Geophysical Imaging

eophysical imaging is used to see beneath the Earth’s surface. A variety of techniques are studied at ERL that are sensitive to different physical properties (e.g. electrical conductivity or density). Images are made to map the extent of these quantities in the subsurface. These images are then interpreted to estimate the location and quantity of different materials (e.g. oil or water) in the subsurface. ERL scientists work on several different aspects of geophysical imaging, working to create images in increasingly complicated geological environments. For oil exploration, this involves using increasingly large seismic data sets and fast algorithms for their processing and interpretation. For environmental problems or geothermal energy this involves extracting more information from limited data sets and using that information to its fullest extent.

ERL is active in many areas of modern depth imaging, from data processing to high performance computational physics.

SEISMIC: A topic of central interest is inversion from waves that reflect several times before being recorded. While it is standard to ignore or suppress multiple scattering phenomena, new research is now making it possible to model these waves in an explicit fashion, and fully integrate their effect in the imaging process.

Another outstanding challenge is that of mapping the low-frequency components of the background physical parameters. This old question is receiving new answers via optimization methods that seek to “convexify” the essential nonlinearities of wave scattering.

The past few years have seen a major advance in seismology: an understanding of the mechanisms of wave focusing in random environments. This discovery has led to much activity in passive (sourceless) imaging, where original methods map surface velocities from completely noisy signals.

NON-SEISMIC: ERL scientists are leaders in the use of deformation monitoring to understand changes in reservoir properties; monitoring subsidence from orbiting satellites has high potential to greatly reduce the cost of this sort of monitoring.

As the world’s needs for water increase, geophysical imaging, in particular electrical methods, are becoming more important to find and monitor clean water supplies. As these data are generally sparser than typical exploration seismic data, robust ways of imaging are even more important in this context.
There are many more questions of current interest in the imaging team at ERL, such as dimensionality reduction methods, parallel and GPU computing, and coupling of different modalities.

Geophysical imaging is central to many aspects of subsurface science. A seismic image of the subsurface is the typical starting point for reservoir monitoring, CO2 sequestration, and oil exploration. An image of changes in electrical properties in the near-surface is the typical starting point for most environmental geophysics problems. An image of changes in position, generally made with GPS or INSAR, gives key information for monitoring stress changes and understanding the geomechanics of a region; such understanding is important for monitoring CO2 sequestration sites and changes in active petroleum reservoirs. Combining images with information on fluid flow, stress changes, and borehole data allows us to best understand the structures and fluid distributions in the subsurface.