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Tapping into Geospatial Data for Better Insights

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Oil and gas organizations collect massive volumes of data being generated and stored in the well planning, drilling, and production processes. Integrating these data sets for visualization and analysis is difficult. New technology brings new opportunities to tap into these datasets for modeling across geographies and time. The key is geospatial analytics which has historically been available only to GIS specialists focused on mapping and data automation/management. 

You can play with the live data and tools via an online demonstration from OmniSci. Interactively explore a US oil and gas dataset from UpstreamDB covering nearly 256 million well production records from nearly 1.3 million wells, spanning 20 years of well performance. Analyze production decline performance, correlations, rate of change and compile formation-based type curves in seconds.

As geospatial capabilities support large datasets over time, data that was collected for a single purpose can now be used for new analysis to make better decisions and find hidden opportunities. See what you can find in the data and imagine what else you can do by adding your own internal information. 

Linda Stevens's picture

Thank Linda for the Post!

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Matt Chester's picture
Matt Chester on Jan 13, 2020 4:17 pm GMT

Interesting-- what sort of applications will this have? Is this more for people in  the oil and gas industry or for outside stakeholders (regulators, citizens, etc.) to get a view of the oil and gas industry?

Linda Stevens's picture
Linda Stevens on Jan 13, 2020 6:50 pm GMT

Within the industry. This data and analytics capabilities help oil & gas companies increase well yields by looking at trends over time. It also helps organizations identify properties to lease and monitor operational, fleet and vendor activity in real-time to ensure quality and consistency. And by being able to do this analysis quickly, organizations are saving time in finding the best wells to target, giving them a competitive edge. 

I think as more organizations realize they can effectively use large datasets that have a geographic component in their analytics, we will see even more creative applications. 

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