of the model
[15]. Contoured or gridded surfaces of tops, bases, thicknesses and volumes of single or combined geological
units (including artificial ground) [6]. The 3-D Geological Modelling focuses on different types of visualization
and predictive 3-D mapping but also provides all types of virtual cross-sectioning and predictive calculations of
hydro-stratigraphical units and apparent validity inspections [17].
The 3-D spatial geological model can be interrogated using simple tools available in the software to
produce,
 Horizontal slice maps at any depth and vertical cross-sections in any orientation [6].
 Synthetic logs and cross-sections at user-defined locations; /Contoured surfaces; Isopachytes of
single or combined units; / Domain maps- Sub- and supracrop maps [6].
 A fully attributed Generalized Vertical Section (GVS). This forms the basis for engineering
geological, hydrogeological and mineral potential classifications [6].
 Virtual sections can be calculated in highly variable positions and can be combined with subsurface
and surface topographic information. The processing of such horizontal and vertical virtual sections
gives a very precise positioning of distinct units or structures within the spatial model, especially of
geotechnical and remediation applications. Thus it is also possible to analyse the subsurface, by
creating geological maps, thematic maps, user defined cross-sections, horizontal slices in any
elevation and synthetic drill holes [17].
Advantages of detailed, coherent ground model are, better knowledge of the ground conditions, more
control, better the assessment of risks for construction, safety, constrain design and the final costs [1]. The
integration of geoscientific data within a single 3-D model, and the ability to display and query these data, are
significant advances for project decision [9]. The interpreted geological data pool can be used to develop
management strategies for a wide range of sustainable ground-related issues. A detailed geo-scientific
knowledge of the subsurface is essential for sustainable urban management and strategic planning, in terms of
revitalization of contaminated sites, groundwater protection, and assessment of engineering conditions, mining
resources, and the preservation of archaeological sites. The high-resolution 3-D models can be used for
predictive application in the field of hydraulic modelling, environmental and geotechnical investigations. Digital
3-D subsurface models provide decision support tools for, planners and strategic decision makers. Visualization
and analysis of the subsurface, by the expert geologist, - in order to deliver an easy-to-understand decision
support system for policy and decision makers involved in sustainable regional planning [17].
The models can be kept in a dynamic form; such that each newly gathered piece of geo-scientific
information, e.g. new drillings, can be added to the existing structure-model basic data set and the model can be
modified according to this new information [17]. The models benefit from continuous validation and upgrading
of the underlying database, as well as the production of regional syntheses, integrating geological, geophysical,
and geochemical models in a single platform. It is helpful to catalyze the development of knowledge by easily
integrating data under a common format; and preserving the data in a unique archiving platform where it can
easily be shared, seen, and analyzed [9]. Various interpretive maps can be easily produced and updated with
availability of new information and can be customized for specific needs [2].
3.2 Diverse Fields of application.

1. The multidisciplinary approach used in 3-D integrated geological modelling demonstrates its
usefulness as a regional interactive exploration tool, allowing the use of various criteria to constrain
and refine queries. [9]. The 3-D model can be used to quickly generate synthetic lines of section or
synthetic borehole logs, to predict ground conditions at a particular point or on an alternative route
alignment. It has also identified gaps in the dataset, assisting in the planning of continuing ground
investigation [1].
2. Integrated investigation strategies of contaminated sites [17]. Identification, assessment, and
remediation of large-scale groundwater contamination require a detailed knowledge of the
heterogeneous geological structure to predict the fate and pathways of contaminants and their
potential interaction with, e.g., surface water [30].
3. Management of groundwater resources, monitoring of water quality and all related environmental
issues Assessment of location, thickness and capacity of aquifers and aquitards [17]. The conceptual
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method consist of GIS-based „„Spatial 3-D-Model‟‟ with emphasis on 3-D geological modelling and
prediction of groundwater flow and transport for an integrated environmental risk assessment [30].
4. The geologic factors affecting conductivity and storage properties of the aquifer system for
characterization of groundwater flow can be assessed. A 3-D portrayal of sediment texture (3-D
Subsurface Mapping of Textural Classes) developed from the 3-D lithology model can help to
characterize grain-size variations of the aquifer system [7].
5. The development of regional hydrogeological frameworks to serve as the basis for understanding
groundwater, geological hazards, and natural resources [11].
6. The main sectors using 3-D geological models include Water, Wastewater, Waste Disposal,
Contamination and Management, Hydrocarbon, and Carbon Capture and Storage, Land-Use Planning
and Local Decision Making, Civil Engineering and Infrastructure, Archaeology, Mineral Resources
(exploration), Research and Education and Outreach [2].
3.3 Specific Engineering Applications

The geological understanding developed through specifically built 3-D model can be utilized for
engineering application e.g.
1. The ground characterization for tunneling in soft soils: The engineering requirements was to
determine the volumes of each soil type to be encountered and its geotechnical properties, water
pressures and surface settlements determination. The requirement were satisfied with the 3-D
modelling functions with extensive use of external associated routines. 3-D geotechnical models can
be used for numerical calculations to verify the engineering feasibility with regard to overall stability
of tunnel sections, landslide prone slope etc. [18].
2. Analysis of geomechanical TBM performance modelling and quantitative volumetric analysis of
geologic units [8].
3. The selection of cost effective and safe foundation type was determined by the regional estimation of
soil settlement, aided by geometrical modelling, visualization and geostatistical analysis [18].
4. The subsurface conditions and the ground- structure interaction information was acquired for
foundation decision-making. The geological information (depth, extent, thickness of layers),
geotechnical information (soil/rock engineering properties, unit weight, cone resistance), and
information regarding the behaviour of the ground when subject to a change in equilibrium was
modelled for foundation decision. The 3-D geological and geotechnical models provide the ground
parameters to the soil mechanics models [18].
5. Preparation of Maps for tunnels or pipelines along the proposed design route [6].
6. Seismic risk Evaluation ,Engineering projects, Assessment of CO 2 storage capacity Assessment of
geothermal potential (BRGM French geological survey)
IV. Modelling Approach

A wide range of software can be used for 3-D geological modelling. The methods and related software
are based either on use of sophisticated statistical methods; or on traditional geological understanding [2]. For 3-
D geological modelling, choose software and methods that allow significant geological control on the
distribution and character of the substratum being depicted. Constrains should be applied for the basic unit
distributions and the characteristics of the modeled properties [2]. Different 3-D modelling approaches are,
geostatistically and constructive cross-section based interpolations (TIN - Triangulated Irregular Net
Interpretation) [30].
4.1 Modelling approaches based on Geostatistical algorithms;

The methods for developing the property models typically involve geostatistical tools. Statistical
methods of interpolation reflects additional information on spatial variation, but alone do not depict the
complete spatial structure of specific depositional environments or geological knowledge, and so the value of
this information is limited [2]. There are several software packages incorporating geostatistical interpolation
techniques, e.g. 3-D GIS, EVS/MVS, Earth Vision and RockWorks, MOSYS modelling system, GeoModeller,
Gocad, Multilayer-GDM ( Geoscientific data model)BRGM, Isatis etc.
4.2 Modelling approaches based on Constructive cross-section (the TIN - triangulated irregular net
interpretation)
The geometrical modelling of the ground in Cognitive modelling methodology GSI3-D is based on
cross-sections derived from the geological map, boreholes. The software utilizes a digital elevation model,
surface geological line-work and downhole borehole data to construct cross sections by correlating boreholes
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and the outcrops to produce a geological fence diagram. The software takes into account all structural geology
features such as dip, dip directions, strike, hinge lines, axial trace, and geologic faults to build the geometry of
geological units [28].
V. Modelling Data
Data requirement for modelling is based on specific modelling objectives and application. Several
different modelling methodologies have been developed depending on the type of data available. These
methodologies, accounts for the variety of available data models and their integration in a 3-D geological model
(Multi-Source Data Integration). To enhance the practical utility and the effectiveness of 3-D geological models,
along with the stratum lithology, components, and grade information of geological bodies, the expression of
attribute-oriented information and semantic information in 3-D geological modelling can be used [27].
5.1 Geological Data

Geological data obtain from site investigation consist of,
 Punctual data like Well data (water wells, geoscientific and academic wells, and oil and gas wells),
/Borehole data. The Borehole data consist of stratum lithology/stratigraphy data, stratigraphic
contacts.
 Details of structural geology features such as interfaces and orientation data (dip, dip directions,
strike, hinge lines, axial trace, and geologic faults). Surface traces of faults.
 2D cross-sections geological map (digital geological cross sections), historical maps, and
archaeological subsurface data, digital thematic maps topographical, geological, hydro-geological
maps, structural geology maps, digital terrain data, DTM of appropriate resolution [17].
 3-D surfaces of formation bases, Isopachyte maps for formation [1].
 Line data such as rivers and creeks, and polygon data and outcrop data [30].
5.2 Geophysical Data

The 3-D geological models can be developed with an internal geometrical consistency, compatible with
available geophysical data (magnetic, seismic, gravity etc.), and integrating the geological knowledge [15]. The
modelling combines geological knowledge (surface geology) and geophysical surveys measurements (gravity
data- ground-based and airborne gravity coverage, and a deep seismic reflection profile density, magnetic
susceptibility) to model the 3-D geometry.The 3-D geophysical data such as resistivity, seismic, gravity or
magnetic, GPR (Ground Penetrating Radar) etc., obtained from geophysical investigations and the conventional
geological data along with the structural cross sections and the structural maps can be integrated together to
develop 3-D model of the structure.
5.3 Physical Parameters

The geotechnical database for lithology characterization with parameters such as, unit weight, porosity,
water content, friction angle, cohesion, permeability coefficient, and friction ratio i.e. attribute information of
can be modelled over the geological bodies. In situ and laboratory test results such as Cone Penetration Tests
(CPTs), vane tests, dilatometer, & pressiometer tests, Physical & chemical property parameter, hydrochemistry
(contaminants) monitoring data can also be used for property modelling.
VI. Data Management

Integrating, homogenizing, visualizing, analyzing and storing all these differing data sets in one
database management system, ready-to-use for the end-user groups, enables the cost and time for planning
individual campaigns to be reduced. [17]. Digital geospatial databases allow many different types of geological
data to be stored together, so that the user has a visual interface to all of the data collected for an area. Digital
database offers considerably improved data retrieval, database searching, archiving and remote accessibility
compared with conventional paper-based methods. This digital database will be input for modelling. The large
amount of geological and geotechnical data expected from investigation works required an organized structure
for data management, -evaluation, -analysis and –visualization to support decision making processes.
Because most geoscientific data are spatial in nature (i.e. specific to a given location) GIS are now
widely used. GIS has evolved as a computer cartographic system, which is defined as „an information
management system for organizing, visualizing and analyzing spatially orientated data. The, data collected from
these investigation works can be compiled in a Geographic Information System (GIS) providing a geo-
referenced database. In its original guise, GIS largely dealt with 2D data that were mapped onto the Earth‟s
surface. However, it was recognized that to deal with volumetric spatial information or 3-D geometries from
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subsurface data, a 3-D GIS or a GSIS (Geoscientific Information System) was required. Majority of software
are with RDBMS software interface where data can be better managed with ease.
VII. Data Pre-processing

The quality of the model is affected by the quality & density of the data. Different data preprocessing
means are applied ensure data quality used for modelling. Data pre-processing includes collecting, structuring
and reinterpreting data in order to build a consistent dataset [12]. The reliable, usable and validated data are
selected for the 3-D geological model reconstruction [12]. The interpreted and validated interpretative data and
observational data has to be used for modelling. Interpretation can be compared with that of its nearest
neighbours, as a check on the consistency of the interpretation [21]. The validity of borehole records and their
interpretations can be assessed objectively, imparting greater confidence of reliable and representative borehole
data. In addition, the methods are adopted for providing a means of objective identification of data that should
be excluded [1].
Each borehole records can be examined in the 3-D context of surrounding data and interpretations [1].
The deepest of multiple, closely spaced and equally reliable boreholes can be selected for coding. Borehole
selection should be independent of any pre-conceived geological model but quality and reliability criteria may
be applied [6], also even distribution of good-quality borehole data should be ensure [10].
Initial Data Consistency Analysis is needed to be carried out. Data Pre-processing ensures that all data
are considered in their correct position in 3-D space. All the data is check for its true coordinates, accurate
geological description, good georeferencing, etc. Data is check for the data accuracy during the compilation of
the databases, and statistical methods are use (e.g., histograms, scattergrams, and variance and covariance
values) to discriminate the abnormal data before beginning the actual 3-D geomodelling process [4].
The mesh of consistent cross-sections should be used. It should validate the genetic aspects of
landscape evolution envisaged by the geologist [17]. The geological data, representing lithological and
stratigraphical characteristics and geological structures, should be validated by reference to genetical and
morphological rules and perceptions [17].
Some tailor-made tools can be been written to manipulate, control and validate the data through an
adapted interface including a visual comparison of logs of neighbouring data [12]. To utilize the geological data
of different types and qualities and to maintain the data consistency, data Integration architecture can also be
design [29].
Few software itself ensure data and geology consistency during modelling procedure e.g. 3-D
GeoModeller (BRGM-Intrepid Geophysics) is use to,
i. Ensures that the model consistency with known geological relationships of the area in 3-D [11].
ii. To input of derivative geophysical data and geological concepts as guides to the geological modelling
[11].
iii. Provides geophysical forward and inverse modelling to check for geophysical validity [11].
VIII. Modelling Approach

8.1 Geostatistical algorithm based Modelling
The distinctive lithologic classes can be used to construct a 3-D model of lithologic variations within
the basin by extrapolating data away from drill holes using a suitable algorithm e.g. nearest-neighbor approach
(3-dimensional gridding process). Interpreted drill-hole lithologic data can be numerically interpolated between
drill holes by using a cell-based, 3-D gridding process (such as the RockWorks 3-D modelling software package
- Rockware Earth Science and GIS software: www.rockware.com). A solid modelling algorithm can be used to
extrapolate numeric codes that represent a lithologic class [7]. A strength of the 3-D gridding process is that the
interpolated data in the resulting 3-D grid have the appearance of stratigraphic units, with aspect ratios that
emphasize the horizontal dimension over the vertical. In addition, the method preserves the local variability of
the lithology in each drill hole with no smoothing or averaging. Thus, where data are abundant, local lithologic
variability is incorporated [7].
The single-stepped numerical modelling methodology requires a high concentration of boreholes,
which are evenly distributed for each surface to be modelled [21]. The limitation of the type of numerical
interpolation is the sensitivity to the distribution of the data, where values from an isolated drill hole tend to
extrapolate outward to fill an inordinate amount of the model area. The effect is particularly noticeable where a
small number of deep drill holes are interspersed with shallower holes. Data from the deepest drill holes in this
case tend to over extrapolate over the entire model area. [7]. The uneven and spotty distribution of geological
drilling information is one of the major obstacles in regional modelling with automatically contoured
distribution and thickness [30]. The geostatistical-based interpolation of geo logical layers requires sufficient
statistical borehole coverage [30]. With depreciating amounts of borehole data intersecting each succeeding
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lower layer the results achieved with a single-stepped numerical workflow become increasingly inadequate [21].
Another limitation of this method is that it is purely deterministic and data based. Alternatively, it may be
possible to use a stochastic approach where the drill-hole data are used as a guide to predict subsurface
lithologic variability. Such an approach would have the benefit of being able to incorporate depositional process
Factual data from Geological, Geotechnical

and Geophysical Investigations
Data Validation & Organization
Data Evaluation and Interpretation.
Geostatistical Interpolation.
3D Spatial Model
(Visualization of interpretative,
Inter and extrapolated data.)
Query analysis and

Spatial Analysis.
Reliability Estimation
Data Extraction for Application
Fig.1. Conceptual Work Flow -Geostatistical Method

and facies relationships by evaluating the tendency of specific lithologic units to be adjacent to each other in
specific geologic environments. For the large-scale nature of the study area, the presence of multiple
depositional environments, and resource limitations, stochastic modelling approaches can be not applied. Faults
cannot be explicitly included in the creation of the 3-D lithologic model, owing to the limitations of the
geostatistical software package. However, the interpolation methods used produce lithologic variations can
approximate fault truncations of lithologic units where data density is high [7].
Statistical methods of interpolation reflects additional information on spatial variation, but alone do not
depict the complete spatial structure of specific depositional environments or geological knowledge, and so the
value of this information is limited [2]. Interpolation between widely spaced filed observations requires
geological knowledge to successfully replicate actual geological environments [23]. In combined use of
cognitive and geostatistical interpolation method, the reference boundaries of lithostratigraphic units, obtained
from the geological maps, locally modified from the boreholes data can be used to constrain the interpolated
surfaces, and to limit the interpolations to the zones of different units [22]. Thus improving the quality of
modelling.
8.2 Constructive cross-section based (knowledge-driven)

Modelling methodology such as GSI3-D allows the modelling of the distribution and geometry of
sedimentary layers, stratigraphical situation as well as the geological history by knowledge-based control of the
modeller, which is highly needed for heterogeneous aquifer systems [30]. No prior assumptions need be made
about the local geological structure.
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Digital Geological Maps
Correlated Digital
Geological Cross-sections
Fence Diagrams
Unit Distribution
Block Model
Extracted Thickness Grid, Synthetic

Boreholes, Sections, Exploded Model
Fig.2. GSI3-D Workflow
The modeler controls the detailed configuration of each modelled surface, not by modelling algorithms
within the software [1]. A cognitive interpretative approach can be used to create traditional geological maps to
incorporate possible geological features for areas with the sparse or uncertain data.The software provides the
modeller with the ability to connect areas in the model, where there is either only partial data coverage or where
the geometry of the geological units is poorly understood [21]. The method can reproduce surfaces (faults and
stratigraphic horizons) that not only honoured the data but also were also geologically reasonable even in areas
where the data was sparse or uncertain [21]. The constructive and “knowledge-driven‟‟ 3-D modelling allows
the prediction of vertical and horizontal sections, visualization purposes, volumetric calculations of distinct
sedimentary units.
The lithostratigraphic classification of the sedimentary succession within a consistent regional
stratigraphic framework is more helpful than a pure grain-size or lithology-based approach. The
lithostratigraphic approach in construction of 3-D geological models gives better results than only a pure grain-
size or lithological-based automatically contoured approach. This statement is valid for most Quaternary
sediments and artificial cut-and fill structures [30].It must be stated very clearly that the mentioned restriction
depends on the specific geological situation. The advantages of geostatistically based modelling are high if the
coverage of borehole data is sufficient. The insufficient density of borehole data is a function of the complexity
of the subsurface. Therefore, the application of 3-D subsurface models, on local or regional scale, has to be
completed by knowledge-based control, as much as possible [30].
The subsurface data available is normally very limited. Some basic geological, limited number of boreholes or
probing data, rarely supplemented by geophysical data, is generally available for the modelling of the subsurface
in civil engineering projects. To create a model of the subsurface from this limited amount of data requires the
availability of expert knowledge. However the correctness of the model whether on paper or in a program
cannot be assessed, because of the limited amount of data available and the heavy influence of expert
knowledge/judgement on the final model. The statistical analysis of the relative uncertainty with GSI3D cannot
be done inside the software package. Due to the plausibility-checked cross-section network, as well as additional
information from 2D mapping and expert-driven interactive remodelling, the statistically based uncertainty of
information is therefore difficult to estimate [30].
8.3 Combine Approach

The modelling methodology combining cognitive and numerical modelling can be developed to avail
the advantages of both systems and to overcome the problem of having an uneven distribution of
borehole/subsurface data. [21].Geostatistical Interpolation is applied within constrain defined by the geological
boundaries identified with cognitive geological understanding.
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Geological Data
Bore holes, Cross sections, Geological & Terrain Maps, Geophysical etc.
Geological Mapping
Stratigraphy & Fault Network
Data Driven Model Knowledge-Driven

Geostatical Interpolation Model respecting Geological
Geological Rules
Techniques understanding
3-D Modelling Revision

and synthesis Based on validation
Fig.3. Combine Modelling Approach
IX. Validation of model

The density of drill-hole lithologic data is greatest at the surface, so resolution of the resultant model
will be highest. When the solid lithologic model is trimmed with a DEM/ surface grid, the resulting upper model
surface should compares to the geologic map. An initial test of the strength of the subsurface 3-D lithologic
model is to compare the mapped surface geology to that predicted at land surface by the 3-D model [7]. The
model simulated results should also be compared to the „„real-world scenario‟‟ of the 3-D spatial model of the
investigated site [30]. E.g., the evidence for validation of the modelling methodology for 3D modelling carried
for the structure of the Chalk in the London Basin has come from chalk-cored boreholes from the Thames
Waters Lee Tunnel and Thames Waters Ring Main extension, where site investigations suggest the presence of a
major north south offset which has again been predicted by the model. In addition, a new hydrogeological model
for London has found that in using the new fault model the resulting groundwater level pattern fits better [21].
An interactive comparison between modelled and measured potential fields provides a best-fit
adjustment of the model geometry compatible with the different input data sets [15]. When discrepancies
between computed and observed gravity fields are identified, the geology is locally reinterpreted. The model
being interactively adjusted in 3-D. E.g. the 3-D gravity or magnetic contribution of the model can thus be
calculated and compared to the measured potential fields for further interactive adjustment of the model
geometry, to improve the accuracy of the geological model [15]. The result is a 3-D model that respects
constraints imposed by geological and geophysical data and can be further use to interpret and discuss crustal
scale structures [15].
X. Limitations of Modelling
Euro Conference in Spa, Belgium in [20], identified important impediments, at that time, to greater use
of 3-D geological models:
 a lack of 3-D/4D mathematical, cognitive and statistical spatial tools;
 a lack of cheap modelling tools designed for the shallow subsurface that can be operated without
specialist personnel
 the inability of models to depict natural variability of geological systems;
Very localized geological phenomena such as small scour hollows, relict pingo and allied periglacial
structures and small channel infills cannot be easily shown at the intended resolution of the model unless a
borehole proving the structure is included in a cross-section [16].
XI. Modelling Software.

The most common software packages used for building 3-D geologic maps and models in many
geological survey organizations (GSOs) include, ArcGIS, Gocad, EarthVision, 3-D GeoModeller, GSI3-D,
Multilayer-GDM, and Isatis. Many other software packages are also used in GSOs worldwide as part of
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modelling workflows, and these include software for GIS, geostatistical analysis, visualization, and property
modelling [13]
The choice of 3-D modelling software and methodology used depends on many parameters such as
required depth of the models, type of geological setting, geological context and degree of complexity of the
geological objects. (e.g., karst, fault networks, dolerite intrusions, buried channels); need to mesh models for
simulation; method to populate the models and the kind of properties needed for population; requirement for
quantification of uncertainty [4]. Different 3-D modelling software packages are used to address different
geological conditions and to satisfy other requirements such as quality and complexity of the initial data set and
the final purpose of the model [4]. Approaches to geological modelling are different to suit the needs of
individual GSOs (partly as a reflection of their customer base), which will likely remain the case in the
foreseeable future. Convergence or streamlining of software use might occur over time, but it is impossible at
present to envisage a standard piece of software, as this will intrude into individual organizational policies and
culture, as well as the possible capabilities of clients [3]. Over time, common data formats and relevant
standards should emerge, leading to increased interoperability and exchange [3].
11.1 Interface with other software

For pre-processing spatial data, calculating grids, or triangulating unevenly distributed data, (1) GIS
tools (mainly ESRI products), (2) CAD programs such as MicroStation, or (3) interpolation software such as
Surfer are applied.The geological structure in a GIS database is used to obtain an interface to numerical
groundwater modelling tools such as Feflow or Modflow. These data are stored in GRID or point formats in
ArcView. The GIS data management for all hydrogeological and hydrochemical data can be done with ArcView
(ESRI). The geological cross-sections with their vertical 2D structure were held in a special tool for geological
3-D models. [30].The model can be used to generate synthetic cross-sections or borehole prognoses; or to
generate files appropriate to displaying the component geological surfaces or shapes commonly used computer-
assisted design (CAD) or geographic information system (GIS) software packages [14],[1].
The software being used have, common data formats interoperability and exchange capabilities. The
specific engineering application and the multiple data with diverse quality and quantity may force to adopt
combine use and integration of various software. This requirement may also lead to the new methodology, and
new approach to data integration. The selected case studies from the various fields highlights the same.
Following are the commonly use 3-D geological modelling software and their modelling functionalities [13].
Table. 1. Software for 3D Geological Modelling
No Software Application
1. 3-D GeoModeller  3-D GeoModeller is “Geological editor” alternative to CAD or GIS, for
(Intrepid- French helping to define complex 3-D geology.
Geological Survey -  Implicit modeling; geological thinking; accurate prediction of complex
BRGM) geological structure
 3-D GeoModeller allowed simultaneous data integration, synthesis, and
geological interpretation of geophysical data in conjunction with 3-D
geological mapping.
 3-D Geomodeller is based on an implicit modelling of surfaces where, each
horizon is built by a 3-D interpolation function (potential field cokriging)
that simultaneously account, for
 Data points on horizon locations (Iso-potential values),
- General orientations and polarities of structures (gradients), and
existence of discontinuities (faults).
- Full Tensor Inversion Gravity and Magnetic Modelling software to
combine geological modelling and validation through geophysical
inversion.
- Geostatistics based model building with inherent the
uncertaintymeasures in the model-building approach.
2. ArcGIS  Multi-source geological databases the effective organization and
(ESRI) management of data.
 To create additional input data for the modelling, including fault patterns,
maps showing the extent of lithostratigraphic units, and other geological
features
 Analysis and interpolation of geological characteristics,
 Assembling and visualizing 2-D maps and, for developing and visualizing
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3-D geological models (ArcScene).
 Customized tools for 3-D geological modelling to create cross sections,
make stratigraphic picks on 3-D boreholes, and generate surface maps of
the tops or bottoms of map units.
 3-D GIS provide the tools for enabling interactive construction of
volumetric models of the ground profile. These permit analysis and
interpolation of geological characteristics, facilitating appraisal of the
engineering problem.
 With the aid of the powerful capability of data visualization, manipulation,
sharing and editing.
3. Earth Vision  High end 3-D geological modelling and visualization application
(Dynamic Graphics)  Data: 3-D passage points from boreholes, geological map, digitized cross
sections, seismic data
 Complex 3-D geometry and fault network representation
 Spline type interpolation for layer-cake geometry, or 3-D function for 3-D
objects
 Modelling for oil and gas resources, mining applications, and surficial and
near-surface geological mapping and modelling projects
4. Gocad (Geological  Gocad is a CAD system, with interpolation and surface fitting algorithms.
Object Computer  Use for visualization of 3-D models and inspection of 2-D surfaces.
Aided Design)  incorporation of many data formats, integration of many workflows for
(Paradigm reservoir engineering and advanced geological interpretation
Geophysical.)
5. GSI3-D  GSI3-D is a methodology and associated software tool for 3-D geological
(Geological modelling based on working practices of geologists- Cognitive modelling
SurveyingAnd methodology/ Constructive method/knowledge-driven approach
Investigation  GSI3-D is programmed to be part of a systematic, iterative, and
In three dimensions) interpretative geological mapping process.
(Hans-Georg Sobisch,  Cross-section net- based interpolation
British Geological  The functionality to model more complex bedrock environments.
Survey)
6. Multilayer-GDM  Suited for data control and for layered models with vertical faults with
BRGM geostatistics application.
(Geoscientific Data  The Multilayer-GDM software utilizes BRGM‟s borehole and geological
Model- French map data sets including fault traces, outcrop information, existing cross
Geological Survey sections and outcrop-subcrop distributions, and a DEM.
(Bureau de Recherches  The software performs consistency checks between these varied sources.
Géologiques et  The model is controlled by a stratigraphic sequence with rules concerning
Minières): the nature of bounding surfaces (e.g., erosional, on lap).
7. Isatis  Advanced spatial and geostatistical analysis package that can be used for
(Geovariance) sophisticated spatial data analysis, geostatistical modelling and simulation,
statistically based assessments of uncertainty, and 3-D
visualization.Interfaces with standard 3-D geomodeling software
 Statistical data analysis, semi-variograms, and interpolation facilities
 2D-3-D Simulation (facies simulation, pixel-based methods or object-based
methods)
8. Rockworks  The geostatistical modelling packages, it interpolates surface and solid
(RockWare) models, computes reserve and overburden volumes, and can display maps,
logs, cross sections, fence diagrams, solid models, reports, and animations.
 Supports wide range of 2-D and 3-D geological mapping and modelling
techniques for visualizing, interpreting, and portraying surficial and
subsurface information.
9. SKUA  Mapping in structurally complex geological settings where modelers can
(Paradigm Geophysics) create grids consistent with true stratigraphy and structure while honoring
data and geological rules.
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10. Surfer  The interpolation and visualization of 2-D surface models. Surfer has the
(Golden Software) capability to simultaneously view stacked sets of independent surfaces in 3-
D space.
 True stratigraphy and structure honoring data and geological rules.
11. Lynx  Using Lynx, data is stored in a 3-D database projected to user-selected
(Geoscience planes to delineate polygonal boundaries of each geological unit.
ModellingSystem)  These are connected by links to form solid volumes by interactive volume
modelling
12. EVS/ MVS  Geostatistics (Geostatistical Algorithm) based
Environmental/Mining
Visualization
System
(C Tech. Development
Corp.Kaneohe, HI)
13. Geophysical Data  Geostatistical Interpolation software to analyze geophysical data.
Analysis Software  Examples Oasis montaj, GM-SYS (Geosoft), IPI2win, Geotools MT (AOA
Geophysics, Inc.), and methods and software developed by the USGS etc.
XII. Conclusion
In spite of the limitations with 3-D modelling can prove to be the valuable tool for better geological
understanding and related project decisions. Convergence of different modelling software capabilities, better
data integration along with use of advance geostatistical techniques blended with cognitive knowledge are
required to overcome these limitation. It has potential research element to modify the modelling approach. The
knowledge gain through various case studies and associated research will definitely add to the 3-D geological
modelling experience.
References
[1]. Aldiss D. T., Black M. G. et al. 2011. Benefits of a 3D geological model for major tunnelling works: an
example from Farringdon, east–central London, UK ASIA GEOSPATIAL FORUM 2011.
[2]. Berg R. C., Mathers Stephen J., Kessler Holger, et al. 2011 Synopsis of Current Three dimensional
Geological Mapping and Modelling in Geological Survey Organizations.
[3]. Berg Richard C., Mathers Stephen J., Kessler Holger, et al. 2011, Conclusions and Recommendations
Synopsis of Current Three dimensional Geological Mapping and Modelling in Geological Survey
Organizations.
[4]. Castagnac Claire, Truffert Catherine, Bourgine Bernard, et al. 2011.French Geological Survey (Bureau
de Recherches Géologiques et Minières): Multiple Software Packages for Addressing Geological
Complexities Synopsis of Current Three dimensional Geological Mapping and Modelling in
Geological Survey Organizations.
[5]. Caumon Guillaume, 2010. Towards stochastic time varying geological modelling 2010 Mathematical
Geosciences 42(5):555569.
[6]. Culshaw M.G. 2005. From concept towards reality: developing the attributed 3D geological model of
the shallow subsurface(Quarterly Journal of Engineering Geology and Hydrogeology, 38, 231–284
1470-9236/05 $15.00 2005 Geological Society of London).
[7]. Donald S. Sweetkind, Emily M. Taylor et al. 2010. Three-dimensional geologic modelling of the Santa
Rosa Plain, California (Geosphere; June 2010; v. 6; no. 3; p. 237–274).
[8]. Elkadi A.S., Huisman M. 2002. 3D-GSIS geotechnical modelling of tunnel intersection in soft ground:
the Second Heinenoord Tunnel, Netherlands.
[9]. Fallara F., Legault M. and Rabeau O. 2006. 3-D Integrated Geological Modelling in the Abitibi
Subprovince (Québec, Canada): Techniques and Applications Exploration and Mining Geology;
January 2006; v. 15; no. 1-2; p. 27-43.
[10]. Greg Keller, Gaywood Matile, Harvey Thorleifson. 2011. Manitoba Geological Survey: Multi-scaled
3-D Geological Modelling with a Single Software Solution and Low Costs, Synopsis of Current Three
dimensional Geological Mapping and Modelling in Geological Survey Organizations.
[11]. Jacobsen Linda J., Glynn Pierre D., Phelps Geoff A., et al., 2011. U.S. Geological Survey: A Synopsis
of Three-dimensional Modelling, Synopsis of Current Three dimensional Geological Mapping and
Modelling in Geological Survey Organizations.
ISSN: 2455-4847
[12]. Kaufmann Olivier, Martin Thierry, 2008. Reprint of „„3D geological modelling from boreholes, cross-
sections and geological maps, application over former natural gas storages in coal mines‟‟ [Comput.
Geosci. 34 (2008) 278–290].
[13]. Kessler Holger, Mathers Stephen J., Keefer Donald A., et al., 2011. Common 3-D Mapping and
Modelling Software Packages, Synopsis of Current Three dimensional Geological Mapping and
Modelling in Geological Survey Organizations.
[14]. Kessler, H., Mathers, S. & Sobisch, H.-G. 2009. The capture and dissemination of integrated 3D
geospatial knowledge at the British Geological Survey using GSI3D software and methodology.
Computers and Geosciences, 35, 1311–1321.
[15]. Marteleta G., Calcagno P., Gumiauxb C., C. Trufferta. et al., 2004. Integrated 3D geophysical and
geological modelling of the Hercynian Suture Zone in the Champ toceaux area (south Brittany, France)
Tectonophysics 382 (2004).
[16]. Mathers S.J., Burke H.F., Terrington R.L., et al., 2014. A geological model of London and the Thames
Valley, southeast England. Proceedings of the Geologists‟ Association 125 (2014) 373–382.
[17]. Neber A., Aubel J., Classon F., et al. 2006.From the Devonian to the present: Landscape and
technogenic relief evolution in an urban environment IAEG2006 Paper number 517.
[18]. Ozmutlu enol, Hack Robert, 2003. 3D modelling system for ground engineering Springer-Verlag
Berlin Heidelberg 2003.
[19]. Parry S., Baynes F. J., Culshaw M. G., et al. 2014. Engineering Geological Models – an introduction:
IAEG Commission 25.
[20]. Rosenbaum & Turner 2003. EuroConference in Spa, Belgium.
[21]. Royse Katherine R. 2010. Combining numerical and cognitive 3D modelling approaches in order to
determine the structure of the Chalk in the London Basin (Computers & Geosciences 36 (2010) 500–
511).
[22]. Thierry Pierre, Marie Anne, Leparmentier Prunier et al. 2009. 3D geological modelling at urban scale
and mapping of ground movementsusceptibility from gypsum dissolution: the Paris example (France)
Engineering Geology 105 (2009) 51 –64.
[23]. Turner, 2006. Challenges and Trends for Geological Modelling and Visualization, Bulletin of
Engineering Geology and the Environment, Volume 65, Number 2, May 2006, pp. 109-127.
[24]. Turner, A. K. Gable, C. (2007)."A review of geological modelling” In: Three-dimensional geologic
mapping for groundwater applications, Workshop extended abstracts,” Denver, Colorado
(PDF).http://www.isgs.uiuc.edu/research/3DWorkshop/2007/pdffiles/turner.pdf .
[25]. Turner, A.K., [Editor] 1991. Three-dimensional Modelling with Geoscientific Information Systems.
NATO ASI Series C: Mathematical and Physical Sciences, v. 354, Kluwer Academic Publishers,
Dordrecht, the Netherlands, 443p.
[26]. Turner, & Dearman, W. R. 1980. The early history of geological models. Bulletin of the International
Association of Engineering Geology, 21, 202-210.
[27]. Wang Yongzhi, Zhao Hui, Sheng Yehua et al. 2015. Construction and Application of 3D Geological
Models for Attribute-oriented Information Expression Journal of Applied Science and Engineering,
Vol. 18, No. 4, pp. 315322 (2015).
[28]. Williams, J., Scheib, A. 2008. Application of near-surface geophysical data in GSI3D: case studies
from Shelford and Talla Linnfoots. British Geological Survey Open File Report (OR/08/068), 29pp.
http://nora.nerc.ac.uk/5347/1/OR_08_068.pdf.
[29]. Wu Qiang, Xu Hua, Zou Xukai. 2005. An effective method for 3D geological modelling with multi-
source data integration Computers & Geosciences 31 (2005) 35 – 43.
[30]. Wycisk P., Hubert T., Gossel W., Neumann Ch. 2009. High-resolution 3D spatial modelling of
complex geological structures for an environmental risk assessment of abundant mining and industrial
mega sites (Computers & Geosciences 35 (2009) 165 – 182).
[31]. Zhu Liang-feng, Li Ming-jiang, Li Chang-ling, et al. 2013. Coupled modelling between geological
structure fields and property parameter fields in 3D engineering geological space Engineering Geology
167 (2013) 105–116.

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International Journal of Latest Engineering and Management Research (IJLEMR)

An Overview 3-D Geological Modelling Part I- Basics of 3-D

I. Introduction to Geologic Models

II. Geological Modelling Process

2.1 Stratigraphic Models

2.3 Non-stratigraphic models

2.4 Surface-based approaches

III. Applications Of 3-D Geologic Models

3.2 Diverse Fields of application.

3.3 Specific Engineering Applications

IV. Modelling Approach

4.1 Modelling approaches based on Geostatistical algorithms;

5.1 Geological Data

5.2 Geophysical Data

5.3 Physical Parameters

VI. Data Management

VII. Data Pre-processing

VIII. Modelling Approach

Factual data from Geological, Geotechnical

Data Validation & Organization

Data Evaluation and Interpretation.

Query analysis and

Data Extraction for Application

Fig.1. Conceptual Work Flow -Geostatistical Method

8.2 Constructive cross-section based (knowledge-driven)

Extracted Thickness Grid, Synthetic

Fig.2. GSI3-D Workflow

8.3 Combine Approach

Data Driven Model Knowledge-Driven

3-D Modelling Revision

Fig.3. Combine Modelling Approach

IX. Validation of model

XI. Modelling Software.

11.1 Interface with other software

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