A data-driven pathway to reliable geological models


Your next discovery is already in your data.

Most geological models are still user-driven. Driver closes the gap between available data and extracted insights from it. Using machine learning to detect and quantify structural trends directly from your data, it gives geoscientists a faster, more objective foundation to build on. Driver shifts the paradigm from user-driven to data-driven. The result is a structural foundation that is faster to build, easier to defend, and continuously informed by everything your data has to say.

In this white paper, you’ll learn:

  • How Spatial Continuity Mapping reads geological continuity in 3D from your drilling data
  • How OceanaGold found over 2,000 additional gold ounces from existing data in less than an hour
  • How Driver clusters its structural trends to segregate domains and isolate individual veins
  • Driver closes the loop from discovery to estimation, supporting LVA for accurate estimates

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