Trajectory similarity using Machine Learning

Posted 22.10.2018 11:09 by Cathrine Eide

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.

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Score: 8/10 - Our First Machine Learning Project Delivered

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.

Now Available - Easy start to Machine Learning Projects in Well...

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.
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The Team

Pro Well Plan AS is based in Bergen, Oslo and
Stavanger
Magnus Tvedt
CEO Magnus Tvedt magnus.tvedt@prowellplan.com
Nicholas Mowatt Larssen
CTO Nicholas Mowatt Larssen nimola@prowellplan.com
Cathrine Tangerås Eide
Project Manager Cathrine Tangerås Eide cathrine.eide@prowellplan.com
Khushal Adlakha
Data Scientist Khushal Adlakha khushal.adlakha@prowellplan.com
Torgeir Lassen
CFO Torgeir Lassen torgeir.lassen@prowellplan.com
Eirik Lyngvi
Software Developer Eirik Lyngvi eirik.lyngvi@prowellplan.com

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