Hi, I'm Amir
I'm  Programmer. Seismologist. Researcher. Data scientist. Pythonista.

About Me

A Computational Seismologist & Machine Learning Practitioner

Hello! I'm Amir, a PhD candidate in Earth Science studying Geophysics (seismology) and based in Quebec City, Canada. For my master's degree, I used machine learning for detection of channels and faults in seismic data. In addition to my thesis work, I used clustering techniques for facies analysis in oilfields in the south of Iran. Currently, I work on full-waveform inversion (FWI) to apply it as a time-lapse tool (TL-FWI). TL-FWI is a powerful tool to monitor changes under the surface that could occur as a result of extraction from, or injection to, reservoirs. Due to the importance of monitoring the saturation of injected CO2 for carbon capture and storage (CCS), TL-FWI has an important contribution to the environment. In addition to TL-FWI, our application can be a useful tool for other sections of seismology.

Research Interests

Currently, I'm focusing on full-waveform inversion (FWI) and its applications for monitoring the subsurface. Having experience in using machine learning techniques for facies analysis and feature detection in seismic data, I'm also interested in using deep learning for velocity analysis and fluid monitoring in the subsurface. Here are short summaries of the projects that I've worked on.