This phase involves understanding the sub-surface and surface conditions to guide design, construction, or resource extraction.

1. Geological Exploration

Focuses on studying the physical and chemical characteristics of surface and sub-surface materials.

Objective: Identify rock types, soil conditions, fault lines, mineral deposits, and stability.

Key Activities:

• Geological mapping of surface formations
• Identification of rock and soil types
• Structural geology (faults, folds, fractures)
• Assessment of slope stability and erosion risks
• Collection and analysis of rock/soil samples
• Assessment of weathering patterns and landslide potential

Tools & Methods:

• Field sampling and petrographic analysis
• Geological mapping tools (Brunton compass, clinometers)
• Laboratory testing (Atterberg limits, grain size, UCS tests)
• Remote sensing and aerial photography

2. Geophysical Exploration

Involves indirect investigation of subsurface conditions using physical properties.

Objective: Detect variations in subsurface features like voids, water tables, faults, and rock interfaces.

Key Activities:

• Measurement of physical parameters (resistivity, magnetism, gravity, seismic velocity)
• Locating underground water, mineral bodies, or cavities
• Identifying depth and thickness of strata
• Mapping fault zones and potential hazards

Techniques Used:

• Seismic Surveying: Measures wave velocity to interpret sub-surface layers
• Electrical Resistivity: Identifies moisture content and layer differentiation
• Magnetic Surveying: Detects magnetic anomalies linked to mineral deposits
• Ground Penetrating Radar (GPR): High-resolution imaging of shallow subsurface
• Gravity Survey: Detects density variations below the surface

Deliverables:

• Geological and geophysical maps
• Subsurface profile models
• Risk assessment reports (landslides, liquefaction, sinkholes)
• Recommendations for design modifications or construction methods

This process involves quantifying the amount, quality, and distribution of mineral resources in a given geological deposit using data-driven and geostatistical methods.

Objective:

• Determine the size, grade, geometry, and economic viability of a mineral deposit.
• Provide a basis for mine planning, valuation, and investment decisions.

Key Inputs:

• Exploration Data: Drill hole logs, trench samples, channel sampling
• Geological Data: Rock types, structures, alteration zones
• Assay Results: Mineral concentrations and grades
• Geophysical & Geochemical Data: Supporting indirect indicators of mineralization
• Topographic & Survey Data

Estimation Process:

1. Data Compilation & Validation
   • Cleaning and verification of geological and assay data
   • Removal of duplicate or erroneous entries
   • Quality control of sampling techniques and lab procedures
2. Geological Modeling
   • Development of 3D geological framework
   • Interpretation of lithology, faults, ore zones, and boundaries
   • Use of software such as Surpac, Leapfrog, or Datamine
3. Compositing & Domaining
   • Aggregating sample data into regular intervals (composites)
   • Defining geological or grade domains for focused estimation
4. Statistical & Geostatistical Analysis
   • Descriptive statistics: mean, variance, histograms
   • Variogram analysis for spatial continuity
   • Anisotropy detection for directional mineral trends
5. Grade Estimation
   • Techniques Used:
     • Inverse Distance Weighting (IDW)
     • Ordinary Kriging (OK)
     • Multiple Indicator Kriging (MIK)
     • Conditional Simulation (for risk assessment)
   • Estimation of block grades, tonnage, and mineral content
6. Resource Classification
   • Categorized as per international codes (e.g., JORC, NI 43-101, SAMREC):
     • Measured: High confidence
     • Indicated: Moderate confidence
     • Inferred: Low confidence

Modeling Outputs:

• 3D Resource Block Model (tonnage, grade distribution, ore boundaries)
• Cut-off Grade Analysis
• Tonnage vs Grade Curves
• Classification Maps showing resource confidence levels
• Mineral Inventory Reports

Reporting Standards:

• Compliant with international reporting codes (e.g., JORC, CIM NI 43-101, SAMREC)
• Inclusion of QP (Qualified Person) sign-off
• Clear disclosure of methodology, assumptions, and risks

This process combines geospatial technologies to capture, analyze, visualize, and interpret spatial data for informed decision-making in planning and operations.

Objective:

• To collect, manage, analyze, and visualize spatial and environmental data.
• Support site selection, land use planning, resource management, and hazard analysis.

GIS Mapping (Geographic Information System)

1. Definition & Purpose
   • A system for capturing, storing, checking, and displaying spatial (geographic) data.
   • Integrates location data with attributes to map relationships, patterns, and trends.
2. Key Activities
   • Creation of thematic maps (land use, soil, topography, infrastructure, drainage, etc.)
   • Digitization and geo-referencing of maps
   • Spatial analysis (proximity, buffer, overlay, slope, aspect)
   • Database creation of spatial and non-spatial attributes
   • Query and visualization for planning and reporting
3. Tools & Software
   • Software: ArcGIS, QGIS, MapInfo, ERDAS Imagine
   • Hardware: GPS units, total stations, drones, satellite receivers
   • Data Sources: Satellite images, topographic sheets, drone surveys, field data

Remote Sensing Analysis

1. Definition & Purpose
   • Acquisition and interpretation of data from satellite or aerial platforms to assess the Earth’s surface.
   • Helps in large-scale and inaccessible area analysis.
2. Key Activities
   • Image acquisition (multispectral, hyperspectral, radar, thermal)
   • Pre-processing (radiometric and geometric correction)
   • Image classification (supervised & unsupervised)
   • Change detection analysis (land cover/use changes over time)
   • Vegetation, soil, water body, and urban feature analysis

Techniques Used

• NDVI (Normalized Difference Vegetation Index) – vegetation health
• LULC (Land Use Land Cover) Mapping – land categorization
• DEM/DTM/DSM Generation – elevation and terrain modeling
• Thermal and Infrared Analysis – heat zones and water stress

Applications

• Urban & Infrastructure Planning
• Environmental Impact Assessments (EIA)
• Disaster Risk Mapping (floods, landslides, erosion)
• Agriculture Monitoring & Crop Health Analysis
• Natural Resource Management (forests, minerals, water)
• Road Alignment, Utility Corridor, and Land Acquisition Planning

Deliverables

• High-resolution base maps (topographic, thematic, analytical)
• Geo-databases with attribute-linked spatial data
• 3D Terrain Models and Elevation Profiles
• Change Detection Reports and time-series analysis
• Interactive GIS dashboards for visualization and decision support