Clustering of Wells with Machine Learning

Posted 15.10.2018 09:29 by Magnus Tvedt

Clustering of Wells with Machine Learning

In January 2019 we are launching a new era in Well Planning with our machine learning powered well analysis tool. Here is a behind the scenes peek of what you will get when we merge the best of data science with global experience transfer based on real data in well planning.

In this video we show you a preview of our well similarity module, where machine learning guide you towards wells with similar characteristics. The exiting value of this is that you instantly compare wells on known and unknown parameters.

So if you are comparing two wells because of their similar length in the 17 1/2" section, you  discover that there are other wells they are more similar to, guiding you to further learning and experience transfer. 

Can you imagine the work processes of browsing through similarities instead of searching for them?

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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
Magnus Tvedt
CEO Magnus Tvedt
Nicholas Mowatt Larssen
CTO Nicholas Mowatt Larssen
Cathrine Tangerås Eide
Project Manager Cathrine Tangerås Eide
Khushal Adlakha
Data Scientist Khushal Adlakha
Torgeir Lassen
CFO Torgeir Lassen
Eirik Lyngvi
Software Developer Eirik Lyngvi

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