Python Plotly Tutorial - Creating Well Log Plots - Plotly Graph Objects and Plotly Express

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Data visualization is an import part of working with data and Python has many libraries that allow you to display a wide range of charts. In this video we go over the basics of the Plotly library to display well log data on a simple, but interactive log plot.
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REFERENCES & LIBRARIES
Plotly Library: plotly.com/python/
NLOG Database: www.nlog.nl/
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PYTHON FOR DATA ANALYSIS: Data Wrangling with Pandas, NumPy, and IPython
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FUNDAMENTALS OF PETROPHYSICS
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PETROPHYSICS: Theory and Practice of Measuring Reservoir Rock and Fluid Transport Properties
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WELL LOGGING FOR EARTH SCIENTISTS
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GEOLOGICAL INTERPRETATION OF WELL LOGS
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26 окт 2021

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Комментарии : 22

@heirofsam Год назад

This is Awesome. Thanks man!

@mohammadkeshtkar9655 2 года назад

This video is very fantastic .Thank you Andy

@AndyMcDonald42 2 года назад

You are very welcome

@AndyBrickell 2 года назад

very easy to understand and follow, thanks Andy

@AndyMcDonald42 2 года назад

Glad to hear that :)

@texasfossilguy 2 года назад

this is a good start to making something with functionality. I think showing how to plot multiple curves on one chart would have been good also to make it look like standard charts.

@AndyMcDonald42 2 года назад

Just catching up with comments. Sorry for the late reply. Yes it is possible, but it is a little bit tricky with Plotly compared to using matplotlib. It is something I am planning to look into.

@geraldmogi2937 3 месяца назад

Hello Andy, thanks for the great tutorial. I have a question, do you know how to create/calculate the trend log such as DT Sonic trend line (Normal Compaction Trend)? And how to filter the spike log values (despike)?

@josedavidbastoaguirre2099 2 года назад

you are my hero!!!

@AndyMcDonald42 2 года назад

Thanks 👍

@MerekRoman Год назад

fantastic video would love to see how I can add data to each point i.e. formation, mud viscosity etc

@AndyMcDonald42 Год назад

Great suggestion!

@igorsouza2333 2 года назад

Very nice! Is it possible to select specific parts from df to handle with others pourposes? such as ML.

@AndyMcDonald42 2 года назад

Thanks Igor. Do you mean selecting columns from the dataframe or rows? If so, the answer is yes. :) I would recommend having a look at this article on how to achieve that: datacarpentry.org/python-ecology-lesson/03-index-slice-subset/

@serdarbayramov996 2 года назад

Hi Andy, thanks for this video. Assuming if I have two depth columns, let's say, MD and TVD, how can I have them both shared among all columns. In your example, you showed how we can share only one column of depth, but I wonder if we can share the second y_axis (TVD) just alongside the MD and share among the columns. I attempted this by creating the secondary y_axis, but I couldn't; find a way to share it.

@AndyMcDonald42 2 года назад

Hi Serdar. This is not something I have tested out yet, but I would have thought adding a secondary axis as outlined in the plotly docs would do it: plotly.com/python/multiple-axes/ Have you tried this one?

@porter3277 Год назад

Wowwwwww

@ricardoperez2490 2 года назад

what is your jupyter theme sir?

@AndyMcDonald42 2 года назад

Hi Ricardo, This is the default jupyter theme

@ricardoperez2490 2 года назад

@@AndyMcDonald42 Hello Mr. Interesting, I also use the default theme, but it seems you have coloured some features. Thank you for your reactivity

@user-yh2er3cr9j Месяц назад

Do you know how to set the x-axis range for the log plots to show a little padding? I used fig.update_xaxes(range=[min, max]) but it sets the x-axis range to the same values for all three plots even though I did this for all three subplots separately.

@user-yh2er3cr9j Месяц назад

No worries, I figured it out right after posting. It was standard "user error" on my part. range=[min, max] works as advertised when implemented properly.