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Edinburgh Imaging Project

The Edinburgh Imaging Project (EIP) develops novel methods for imaging and monitoring of the Earth's subsurface, using methods from inverse theory, migration, tomography and data science
 
Edinburgh Imaging Project

Edinburgh Imaging Project

The Edinburgh Imaging Project (EIP) develops novel methods for imaging and monitoring of the Earth's subsurface, using methods from inverse theory, migration, tomography and data science

Research

The EIP has published much over the past 15 years. These links provide an overview of our publications, and some codes that we developed. Publications Codes Nov 20, 2019

People

These are the scientists involved in the EIP, starting with team leader Prof. Andrew Curtis. Prof. Andrew Curtis Andrew Curtis is the Professor of Mathematical Geoscience at the University of Edinburgh and leads the EIP....

Publications

On this page, we list our publications sorted by year. If you are prompted for a DataSync password, the password is ‘EIP’. 2023 Xin Zhang, Angus Lomas, Muhong Zhou, York Zheng and Andrew Curtis, 2023....

Public Codes

Check out our GitHub page for the newest codes: Edinburgh Imaging Project. In addition, the following codes are publicly available in the form of zip packages. Our fileserver requires us to have a password on...

 

The Edinburgh Imaging Project (EIP) explores the exciting fields of imaging and monitoring of the Earth’s subsurface, principally for applications within industry. EIP often uses methods from inverse theory, migration, tomography and data science.

Over the past decade, EIP has created many new seismic, seismological, electromagnetic, and ambient noise imaging methods. EIP explores and creates these advances, transfers them to sponsors organisations, publicises them to interested communities, and trains excellent graduate students.

The fundamentals of imaging methods span a broad range of disciplines, requiring expertise in mathematics, physics, wave theory, signal processing, exploration geophysics, earthquake seismology, ambient noise theory, inverse theory, machine learning, and numerical and experimental modelling and imaging. EIP therefore includes researchers from a wide variety of international backgrounds, and Ph.D. and postdoctoral positions are often available for the brightest students and researchers in the above areas. All research is fully funded by a consortium of industrial companies, currently:
Total and BP.

Restricted Content

Our latest and most exciting research may not be ready for publication yet. Our sponsors have early access via the links below.

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