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0 Replies and 422 Views Takeaway from Playmakers Series / Moneymakers Forum @OKC  422  0 Started by  Patrick Ng Takeaway - expect shifting landscape and limiting capital for the next 3 years. Reasons being: 1) Binge on leasing and flipping is over. Consolidation is happening. 2) Focus on returns and cash flows. Running a business for the long haul (vs. transacting in and out). So the Panel's exchanges on: a) Minimize frac hits (interference) - combine analytics and in-situ experiments, pave the way to reduction of plugs with diverting agents, eventually lead to potential savings of $ 450,000 to ...
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05 Apr 2019 11:48 AM
0 Replies and 355 Views Automated Machine Learning vs ML causing crisis  355  0 Started by  Patrick Ng Fine tuning ML model is made easy with Azure’s automated ML (link: https://azure.microsoft.com/en-us/blog/announcing-automated-ml-capability-in-azure-machine-learning/ ) While it is the opposite end member to “ML causing science crisis” (February 20, 2019 post), the real question is whether we learn with the machine, or outsource learning to the machine with “No need to “see” the data'. For gut check, how about auto-nose correction algorithm on the 737...
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23 Mar 2019 12:00 PM
2 Replies and 402 Views Machine Learning causing science crisis?  402  2 Started by  Patrick Ng 'Machine-learning techniques used by thousands of scientists to analyse data are producing results that are misleading and often completely wrong.' Link: https://www.bbc.com/news/science-environment-47267081 According to professor Allen from Rice University, Houston, “answers they come up with are likely to be inaccurate or wrong because the software is identifying patterns that exist only in that data set and not the real world.” Crisis Not quite. Pe...
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20 Feb 2019 01:55 PM
0 Replies and 359 Views Machine Learning experience across the Pond  359  0 Started by  Patrick Ng The very first EAGE / PESGB Workshop on ML, November 2018, focused on the latest developments in digital transformation, AI / ML, analytics, cloud computing, approaches, challenges and business impact in upstream. Link https://www.eage.org/sitecore/content/events/home/2018/first-eage-pesgb-workshop-on-machine-learningsc_lang=en Specifically of interest here are Deep Learning applications - 1. Reservoir properties prediction - compare deep neural network with multi-vari...
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12 Feb 2019 10:39 AM
0 Replies and 355 Views Business Breakthroughs with Digital Transformation Crossing Disciplines coming June 2019 @Austin, Texas  355  0 Started by  Patrick Ng Whether it is machine learning, AI or game changing practices we always want to know but may be afraid to ask, Energy IN Data is one venue to learn about, and share our experiences on tackling these challenges: 1. Technology / workflow 2. Business model / organizational culture 3. Changing professional / industry landscape See attached flyer for more information.
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07 Feb 2019 11:41 AM
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