kwinkunks/notebooks

IPython Notebooks

notebooks

IPython Notebooks. View them in NBViewer:

• Battleship — What's the best place to go in Battleship?
• Amplitude horizon — Loading time and amplitude for a seismic horizon from OpendTect
• Fun with logs — Haralick textures for log data
• Spectral wedge — A 3D wedge model for spectral reponses
• Variable wedge — A 3D wedge model with varying properties
• Faster wedges — The sudden realization that I was not exploiting NumPy's fast indexing and vector operations
• Matteo's colourmaps for Matplotlib — Matteo Niccoli's awesome colourmaps
• Fun with spectrograms — Playing with time-frequency representations of signals

See also Agile's notebooks.

notebooks's Issues

Converting polygon coordinates inline/xline/depth slices and image mask from it

Dear Mr. Matt Hall,
Thanks for sharing such enthusiastic notebooks!

I want to try DL for seismic interpretation and now I prepare data for it.
Could you please help me with some question on conversion of x,y coordinates to inline/crossline and consequent turning it mask image?
I assume it is strongly correlated with this notebook.
I have 3d seismic cube data which is currently 3d numpy array with dimensions (inline slice/crossline slice/depth slice). I labelled some polygons on this data using other software (Petrel).
3d seismic cube has CRS metadata and as polygons do.
I can export data from 3d cube in form of 2d image slice either inline, crossline or depth slice. Also I exported polygons in form of shapefile. After browsing through your notebooks I guess may be it is better to try to save and read polygons with ASCII rather than shapefile.
I managed to address them using geopandas library. Shapefile has x,y coordinates grid while that could be converted into belonging some cross section of inline/crossline/depth slice. Cube dimensions are [1436, 624, 151] while shapefile is in x,y coordinates.

Shortly, I want to try conversion as bruges library did. I looked the web and found this formula and tried but I am missing something as this does not correlate with real values.
I have all corresponding CRS data for cube.
My idea is to convert shapefile or ASCII to crossline/inline/depth dimensions, overlay it with data to check and create a mask image from it. Could you please help me how to do it?
I attach images for convenience what I have and what I want.
Example of rendering together inline slice/crossline slice/depth slice and polygon which are of orange color.

Depth slice and same shapefile with polygons in python. Notice, that here polygons are in x,y meters dimensions

Geographic and data information

Example of desired output which here is along crossline

I did test conversion of polygon in OpendTect, but want to do it for all polygon in python. However, this is only visual inspection.
For example,
x = 116003.485084 y = 59713.656120 -> inline 5826 crossline 1244 -> inline = 789 crossline = 225
x = 115394.130714 y = 59377.500480 -> inline 5814 crossline 1269 -> inline = 775 crossline = 250
x = 116655.722511 y = 60282.412712 -> inline 5847 crossline 1217-> inline = 808 crossline = 198

I found this formula , but it did not match with this calculations or I am missing something.

Survey parameters:
min max
X | 105269.86 | 122544.19
Y | 39605.21 | 76201.71

Origin X: 122531.11
Origin Y: 40352.05
End first inline X: 106973.10
End first inline Y: 39618.29
End first crossline X: 120840.95
End first crossline Y: 76188.64
Number of inlines: 1436
Number of crosslines: 624
Inline interval: 25.00
Crossline interval: 25.00
Inline rotation from north: -92.70
CRS is["GK42-13N:Pulkovo 1942, Gauss-Kruger Z13 North Russia".

So could you tell me what is the formula for conversion? I feel that it is easy task, but miss something. Is there dependence on inline rotation angle?

I understand if it is out of scope of your expertise but I would be glad any suggestions on this task.

Thank you. I appreciate your time

Sincerely,
Kirill

Backus deprecation warning

Hi Matt

I was playing with your moving_average function in Backus.

I get this warning:

C:***AppData\Local\Continuum\Anaconda2\lib\site-packages\ipykernel__main__.py:9: DeprecationWarning: using a non-integer number instead of an integer will result in an error in the future

Here's what I am trying to average:

[86.544132822954765, 86.204349283696786, 84.263685498914469, 83.619860049308514, 83.415599316141169, 82.512319865929754, 82.812371366274434, 81.430738171894291, 81.027111369532435, 80.768922397914935, 79.657359574573206, 78.978330807691705, 77.421470161724429, 77.125328486430334, 76.51645503846477, 76.245894367769893, 75.082916798472681, 75.09821675713394, 74.812804540979585, 74.197337409857582, 73.933643720603627, 73.655345392427208, 72.797818855466801, 72.81736273625296, 72.259671462235261]