The C-Team
The Computing Team (C-Team), under the direction of Dr. Jeffrey Shragge, focuses on theory and applications of computational seismology, including 3D seismic wave propagation, imaging and inversion, as well as aspects of time-lapse (4D) monitoring. Our research leverages modern high-performance computing (HPC) architectures (e.g., multi-core CPUs and GPUs) to develop, implement and validate computationally efficient solutions to large-scale (>1 billion grid points) 3D geophysical problems.
Our Team
Adesh Pandey
PhD Student
Madeleine Pels
PhD Student
Daniel Davis
PhD Student
Cullen Young
PhD Student
The Problems We Solve
How can we improve the quality of anisotropic elastic subsurface models using extended microseismic source images?
Accurately estimating event locations is of significant importance in microseismic investigations because this information greatly contributes to the overall success of hydraulic fracturing monitoring programs. Full-wavefield, time-reverse imaging (TRI) offers an effective methodology for locating surface-recorded microseismic events. To be most beneficial in microseismic monitoring programs, though, the TRI procedure requires using accurate subsurface models that account for anisotropic elastic media effects. We developed a novel microseismic extended PS energy imaging condition that exhibits improved sensitivity to anisotropic elastic model errors compared to its existing counterparts. The sensitivity information in extended PS energy images can be successfully used as a quality control tool to update subsurface models. Therefore, we also developed a microseismic, image-domain elastic wavefield inversion methodology to obtain accurate elastic models, which can significantly improve the focusing of imaged events, leading to enhanced fluid-injection programs.
Microseismic imaging, inversion, and monitoring
Full-wavefield, time-reverse imaging
Figure 1. 3D vertical P-wave velocity model from the Barrett unconventional orthorhombic model. Microseismic event is at the intersection of the blue lines and is recorded at a sparse and non-uniformly distributed surface receiver array.
Figure 2. 3D elastic zero-lag PS energy image. The intersecting cross-hair lines denote the true source location, which corresponds to the maximum image focus.
Figure 3. 3D space-lag extended PS energy image computed at the maximum amplitude point of the zero-lag image, which corresponds to the true source location. The energy is well focused at zero lag due to the correct model used in the elastic TRI process.
The Techniques and Tools We Use
Seismic Anisotropy
Elastic and acoustic reverse-time migration (RTM)
Microseismic imaging, inversion, and monitoring
Velocity analysis and model-building
Elastic and acoustic full-waveform inversion (FWI)
Distributed acoustic sensing
Machine learning
3D/4D elastic anisotropic modeling
Time-lapse seismic including FWI
Recent Honors and Awards
2021
2019
Aaron Girard
Tugrul Konuk
Honorable Mention-Best Paper, SEG
Top 25 Papers at SEG
What is the C-Team?
Join the C-Team
Mention the C-Team and CWP in your statement of interest when you apply for graduate school.