We see that using data science and machine learning in is a powerful way of revealing the hidden patterns in historic data.
The latest addition to our Machine Learning portfolio is well trajectory classification. The model helps us to identify similar well trajectories in seconds. The distance between trajectories is a quantification of similarity, and tells you how similar different well paths are to each other.
The feature will be included in our new release of our software, stay tuned for more data driven features.
It started with a discussion on how to solve a drilling problem for a portfolio of development wells, and the experienced drilling engineer asked us if we could do an analytical study based on data for the entire NCS to transfer experiences from all the historic wells.
Example of machine learning results with more than 1000 development wells in NCS^^ Curious of how drilling problems are distributed across fields, areas, formations, temperature ranges, depths, trajectories, operators or any other metric? We have capacity to take on data science and machine learning projects for drilling and well in September and October.