A digital revolution is underway in all sectors of our economy (Gurumurthy and Schatsky, 2019), posing unique challenges and opportunities for science and engineering research and practice. Still, in many ways, geoscientists and subsurface engineers are further down the digital path due to our long history of implementing data-driven methods in our workflows. Motivated by the complexity of the vast subsurface, the challenges of subsurface data, including data volume, variety, and veracity, and the necessity to support costly development decisions, statistical tools for subsurface resource estimation and mapping were developed by Krige (1951) and later augmented with theory...

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