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1 Replies and 1127 Views
TensorFlow in the Cloud - AWS, GCP or Azure? 1127 1
Started by Patrick Ng
TensorFlow on three platforms - first impression: Amazon Web Services (AWS) - does require use of Unix script, and if running from Windows, additional download of utility PuTTY for ssh connections (geek speak for cybersecurity key). https://www.datacamp.com/community/tutorials/deep-learning-jupyter-aws Google Cloud Platform (GCP) - much the same as AWS, and no PuTTY download required. https://towardsdatascience.com/running-jupyter-notebook-in-google-cloud-platform-in-15-min-61...
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0 Replies and 924 Views
Alexa Well Econ coming to your Amazon Echo 924 0
Started by Patrick Ng
For the avid followers of the December 30, 2017 entry, Alexa Well Econ is here to kick off 2018. Think of Alexa Well Econ as a smart digital assistant used to determine the economics of drilling and completing a well. It takes into account well costs, the oil price, the initial well production, Arps type well profiles and production decline rates suitable for use in conventional and unconventional wells. Well Econ translates all these parameters into net present val...
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31 Jan 2018 02:21 PM |
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0 Replies and 813 Views
First Step to AI 813 0
Started by Patrick Ng
As 2017 comes to a close and 2018 is just around the corner, why don't we take a stab at AI TensorFlow and Deep Learning emphasize programming and experimentation. Geoscientists can make a real difference in designing how we interact with machine – AI front end. As an example, imagine you can “talk” to Echo back and forth and ask Alexa about a particular basin. We use Amazon Alexa Skills Kit (ASK) and role play with “Basin Bot” as follows: You: “Alexa start Basin Bot” A...
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30 Dec 2017 01:28 AM |
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1 Replies and 805 Views
AAPG Business Meeting Leadership Days Live 805 1
Started by Patrick Ng
Lets make this TIG a go-to place for outside the box thinking and help AAPG plan for the next 100 years. For warm up, post your answers to: Q1: what do we do today to show value Q2: new venture strategy - number of super vs. mini-basins Q3: kind of data that we need to be successful All ideas welcome! Let your creativity rip, fast and furious.
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0 Replies and 908 Views
Model Non-Uniqueness and First Principle 908 0
Started by Patrick Ng
In classic model-based inversion, we learn to live with non-unique solution (i.e., there is more than one model that fit the data using criteria like minimum mean squared error). One safeguard is calibration (e.g., seismic-inverted model properties vs. that from well logs or drill bits) to determine if the resulting model makes sense or not. Likewise, we can have different neural network configurations (e.g., number of hidden layers and neurons within each layer, even different activation fun...
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17 Nov 2017 11:18 AM |