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0 Replies and 595 Views
Highlights on Tackle the Issues - Where should Machine Learning go (and not go)? 595 0
Started by Patrick Ng
Observations - Dr. Lian and speaker Ball showed in examples simple architecture, random forest (RF) and support vector machine (SVM) work well in many cases (some as good as deep learning models). Q1: what does that tell us about ML model - simplicity vs complexity, and the direction Recap - much has to do with data / sampling. If we have lots of data, deep learning will do well. When we have limited data, RF and SVM may perform better (in supervised and unsupervis...
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02 Oct 2020 05:21 PM |
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0 Replies and 594 Views
Business Acumen, Soft Skills and Machine Learning 594 0
Started by Patrick Ng
In the opening Michel T. Halbouty Lecture: Business Acumen and Soft Skills in an Everchanging Exploration World Day: Duval talked about “soft skills” now considered all the more important since the “engineering” preparation of a prospective deal and the related technologies are and will be more and more dependent on data analytics, advanced approaches involving AI, machine learning, etc. Takeaway - two ML questions were raised in Chat, worthy of recap here. Q1: if you have physics based mo...
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02 Oct 2020 01:53 PM |
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04 Aug 2020 04:03 PM |
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27 Jul 2020 07:17 PM |
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0 Replies and 507 Views
URTEC 2020 507 0
Started by Andrew Munoz
Hi everyone, If you would like to see an interpreter/geologist friendly talk on adding value to seismic interpretation through pre-stack conditioning, please visit my talk: Unlocking Value from Vintage Seismic Processing - Pre-Stack Conditioning and Inversion in the Eagle Ford Shale at Urtec 2020 by visiting the following link and replaying the talk. https://urtec.onlineeventpro.freeman.com/live-stream/15346574/Theme-3-Geophysical-Reservoir-Characterization-Seismic-Attribute-Driven-Decisi...
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22 Jul 2020 01:50 PM |
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