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Are your skilled innovators not performing as quickly as you thought they would? I think I know why. -
As you read the examples in this section, you will see that a change is already under way in that the methods that are being used are increasingly not oil-and-gas-specific but instead follow patterns that are being used in other industries.
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What I find impressive is the number of people who were hiding in normal discipline jobs who are coming out of the closet with their Python scripts. And, it’s working. In many ways, order is coming to the mess, efficiency is coming to tiresome manual activities, and richness is coming to decisions.
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The world is digitalizing all around us. Within the energy sector, the lower-price environment since 2014 has increased the pace of change and the scope of digital integration. But, are you bringing your people strategy along?
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The most-competitive emerging systems blend artificial intelligence to bring better efficiency to the human work that results in good business decisions. As a result, we waste less time and fewer resources finding and manipulating data and focus more on complex engineering judgment.
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Over the last couple of decades, we have seen a steady stream of “intelligent” innovations go from ideas to infancy to catalog solutions.
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Artificial-intelligence (AI) -based methods have become mainstream engineering, and we as practitioners need to have a firm understanding of the principles and be ready to apply them when the opportunities arise.
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What is taking so long? Well, more than a decade into the intelligent-fields initiative, this is a question that remains prominent.
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I recently attended an internal conference in my company where one of the major topics was unconventionals. I have followed at some distance the business and technical trends that have shaped this still-emerging opportunity set, but this was my first exposure to behind-the-scenes experiences.
