Data mining/analysis
This paper introduces in-pipe inspection technologies enabling high-resolution digital measurements of tubular internal diameter and wall thickness for critical downhole applications.
This paper describes an approach to creating a digital, interconnected workspace that aligns sensor data with operational context to place the completions engineer back into a central role.
This paper demonstrates how the integration of multiphysics downhole imaging with machine-learning techniques provides a significant advance in perforation-erosion analysis.
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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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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?
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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.