EigenformAI/ReSolveSA

🪨 Dataset Description: segments_with_geochem.csv

🧾 Overview

This dataset is a merged collection linking image segments of drill core trays with their corresponding lithological and geochemical information.
Each row represents one image segment (a small interval of core depth) combined with a specific geochemical measurement.

It contains 17,992 rows and 31 columns, integrating three main data sources:

1. Segmented core images generated from hyperspectral core tray processing.
2. Lithology intervals from SARIG drillhole logging data.
3. Geochemical assay data matched by drillhole and depth range.

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🧱 Structure and Key Columns

Category	Example Columns	Description
Image Segment Metadata	filename, drillhole_number, core, segment, depth_m	Derived from processed images (e.g. 9955_5_9_9.15.jpg). Each represents a core segment at a specific depth within a drillhole.
Lithology Data (SARIG)	LOG_NUMBER, LOGGING_ORGANISATION, QUALIFICATION, LOGGING_DATE, major_lithology, DESCRIPTION	Imported from SARIG drillhole lithology logs. These describe rock type, logging geologist, and confidence of lithological interpretation.
Spatial Coordinates	EASTING_GDA2020, NORTHING_GDA2020, LONGITUDE_GDA2020, LATITUDE_GDA2020, ZONE_GDA2020	Georeferencing information for each drillhole site.
Geochemistry Data	chem_code, value, unit, chem_method_code, chem_method_desc	Chemical element concentrations and assay method details. For example, chem_code = 'Cu', value = 85, unit = 'ppm', chem_method_code = 'IC4M'.
Depth Range (Lithology/Assay)	depth_from_m, depth_to_m	Defines the downhole interval associated with the lithology or geochemical measurement.

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🧬 How It Was Made

1. Core Segmentation

Core tray images were processed into individual core segments using depth data.
Each segment was saved as an image file named using this pattern: [drillhole_number]_[core_number]_[segment_number]_[depth_m].jpg

Example: 9955_5_9_9.15.jpg → Drillhole 9955, Core 5, Segment 9, Depth 9.15 m.

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2. Lithology Mapping

Each image segment was matched to SARIG lithology logs (sarig_dh_litho_exp.csv), using: drillhole_number matches AND depth_from_m <= segment_depth <= depth_to_m

This allowed each segment to inherit lithological attributes such as major_lithology and DESCRIPTION.

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3. Geochemical Integration

The merged segment–lithology dataset was further joined with SARIG assay data.
Matching was again done by drillhole_number and depth overlap.
Each segment now includes one or more geochemical assay results (e.g., Cu, Fe, Au) with their chem_method_code and measurement units (commonly ppm).

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📊 Purpose and Use

This dataset is designed for data integration and machine learning applications that connect visual and chemical rock properties.
It can be used for:

• Linking visual mineralogical features in core images to geochemical compositions.
• Building ML models to predict chemistry or lithology from imagery.
• Performing cross-domain correlation between NVCL hyperspectral data and laboratory assays.

Each record connects what’s seen in the rock (image/lithology) to what’s measured in the lab (chemistry).

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🧪 Notes

• The value column represents assay readings, often in ppm (parts per million).
• The unit column confirms the measurement type (e.g., ppm, %, etc.).
• The dataset integrates spatial, spectral, and chemical data — making it suitable for multi-modal mineral systems analysis.