AI-Powered Core Logging

🔍 What Is AI-Powered Core Logging?

AI-powered core logging involves the use of machine learning and computer vision to analyse high-resolution images of drill core or chips. These systems are trained on thousands of geological examples to automatically detect and classify features such as:

• Lithology

• Veining and texture

• Alteration zones

• Structural features

• Mineralisation indicators

Instead of relying solely on manual logging, which is often time-intensive and variable between geologists, AI can process imagery and generate preliminary interpretations in a consistent and structured format.

🧩 What Pain Points Can It Address?

Core logging is a critical step in mineral exploration, but several challenges persist:

• Time Consumption: Logging can take days or weeks depending on the volume of core, delaying subsequent analysis and decision-making.

• Subjectivity: Interpretation varies between geologists, which affects data consistency—especially across large teams or over long projects.

• Backlog of Historical Data: Many projects have years’ worth of core imagery that remain underutilised.

• Pressure on Resources: Exploration teams are often lean, with limited time to process and interpret increasing volumes of drilling data.

AI helps address these issues by:

• Rapidly analysing core imagery

• Applying consistent classification rules

• Supporting integration with existing geological databases and modelling tools

🧪 Example: Datarock (Australia)

Datarock is an Australian geoscience technology company applying AI and computer vision to geological data. Their platform allows users to upload core tray images and receive digital interpretations based on pre-trained models and project-specific calibration.

Key features of the Datarock system include:

• Lithological and structural classification from imagery

• AI-assisted visual logging with geologist input

• Compatibility with popular platforms like Leapfrog and Imago

• Scalable workflows for both greenfield and brownfield projects

Datarock’s tools are used by exploration and mining companies seeking to improve turnaround time, reduce manual workload, and build more consistent geological model

📚 Why This Matters

As exploration programs grow more data-intensive, tools that enhance the speed and reliability of geological logging are becoming essential. AI-powered logging:

• Reduces delays between drilling and interpretation

• Standardises geological datasets for modelling and resource estimation

• Enables faster decision-making in dynamic exploration environments

• Supports digital transformation without replacing geoscientific expertise

By incorporating AI into workflows, companies can extract more value from their data and improve operational efficiency across the board.

This is the first post in a series exploring how AI is transforming drilling and exploration in Australia. Next, we’ll look at AI applications in real-time rig data analysis.

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