At the end of the module, student should be able to:
• Explain the range of applications for which 3D subsurface models are required and the specific model properties needed in each.
• Describe technically the steps typically used to construct various types of 3D subsurface geological models in the geo-energy and minerals industries.
• Critically evaluate approaches for 3D subsurface model creation on the basis of available data and ultimate purpose of the model.
• Know how different types of 1D well and 2D map or cross-sectional data can be used to create geologically meaningful structure- and isopach-maps.
• Gain experience in using Leapfrog and Petrel
• Gain experience in the synthesis and presentation of geomodelling work

PART 1: Fundamentals (TM)

Lecture 1: What is geological modelling?
What is a model? Why was it built? How can it be visualized? Modelling in geological surveys: The BGS (British Geological Survey) surface-based modelling approach; The GDN (Geological Survey of the Netherlands) Voxel-based modelling approach

Lecture 2: Introduction to surface modelling
Subsurface interpretation: Hand-contouring of 2D seismic data; Computer mapping of 3D seismic volumes; Stacked surface models of conformable unfaulted sequences; Modelling methods for more complicated volumes: Pillar gridding; Explicit surface modelling (Structural Framework Modelling); Implicit surface modelling (Volume modelling).

Lecture 3: Data Characterisation for modelling
Data-driven vs. Geomodel driven modelling approaches. Sources and scales of sub-surface data: Properties at different scales and locations; Hierarchical modelling: Facies / domain modelling; Property / block modelling. Basic concepts: Correlated Random Fields; Stochastic Realisations, Heterogeneity, Anisotropy, Stationarity. Properties of univariate distributions: Mean, variance; Properties of bivariate distributions: correlation; Spatial variability: Autocorrelation, semivariance.

Lecture 4: Introduction to geostatistical modelling
Hand contouring; Computer contouring; Gridding: Graphical methods - Curve fitting, Splines. Linear Estimation methods: Weighted average methods; Kriging; Radial Basis Functions. Simulation: Sequential Gaussian Simulation.

Practical 1: Contouring and mapping

Practical 2: Estimation and modelling

PART 2: Fieldtrip, Malahide. (TM, KT, CC, LAA)

A day trip to the foreshore near Malahide (Co. Fingal) to examine and discuss characterisation and geomodelling with reference to outcrop geology.

PART 3: Static modelling (KT)

Lecture 5: Explicit geomodelling
Explicit vs. Implicit surface modelling approaches. Explicit geomodelling: Surface and Volume objects, meshes. Triangular Irregular Networks (TIN). Interpolation; mesh modification. Smoothing. Parametric surfaces: NURBS, Bezier, T-spline.

Lecture 6: Implicit geomodelling
Modelling geological surfaces using implicit modelling, Modelling geological surfaces using implicit modelling; 3D geomodels in Leapfrog: How does leapfrog model surfaces; Radial Basis Functions; Visual example of RBF implementation for domaining and isosurfacing in Leapfrog.

Lecture 7: Hierarchical, geometrical and topological rules
Chronology-based 3D modelling: deposit, erosion, intrusion, vein. Surfaces, Vein Systems, Stratigraphies. What do we model? What geometries and topologies do we need? Object or Surface Chronologies. Conditional modelling. Sealed Geological Models.

Lecture 8: Static Property Geomodelling: Mineral Resource Estimation Example - Supergiant Kamoa-Kakula copper project. Minerals resource estimation workflow: Sampling. Compositing. Domained 3D geological model. Block Model. Estimation methods. Cut-off Grade and Grade-Tonnage Curves. mineral resource estimation. Grade Control at the Lisheen Zn-Pb deposit.

Practicals 5-6: Designing and assessing the 3D geological and resource modelling of a mineral deposit using Leapfrog.

PART 4: Dynamic modelling (TM)

Lecture 9: Subsurface flow and Darcy’s Law
Subsurface flow considerations: Natural geofluid flows; operational flows and processes. Fundamental properties of porous media: Porosity and Permeability; Empirical models tied to experimental observations; Semi-theoretical models based on pipe-flow - The Carmen-Kozeny model, Explicit analytical approaches based on network models, reconstructed pore volume models. Darcy’s law in hydrogeology and petroleum geology: Fluid pressure and hydraulic head; Permeability vs. Hydraulic conductivity; Fluid viscosity.

Lecture 10: Darcy’s law and graphical flow modelling
Development of Darcy’s law: Fluid velocity in 1D and 3D; Ordinary and partial differential equations; Conservation of Mass; Laplace’s equation for fluid flow. Graphical solution to Laplace’s equation: Flow nets - Theoretical basis; Quantitative framework to solve Darcy’s Law; Rules for constructing a flow net; Comparison with a physical groundwater model. Numerical flow modelling approaches: 2D Computational flow nets: 3D streamline simulation: 3D finite difference simulation

Lecture 11: Introduction to numerical flow modelling
Introduction: Mathematical models, analytical solutions and discrete representations; Finite difference and Finite element discrete methods. The example system: 2D cross-sectional model of flow under a sheet-pile. Finite difference flow modelling in 2D: Grid conventions and the five-point scheme, Discretisation of Laplace equation; Implementation into Excel. Convergence of the solution; Iteration steps and convergence tolerance. Calculation of flow rate; Directional volumetric rates, dependence on transmissivity. Comparison between finite difference model and analytical flow net. Importance of boundary conditions.

Lecture 12 Finite Difference flow modelling
Reminder: Finite difference approximation to Laplace equation; Finite difference model of steady-state flow with no sources or sinks; Finite different formulation for Steady-state flow with sources or sinks. Example model: Dependance of head distribution on trasmissivility; Model interrogation: is it plausible? Sensitivity modelling to establish plausibility limits. Finite difference approximations for transient flow: Definition of Storage Coefficient. The explicit, implicit and fully-implicit solutions. Comparison of different transient solutions with an analytical solution. Summary: Finite difference flow modelling. Inclusion of heterogeneity. Typical stages in a flow modelling study.

Practical 7: Analysis of groundwater flow using flow nets
Practical 8: Introduction to finite difference flow simulation using Excel.

PART 5: Self-guided learning (TM, KT)

Full day exercise 1: Surface interpretation, mapping and volumetrics estimation in Petrel based on an onshore Australian dataset.

Full day exercise 2: Review of a technical integrated 3D geomodelling study focused on earth resource definition, management or production. Students will consider and assess the study requirements and design, and explain and assess conceptual models and modelling techniques employed

Student presentation: A 20-minute presentation on geomodelling aspects of a specific subsurface project.

Not applicable to this module.

• Feedback individually to students, on an activity or draft prior to summative assessment
• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment

Ongoing practical work will be discussed with students individually and collectively whist it be being performed during the scheduled practical classes. Additionally, written feedback (including grades) will be provided for specific pieces of practical work (about 50% of the total) that will be completed by the students by particular deadlines during the trimester. Students will be encouraged to seek one-to-one verbal feedback on these (and other) pieces of work as desired.