How KoBold Metals transformed mineral exploration

KoBold Metals isn't a traditional mining company. Instead of relying solely on geological intuition and luck, they're revolutionizing mineral exploration through data science and artificial intelligence.

Focused on four critical minerals essential for modern batteries—nickel, copper, cobalt, and lithium—KoBold analyzes vast amounts of geospatial data to determine which areas are most likely to contain valuable mineral deposits before committing significant exploration resources.

This computational approach to mining transforms what was traditionally an intuition-driven process into a repeatable, data-driven science. The goal: identify promising exploration targets faster and with greater precision than conventional methods.

KoBold's analysis starts with two fundamental data types:

1. Point-sampled surface data - Geochemical samples revealing mineral composition at specific locations
2. Continuous field data - Magnetic and gravitational fields measured across entire regions

As exploration progresses, the team incorporates increasingly complex data sources:

• Electromagnetic responses from subsurface structures
• Hyperspectral imagery with hundreds of spectral bands
• Drilling results when a project advances to direct sampling

The computational demands become particularly challenging when processing magnetic field data, which requires taking derivatives of potential fields in various directions. These calculations involve Fourier transforms of entire regions—a process that quickly exceeds the capabilities of even the most powerful workstations.

As the team sought to analyze more extensive areas with finer resolution, they needed a solution that could scale with their ambitions.

KoBold built their technical stack on Python's scientific computing ecosystem, leveraging a combination of standard libraries and custom code:

• NumPy and SciPy power their core numerical computations
• X-Array manages multidimensional geospatial data
• Simpeg simulates electromagnetic responses
• Dask coordinates parallel computing tasks
• Custom algorithms handle specialized geostatistical analysis

When processing demands outgrew single-machine capabilities, KoBold evaluated several cloud solutions. The decisive factor in choosing Coiled was its seamless integration with their existing workflow:

This integration eliminated deployment friction and allowed KoBold's scientists to focus on what they do best—analyzing geospatial data to find promising mineral deposits—rather than managing cloud infrastructure.

With Coiled, KoBold transformed their analytical capabilities, tackling problems that were previously out of reach:

The success of their initial magnetic field processing pipeline catalyzed adoption across the organization. Today, the team uses Coiled for diverse applications:

1. Remote sensing analysis across multiple spectral regimes
2. Hyperspectral processing with hundreds of bands from aircraft surveys
3. Stochastic inversions that generate subsurface models from surface data

From a small group of early adopters, Coiled usage expanded to several team members across departments. The platform's observability features proved particularly valuable for optimization:

For computationally intensive tasks like hyperspectral image processing, KoBold now leverages clusters that would be impractical to maintain in-house.

The computational capabilities enabled by Coiled transformed KoBold's ability to evaluate potential mining sites quickly and accurately:

This acceleration directly impacts the company's core business strategy: generating and falsifying hypotheses about mineral deposits as efficiently as possible. By rapidly evaluating the potential of different areas, KoBold makes smarter decisions about resource allocation—avoiding wasteful expenditure on less promising sites and focusing efforts where data suggests the highest probability of success.

The ability to process continental-scale datasets gives KoBold a competitive edge in identifying promising regions that traditional exploration methods might miss. As the company expands operations, the computational foundation provided by Coiled allows them to evaluate more sites with higher resolution and greater accuracy, without proportional infrastructure costs.

As demand for battery metals grows with the global transition to electric vehicles and renewable energy, efficiently identifying new mineral deposits becomes increasingly critical. KoBold's computational approach, powered by Coiled, positions them at the forefront of this essential industry.

By turning mineral exploration into a repeatable science rather than a hit-or-miss endeavor, KoBold isn't just finding minerals more efficiently—they're redefining what's possible in an industry that has remained largely unchanged for generations.

For a modern mining company looking to discover the materials that will power our future, the combination of advanced geoscience, comprehensive data, and scalable computing provides a foundation for success in an increasingly competitive global market.