Data mining/analysis
A roundtable discussion during CERAWeek pointed to the necessity of a mindset shift for the oil and gas industry to tap into AI’s true potential.
Technology and partnerships play a pivotal role in how the oil industry finds and produces energy from frontier regions and brownfields, both now and in the future.
The authors make the case that data science captures value in well construction when data-analysis methods, such as machine learning, are underpinned by first principles derived from physics and engineering and supported by deep domain expertise.
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Strides made in data analytics over the past few years have been huge. But the complexity of data, and understanding how to use them, can delay the advantages to be gained. If the benefits and methodology of data acquisition are not better explained to engineers, might implementation suffer? -
These days, it is all about digital. Click to find out what industry leaders from Encana, Google, Schlumberger, and Shell have to say about the ongoing transformation towards data-driven profitability.
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The same tools that make it fun and easy for you to see a friend's updates online are also pretty good at tying together unconnected databases holding valuable well information.
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Today’s advancements in unconventional technology are worth marveling over, but there is still plenty of room for growth.
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The company behind the world’s most popular search engine is trying to click with the upstream business at the most distinguished technical event of the year.
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Some operating companies are now enlisting engineers as foot soldiers in their analytics army. It is not required yet, but those looking to get ahead would be wise to get involved.
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Unconventional operators are finally beginning to use to their advantage the nearly endless stream of data they’ve collected over the years. ConocoPhillips explains how it has seen real improvements in its operations by removing data friction and opening up access across typical work silos.
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As leaders in digital drilling analysis push into real-time data analysis and digital controls, they are finally confronting data-quality problems. Humans are better than machines at dealing with ambiguous readings.
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The process of finding, developing, and testing new technology can be as complicated as the technology itself—especially at a time when operators have little tolerance for risk.
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Big-data mining techniques can help determe the type-curves and the resulting estimated ultimate recovery of an asset being evaluated for acquisition.
