by   |    |  Estimated reading time: 2 minutes  |  in Business Technology, Digital Transformation, Oil & Gas, Strategy   |  tagged , , , , , ,

Advancements to analytics are making it possible for oil and gas companies to operate like never before.

Picture yourself knowing your own equipment very well. You have a long history in understanding the design, the operation, the maintenance, the possible failure and the replacement of the equipment you own and operate. This shouldn’t be too hard to picture – this is the reality for most asset owners.

Then picture yourself and the models you have built in order to better understand this equipment. Maybe you have engaged your smartness in building physics-based models that help you understand the system you operate. Maybe you are using single variable threshold analysis to predict the operating state of your equipment. Both methods are well-established ways of optimizing the performance and help predict failure modes.

Overwhelmed by the hype of digital transformation, you have looked into the world of machine learning and artificial intelligence (AI). From every stage in the world, you are being told how different the world will be in just a few years’ time. From a conceptual point of view, you see the logic of the ideas presented – you just don’t exactly know where to start.

Becoming a believer of advanced analytics

Let me then introduce Mr. X. You invite Mr. X into a meeting at your office. You tell him that you can predict the failure of a certain equipment but that you see great potential if you could extend this interval from the 4 hours that you operate with today. Is this something Mr. X wants to look into?

Mr. X. is an engineer, so if you give him a seemingly unsolvable task he becomes unstoppable. He asks for 75% of your data and makes an appointment to come back with his test results.

He comes back to you and says he can predict failure 4 days in advance – not 4 hours. WOW – that’s something. Can he prove it? Well, I only asked for 75% of your data originally. Now I’ll ask for the next 25% so we can test my model against the real data. Then, he asks rhetorically, “If my model can predict correctly against the remaining data, what amount of trust will you then assign to the model?”

Now let’s picture this is all true. Have you then turned yourself into a believer of advanced analytics? I certainly hope so…

If you’re interested in learning more about the use and benefits of advanced analytics in the oil and gas industry, read my white paper: Advanced analytics and the digital transformation of the oil and gas industry.

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