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0 Replies and 451 Views
Deep Learning with Deep Earth Data 451 0
Started by Patrick Ng
Remember the movie 'Inception', DiCaprio explained about planting a thought inside someone's mind - 'We need to go deeper' https://www.iugs.org/dde This is our opportunity to do really deep dive into Earth's data universe, e.g., is 5-layer RNN good enough, or go deeper with 128, and if quantum computing is handy, why not 1,024 kind of deep No doubt what DeepTime Digital Earth reveals will span years of work and lead to hundreds of papers published. But for data sleuths, al...
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13 Jul 2021 03:18 PM |
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0 Replies and 488 Views
ML - more doing, less guessing 488 0
Started by Patrick Ng
Premise - we all learn AI / ML in different ways, I for one go for Coursera (Prof Andrew Ng's ML series) and BYO apps, as well as online learning nuggets that offer value for no cost. Actionable - starting tomorrow, free sampling intro sessions across ML and data science offering from Daytum, an energy-focused education platform. https://www.eventbrite.com/o/daytum-21726800390 First and foremost, Prof Pyrcz speaks 'geo' and makes these a solid starting point / refresher for anyone embar...
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09 Jun 2021 01:57 PM |
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0 Replies and 420 Views
AAPG-SPE Marriage 420 0
Started by Patrick Ng
We all read this morning AAPG and SPE coming together as one. It accelerates the shift from petroleum to energy. So how can Deep Learning TIG contribute 1. Learn a little more jargons used (may be same term but different context) and communicate better; e.g., using visuals of 3Ps (P10, P50, P90) and simple proxy model (linear fit) may be useful. Click on the map (e.g., sweet spots around Midland Airport) https://www.vue-shale-wells.com/ Update 06.09.2021 - attach...
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25 May 2021 09:22 AM |
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0 Replies and 425 Views
Azure, AWS and GCP Snapshot Q1 2021 425 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 |
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0 Replies and 463 Views
Pivot 2021 - ML, Geothermal and Smart Completions 463 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 |
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