Machine Augmented Digital Rock Workflows for Business Impact
Brendon Hall
Despite sustained technological advances in machine learning for the analysis of digital rock images, there are relatively few examples of machine augmented workflows that have demonstrable business impact. There are significant challenges developing concepts into production ready tools. These challenges will be discussed in the context of two case studies - machine augmented analysis of thin sections and whole core CT scans. The technical challenges will be discussed, along with relevant infrastructure considerations. An integrated workflow will be demonstrated that integrates data from plug to log scale.
