Students

Joe Capriotti
PhD Candidate
jcapriot@mines.edu

Joe is developing coupled inversion methods to find reservoir parameters from time-lapse gravity data and applying clustering inversion to recover anisotropic parameters using time-lapse gravity and electrical resistivity data sets.  He has also developed a joint inversion of gravity and gravity gradient data.

Liz Maag-Capriotti
PhD Candidate
emaag@mines.edu

Liz is applying the guided fuzzy c-means clustering technique to discrete-valued inversions of gravity, gravity gradient, and induced polarization data sets. She is also developing a gravity inversion using the finite element method to solve the gravity PDE.

Andy McAliley
PhD Candidate
wmcalile@mines.edu

Andy is developing tools to incorporate structural and petrophysical information into geophysical inversion using machine learning techniques. He is applying these tools to electromagnetic and thermal geophysical data.

Andréa Darrh
PhD Student
adarrh@mymail.mines.edu

Andréa is interested in modeling anisotropic conductivity with electrical and electromagnetic methods for use in geologic interpretation. She is also interested in the integration of multiple geophysical data sets in solid earth geophysics.

Zhuo Liu
MSc Student
zhuoliu@mines.edu

Zhuo is modeling anisotropy in magnetic susceptibility for potential application to mineral exploration. He is also interested in quantitative interpretation of multiple geophysical data sets for use in the mining industry.

Seungwook Charlie Shin
Post-Doctoral Fellow
seungwookshin@mines.edu

Seungwook is investigating supervised machine learning algorithms and associated efficient and stable computational tools. He is applying these tools to lithology classification from multiple geophysical data.

Zhipeng Qi
Visiting Scholar
zqi@mines.edu

Zhipeng is developing transient electromagnetic pseudo wave field imaging technology to extract additional structural information. He is also focused on transient electromagnetic instrumentation, transmitting antenna design, and related interpretation algorithm development.

Kaijun Xu
Visiting Scholar
xukaijun@mines.edu

Kaijun is developing the joint interpretation of magnetic and MT data in exploration for volcanic units. He is applying magnetic inversion with structural constraints from MT to carry out the case study.