Autoencoders for Seismic Waveforms: Compress, Learn, and Generate
Autoencoders learn compact representations by reconstructing seismic data. This tutorial explains their use...
Utpal Kumar, PhD
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- 144+ Posts
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- Jul 2026 Updated
Caffeinate On and Off Controls for macOS with Alfred and SwiftBar
A compact macOS setup with two Alfred workflows for turning caffeinate on and off, plus SwiftBar for keepin...
Recent posts
Recent technical articles on seismic analytics, scientific computing, numerical modeling, and production data workflows.
Towards multi-resolution analysis with wavelet transform
We will learn the basic concepts of wavelet tranform and multi-resolution analysis starting from the Fourier Transform, and Gabor Transform.
Empirical orthogonal function analysis to inspect the spatial coherency in the geospatial data (codes included)
Empirical Orthogonal Functions analysis decomposes the continuous space-time field into a set of orthogonal spatial patterns along with a set of associated u...
Concatenating daily seismic traces into one miniseed file (codes included)
I concatenate the daily seismic traces for 15 days into one miniseed file for further analysis. Then I obtained the spectrogram of the 15 days seismic data. ...
Computing cross-correlation and spectrogram of two seismic traces (codes included)
Read the seismic traces from the miniseed files and compute the cross-correlation and spectrogram
Principal component analysis to decompose signals and reduce dimensionality (codes included)
Use Principal Component Analysis (via SVD) to decompose a space-time signal into a few dominant modes and reduce its dimensionality, with Python code.
Signal denoising using fourier analysis in python (codes included)
We will learn the basics of Fourier analysis and implement it to remove noise from the synthetic and real signals
Analyzing miniseed seismic data in matlab (codes included)
We will learn how to convert a mseed data file into mat format and then read and analyze it using MATLAB
Transfer learning applied on the unsplash data using alexnet pretrained network (codes included)
Transfer learning using the pre-trained deep learning networks from MATLAB can be easily implemented to achieve fast and impressive results
Getting familiar with pytorch data structures (codes included)
In this introduction to the concepts of Pytorch data structures, we will learn about how to create and reshape tensors using Pytorch and compare it with the ...
How to analyze a huge data file with pandas (codes included)
We learn how to read huge csv file containing time series data by breaking it into chunks and then visualizing it with matplotlib
Pyqt5 application for visualizing ambient sound in real-time (codes included)
A PyQt5 application for retrieving and visualizing sound waveforms in real time. Codes included.
How to start using pandas immediately for earth data analysis (codes included)
This tutorial gives a brief description of scientific computing using Pandas by introducing Series, DataFrame, Pandas common operations, methods, conditional...
Introduction to numpy for scientific computing
This tutorial gives a brief description of scientific computing using numpy by introducing arrays, methods, attributes, random numbers, indexing, broadcastin...
A quick look into the sktime for time-series forecasting (codes included)
I used the sktime library to forecast the airline data using NaiveForecaster, KNeighborsRegressor, Statistical forecasters, and auto ARIMA model.
Towards multi-resolution analysis with wavelet transform
We will learn the basic concepts of wavelet tranform and multi-resolution analysis starting from the Fourier Transform, and Gabor Transform.
Empirical orthogonal function analysis to inspect the spatial coherency in the geospatial data (codes included)
Empirical Orthogonal Functions analysis decomposes the continuous space-time field into a set of orthogonal spatial patterns along with a set of associated u...
Concatenating daily seismic traces into one miniseed file (codes included)
I concatenate the daily seismic traces for 15 days into one miniseed file for further analysis. Then I obtained the spectrogram of the 15 days seismic data. ...
Computing cross-correlation and spectrogram of two seismic traces (codes included)
Read the seismic traces from the miniseed files and compute the cross-correlation and spectrogram
Principal component analysis to decompose signals and reduce dimensionality (codes included)
Use Principal Component Analysis (via SVD) to decompose a space-time signal into a few dominant modes and reduce its dimensionality, with Python code.
Signal denoising using fourier analysis in python (codes included)
We will learn the basics of Fourier analysis and implement it to remove noise from the synthetic and real signals
Analyzing miniseed seismic data in matlab (codes included)
We will learn how to convert a mseed data file into mat format and then read and analyze it using MATLAB
Transfer learning applied on the unsplash data using alexnet pretrained network (codes included)
Transfer learning using the pre-trained deep learning networks from MATLAB can be easily implemented to achieve fast and impressive results
Getting familiar with pytorch data structures (codes included)
In this introduction to the concepts of Pytorch data structures, we will learn about how to create and reshape tensors using Pytorch and compare it with the ...
How to analyze a huge data file with pandas (codes included)
We learn how to read huge csv file containing time series data by breaking it into chunks and then visualizing it with matplotlib
Pyqt5 application for visualizing ambient sound in real-time (codes included)
A PyQt5 application for retrieving and visualizing sound waveforms in real time. Codes included.
How to start using pandas immediately for earth data analysis (codes included)
This tutorial gives a brief description of scientific computing using Pandas by introducing Series, DataFrame, Pandas common operations, methods, conditional...
Introduction to numpy for scientific computing
This tutorial gives a brief description of scientific computing using numpy by introducing arrays, methods, attributes, random numbers, indexing, broadcastin...
A quick look into the sktime for time-series forecasting (codes included)
I used the sktime library to forecast the airline data using NaiveForecaster, KNeighborsRegressor, Statistical forecasters, and auto ARIMA model.