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 384 Views Read This First!      384  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 18 Views Azure, AWS and GCP Snapshot Q1 2021  18  0 Started by  Patrick Ng Pick up where we left off last post October 23, 2019 (Azure, AWS and GCP snapshot Q3, 2019). Premise - here we shall focus on productivity (min coding max use of ML). Scenario - take a spreadsheet or table like (structured) dataset, where the rows are well API numbers, and columns of location, well depth, lateral length of horizontal wells, formation thickness, porosity, velocity, density, other subsurface properties, etc.). Objective - train ML model to rank some proposed well locat...
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27 Apr 2021 07:44 PM
0 Replies and 24 Views Pivot 2021 - ML, Geothermal and Smart Completions  24  0 Started by  Patrick Ng Learning from other industries - sign up for a free workshop April 28, after hours for flexibility Presentations: John Holbrook, Ph.D., Texas Christian University Geothermal Developments, Solar Energy Storage Sean Marshall and Danny Rehg, Criterion EP Geothermal Lease Evaluation – A Challenge Dan Taranik, Exploration Mapping New and Old Satellite Imagery for Surface Temperature and Emissivity Deborah Sacrey, Auburn Energy Bivariate Statistics on Old East Texas Field for New Pr...
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22 Apr 2021 03:00 PM
0 Replies and 27 Views EiD - Probing Questions and Seeking Answers  27  0 Started by  Patrick Ng These three observations can benefit taking feedback / sharing experience from a wider community - 1) Edge computing - lots of applications in edge computing helps us reduce cost and increase efficiency. Edge computing enables cheaper ML model to be built and at different time scales. 2) Knowledge curation - make open-source movement useful, we need to organize information in one place (reservoir, geoscience, engineering) and make that searchable like Yahoo! in the early days of internet....
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16 Apr 2021 01:41 PM
0 Replies and 29 Views Energy in Data 2021 - Greeting  29  0 Started by  Patrick Ng Thinking about the two-morning workshop It is a click away.
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08 Apr 2021 12:16 PM
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