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Deep Learning/Machine Learning Technical Interest Group (TIG)

Applying new analytics, neural networks, computational approaches using structured and unstructured data, and also training neural networks with supervised and unsupervised algorithms. Chaired by Patrick Ng and Andrew Munoz.
Deep Learning - Machine Learning TIG
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0 Replies and 285 Views Read This First!      285  0 Started by  Bogdan Michka Welcome to AAPG N.E.T., an online space where you can Network, Engage and Talk. Please complete the following steps before you begin interacting with the discussion boards: 1. Take time to review your profile and privacy settings, paying attention to your display name and photo, as they will be used to identify your posts. 2. Read the Discussion Boards FAQ page to learn the rules and get familiar with the features: — pa...
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09 May 2017 03:37 PM
0 Replies and 83 Views Azure, AWS and GCP - Plug and Play  83  0 Started by  Patrick Ng Hot off the press from Azure Expect AWS and GCP, if not sooner, interoperability to match. p.s. recall May 2019 Q1 snapshot post, 'Predict by 2020, kubernetes will afford true interoperability among different cloud platforms', Azure Arc beats that by a quarter!
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04 Nov 2019 02:45 PM
0 Replies and 86 Views Azure, AWS and GCP snapshot Q3, 2019  86  0 Started by  Patrick Ng Take a specific challenge - portfolio allocation, and focus on how we put it together. Visual reference, figures associated with the two Hybrid model articles. “Hybrid approach to Well Economics” “Operating profitably with $ 50 Oil” Azure Power ...
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23 Oct 2019 03:34 PM
0 Replies and 80 Views Drill down into risk and return using Hybrid model - from DCA to MPT  80  0 Started by  Patrick Ng Highlights of examples shown at the AAPG ML Workshop, Wichita KS two weeks ago. Hybrid model combines neural-network enabled decline curve analysis (DCA) and modern portfolio theory (MPT). We illustrate a powerful methodology to quantify risk and optimize portfolio allocation with granularity, integrity, transparency and science-based machine learning in mind. Examples using the same AI engine First quick check on Hart Energy Majors portfolio (six sto...
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23 Oct 2019 01:10 PM
0 Replies and 206 Views SEG Special Edition - Machine Learning Applications  206  0 Started by  Patrick Ng In case access is an issue, here is a quick takeaway (excerpt from The Leading Edge, July 2019) 1) demystify machine learning (ML) - using wedge model to illustrate thin-bed tuning effect, when the underlying physics is well understood then conventional inverse methods generally lead to a better solution, but when the physical model does not adequately describe the real world, or the inverse problem is nonlinear, then machine learning could succeed w...
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25 Jul 2019 01:03 PM
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Andrew Munoz Ensign Natural Resources
Patrick Ng Real Core Energy

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