When I started learning programming in 2020, my teacher then usually write out his task or goals for his current project down on a sheet of paper and Iโll always wonder โwhy is he doing all this?โ๐,now Iโve gotten to the stage where by I canโt start any project without doing it.
I've been doing some deep research on DFT, FFT & STFT.
I'm making progress, but the entire concept still isn't completely clear to me yet. ๐
I'm sure I'll get the hang of it with more practice.
If you have any insights or resources that helped you, I'd love to hear them.
Day 29 of #90DaysOfCode ๐
Todayโs project: Seismic Signal Filtering
Iโll be using FFT to identify unwanted frequencies and inverse FFT to filter noise from a seismic signal.
Letโs build.
#Python#Geophysics#DataAnalysis
Day 28/90 โ
Built a Seismic Spectrogram Analyzer today.
I moved from FFT to time-frequency analysis, exploring how the frequency content of a seismic signal changes over time.
Another step deeper into seismic signal processing. ๐
#90DaysOfCode#Python#Geophysics#Seismic
Day 27/90 โ Seismic Frequency Analyzer ๐
Used NumPyโs FFT to transform seismic data from the time domain to the frequency domain, identify the dominant frequency, and visualize the frequency spectrum.
#90DaysOfCode#Python#Geophysics
Day 25/90 โ Seismic Data Analyzer
Built a Python seismic data analyzer using Pandas and Matplotlib.
The project checks data quality, calculates amplitude statistics, identifies high-amplitude events, and visualizes seismic amplitude against time.
#Python#90DaysOfCode
Day 24/90 โ Oil & Gas Production Data Analyzer
Used Pandas to analyze daily oil, gas, and water production, calculate key statistics, identify high-production days, and Matplotlib to visualize production trends.
#Python#PythonProgramming#90DaysOfCode
Day 24/90 Oil & Gas Production Data Analyzer
Today, Iโm working with production data using Python, Pandas, and Matplotlib.
The project analyzes oil, gas, and water production, calculates key statistics, identifies high-production days, and visualizes production trends.
#Python
Day 23/90 โ Well Log Quality Control Analyzer
Built a Python QC analyzer using Pandas and Matplotlib to check for missing values, duplicate depths, negative readings, and GR outliers using the IQR method, then visualized the results.
#Python#PythonProgramming#90DaysOfCode
Day 22/90 โWell Log Analyzer
Built a Python well log analyzer using Pandas and Matplotlib. It calculates log statistics, identifies possible shale-rich, cleaner, and high-resistivity intervals, and visualizes Gamma Ray and resistivity against depth.
Applying Python to geophysics.
Day 22/90 โWell Log Analyzer
Built a Python well log analyzer using Pandas and Matplotlib. It calculates log statistics, identifies possible shale-rich, cleaner, and high-resistivity intervals, and visualizes Gamma Ray and resistivity against depth.
Applying Python to geophysics.
Day 22/90
Today, Iโm working on a Well Log Analyzer with Python.
Iโll be using Pandas to analyze Gamma Ray, resistivity, density, and porosity data, then Matplotlib to visualize the logs against depth.
Another step toward combining Python with geophysics.
Day 21/90 โ Geophysics Data Analyzer
Used Pandas to analyze resistivity data, calculate key statistics, filter stations, and find the highest reading. Matplotlib was used to visualize resistivity across stations.
Taking Python closer to real geophysical applications.
#Python
Day 21/90
Today, Iโm building a Geophysical Data Analyzer with Python.
Iโll be using Pandas to analyze survey data and Matplotlib to visualize resistivity measurements.
Taking Python a little closer to geophysics.
#Python#Geophysics#Pandas#Matplotlib#90DaysOfCode