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Weekliii Round-Up: News on the Pipeline Planning Processing and Recycling Oil Rigs for CO2 Storage

Updated: Dec 19, 2019

Here's your chance to catch up on all the Oil and Gas news, technology talk, and more in today's #WeekliiiRoundUp post. Read on!



The way in which a developing field is planned will differ from project to project. When considering the area, the presence of assets for tie-ins, the possibility of future development, and many more factors, our teams must choose the approach that best supports these circumstances. Let's take a look ahead at better optimizing Oil and Gas asset and pipeline placement by embracing methods like backcasting and forecasting. Discover how apps like Integrated Geomancy can help in this week's #MeetTheProduct post.




Decommissioning old oil rigs is expensive and often wasteful. Could re-purposing them for CO2 storage be the solution? Let's explore this idea in this week's #DailyBrainCandiii post.

Refitting old platforms to act as pumping stations for self-contained CO2 storage sites would be 10 times cheaper than decommissioning the structures. The sites would store emissions generated by Natural Gas production.


We're here to help. Explore ways we help set teams like yours on the right path with services like Business Analysis, custom software development, Geographic Information System (GIS) implementation and training, and much more. Discover more now.



One of the most vital factors of Machine Learning is understanding the core business problem and objective of the outcome, framing your approach accordingly. How do you frame these problems? Learn more in this week's #DailyBrainCandiii post.

A general approach for Machine Learning processes to address a core business problem is difficult to recommend without intimate knowledge of the data in use. To help formalize the model, asking questions can help us decide on the issue and what deserves focus. For example... What am I trying to predict? What are my outcomes? As well as... What data can I use to train my model, and what are my inputs? What market factors can I train my model with to predict the outcomes?

 

#DailyBrainCandiii and #WeekliiiRoundUp are inspired by brain candiii, a division of Integrated Informatics that develops Geographic Information System (GIS) training for Energy and Natural Resources professionals.


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