A kriging estimator delivers a single 'best' grade estimate - best in the sense of minimising the estimation error. Sometimes, however, a single 'best ' estimate is not the answer to the question at hand. While deterministic grade estimates are useful for many purposes, they do not allow questions about inherent uncertainty to be addressed.
Conditional simulation provides an alternative method for quantifying uncertainty through development of an ensemble of equiprobable realisations. This concept is intuitive to most geologists – yet despite simulation methods having been available for decades, the methods are not widely or routinely used. Our aim at Seequent is put robust workflow-based conditional simulation outputs, tailored to users needs, into the hands of geologists.
In this webinar, Seequent’s Technical Domain Expert Mike Stewart will explore how Leapfrog Geo and Seequent Evo together unlock accessible, cloud-enabled conditional simulation workflows for grade control and resource geologists.
You’ll discover how Leapfrog’s intuitive modelling environment integrates seamlessly with advanced geostatistical compute in the cloud via Seequent Evo, empowering you to:
- Generate conditional simulations and return post-processed outputs in a single seamless workflow
- Validate model outputs through a dashboard of result
- Add value through application of an economic value calculation to classify ore, taking into account the underlying uncertainty in grades
We’ll step through an open pit mining case study demonstrating how conditional simulation workflows can be practically implemented in your projects today, enabling your team to realise value from uncertainty.
Overview
Speakers
Mike Stewart – Technical Domain Expert – Seequent
Duration
46:35 mins
