What's Happening?
Seequent, The Bentley Subsurface Company, has launched Imago image analysis, an AI-powered feature integrated into its cloud-based Imago solution. This new capability is designed to extract geological data from geoscientific imagery, specifically drill
core photos. The system utilizes proprietary machine-learning models to convert historical and new drill core tray images into quantitative geological data, such as downhole datasets for Rock Quality Designation (RQD). This automation significantly reduces the time required for analysis, transforming a process that traditionally took days or weeks into minutes. For instance, Imago image analysis processed 600 meters of core imagery in two minutes, generating structured, depth-referenced drilling data for subsequent interpretation. Geologists can review and adjust the AI-generated outputs against the original core imagery, ensuring validation before using the data in modeling, interpretation, and exploration decision-making. Customer imagery and geological data are securely managed within the Imago environment, with customers retaining control and the option to leverage their data to enhance analysis outcomes.
Why It's Important?
This advancement is crucial for the mining and exploration industries, offering a significant leap in efficiency and data consistency. Traditional core logging is a manual and qualitative process, often influenced by the individual geologist's training, experience, and available resources. By automating this process with AI, Seequent aims to introduce repeatability and improve the consistency of geological data, which is fundamental for accurate exploration decisions. This leads to substantial time and cost savings for organizations, from junior explorers to major mining companies. The ability to quickly and consistently analyze vast amounts of core imagery allows for more informed decision-making, potentially reducing risks and optimizing resource allocation in drilling programs. Furthermore, the integration of Imago image analysis with other geological software like Leapfrog and MX Deposit ensures that validated interval data can seamlessly flow into broader exploration workflows, enhancing the overall value of core imagery and geological data throughout the mining lifecycle.
What's Next?
The immediate next steps involve the adoption and integration of Imago image analysis by mining and exploration companies globally. As the technology becomes more widespread, it is expected to set new industry standards for geological data acquisition and analysis. Seequent will likely continue to refine its machine-learning models based on customer feedback and new data, further improving the accuracy and capabilities of the system. The company may also explore expanding the application of AI to other aspects of geoscientific imagery and data, potentially leading to more comprehensive AI-driven solutions for subsurface analysis. The increased efficiency and data quality could also foster more sustainable and responsible mining practices by enabling better resource management and environmental impact assessments. The long-term outlook suggests a shift towards more data-driven and automated approaches in geological exploration, reducing reliance on manual processes and human variability.
Beyond the Headlines
The introduction of AI into geological core logging represents a broader trend of digital transformation within traditional industries. This technology not only streamlines existing processes but also fundamentally changes how geological insights are derived, moving from subjective interpretations to objective, quantitative data. This shift could lead to a re-evaluation of geological training and expertise, with a greater emphasis on data science and AI literacy for future geologists. Ethically, the secure management of customer data within the Imago environment and the retention of customer control over their data are critical considerations, especially as AI systems become more sophisticated and handle sensitive information. The ability to preserve a direct connection to the rock itself while leveraging AI for analysis highlights a balance between technological advancement and the foundational principles of geology. This development could also democratize access to high-quality geological analysis, enabling smaller companies with fewer resources to compete more effectively with larger corporations by utilizing advanced AI tools.
