equinor / segyio-notebooks

Notebooks with examples and demos of segyio

segyio-notebooks

Interactive notebooks with examples and tutorials using the segyio library for reading, manipulating and writing SEG-Y files.

Index

• Overview
• Tutorials
• Data

Overview

In order to ensure that everyone can run the notebooks and produce the expected results, each notebook (or set of notebooks sharing a common Python environment) has to be placed in a subdirectory within the notebooks directory alongside with a requirements.txt and/or environment.yml file to be used to create the same virtualenv and/or condaenv used by the author of the notebook.

Tutorials

Tutorials are organized in subfolders of the notebooks directory as follows:

Basic

• 01 - Basic tutorial - demonstrate how to read two F3 seismic volumes as NumPy arrays; manipulate the similarity to create a discontinuity/fault volume; create a fault mask and display a couple of amplitude time slices with superimposed faults; write the fault volume to SEG-Y file using re-using the headers from the input file.

• 02 - Segy quicklook - demonstrate how to transfer binary and trace headers in pandas dataframes and visualize headers and data with matplotlib

• 03 - Basic Segy editing - demonstrate how to perform manipulations of traces length, both resampling and cutting.

PyLops

• 01 - Seismic inversion with segyio and pylops - demonstrate how to download and read a SEG-Y file, perform colored inversion to a portion of the data and saved the inversion result in a brand new SEG-Y.

Data

Data are organized in subfolders of the data directory. Subfolders should have the same name of the corresponding folders in the notebooks tree. Note that some files may exceed the size allowed by github. In that case it is required to provide a set of instructions in the notebook on how to download the file and it will be assumed that the file will be placed by the user in the correct subdirectory of data.

Basic

• Two seismic volumes in SEGY format from the F3 dataset, offshore Netherlands, licensed CC-BY-SA: a similarity volume, and an amplitude volume (with dip steered median filter smoothing applied)

• A 2D seismic line from the USGS NPRA Seismic Data Archive

PyLops

The seismic cube used in this example is too big to be included in this repo. A set of commands to download the file and place it in the data directory is provided within the notebook.

Run the notebooks interactively in Binder

To open and run notebooks interactively in an executable environment, just click the button below.

segyio-notebooks's Issues

Create base segy faster..

According to segyio-notebooks/03_basic_segy_editing.ipynb -> Cut all traces, I am creating a minimum size empty segy from a "source" segy file with spec.samples = spec.samples[:1].

def create_initial_segy_from_same_survey_segy(segy, initial_segy_filename):
    spec = segyio.tools.metadata(segy)
    spec.samples = spec.samples[:1]
    logger.info("creating initial segy..")
    with segyio.create(initial_segy_filename, spec) as dst:
        dst.text[0] = segy.text[0]
        dst.bin = segy.bin
        dst.bin.update(hns=len(spec.samples))
        dst.header = segy.header
        dst.trace = segy.trace
    logger.info("Initial segy created!")

The thing is that copying dst.header = src.header takes too long as the "source" segy is huge. Is there any way to create faster the minimal base segy?

misleading figure title in inversion notebook

I have been reviewing the 01_seismic_inversion.ipynb notebook and note that the figures have a suptitle "Colored Inversion".

Is this an error / misleading? I understood from the implementation that this is a [linear] inversion based on the statistical wavelet estimate made.

In order to be colored inversion, we would need to use a log spectrum to design an inversion operator and apply that which in not what is happening in this code as far as I can see.

Should the mention of to "Colored Inversion" be removed here?

Estimating the convolutional operator

Many thanks for these useful notebooks!

I have a small question about the seismic inversion notebooks. Following the Lancaster and Whitcombe (2000) article and the TLE tutorials the operator is derived from well logs, in this example is derived directly from the data.

# estimate wavelet spectrum
wav_est_fft = np.mean(np.abs(np.fft.fft(d[..., :500], nfft, axis=-1)), axis=(0, 1))
fwest = np.fft.fftfreq(nfft, d=dt/1000)

Is this would not affect the final results?

Install from environment throws error

Conda Wind 7 64:
I get a German error but it basically says

"?PyWinObject_FromULARGE_INTEGER @@YAPEAU:object@@AEAT_ULARGE_INTEGER@@@z" was not found in pywintypes37.dll"

when installing from the envrironment.yml

Typo in the third basic notebook

The last cell is:
plot_segy(destination)

It should be:
plot_segy(final)

Thanks

Export ndarray to sgy

Thanks so much for your notebooks. i think they're great. However, do you know how to export to sgy. file from an ndarray? I see in your first notebook you export from the already existing .sgy file. I dont have this yet.

Thanks!