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 459 Views Read This First!      459  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 14 Views Geothermal Anywhere starts with a click on a map  14  0 Started by  Patrick Ng AAPG Explorer - Existing Skills, Infrastructure Could Power Geothermal Revolution January 2022 Issue Now we can go Big on energy transition, if we can turn 'geothermal anywhere' into reality. It so happens there is an app for that It complements the macro 45,000 ft view of the most current and comprehensive maps published by the Southern Methodist University’s Geothermal L...
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18 Jan 2022 06:24 PM
0 Replies and 61 Views Advancing ESG with Data Analytics  61  0 Started by  Patrick Ng In it, we'd highlight the challenge of machine learning on combined geospatial and time history data, is ripe for GANs. So anyone who can share their experience on generative adversarial network design / data prep will really help the AAPG community.
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02 Dec 2021 11:43 AM
0 Replies and 128 Views CCUS - from an Independent's perspective  128  0 Started by  Patrick Ng This AAPG Pivoting 2021 Webinar took place 09.15.2021. Link to the video recording will be added when available. Watch this space. Data - the challenge and opportunity to 'play' with satellite imaged infrared data is posted on Xrathus (sign up and access). Get set and get started. Abstract - Until recently, Enhanced Oil Recovery (EOR) projects utilizing CO2 have primarily been the exclusive bailiwick of large operators with ...
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16 Sep 2021 09:11 AM
0 Replies and 141 Views Azure, AWS and GCP Snapshot Q2 2021  141  0 Started by  Patrick Ng Premise - usability of OSDU (open subsurface data universe). Scenario - want to access seismic and well log data, prep ML. Azure - Machine Learning Studio (classic) offers the best-in-class drag-and-drop machine learning builder. For those experienced in seismic data processing, the UI comes naturally. However, when it comes to OSDU, if accessible via OSDU connector, like Power BI, that will supercharge ML Studio to ML Nirvana. (Just add one OSDU box at the top to the rest of prep-ML workf...
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19 Jul 2021 09:10 PM
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