Data-2-Decisions

Interested in Stochastic Geothermal Modeling? Sign up for the National Geothermal Academy!

University of Nevada -Reno, June 10-14, 2019 https://gbcge.org/education/

Spatial, statistical learning from RTM & AVA

Determining the Added Value of Surface Distributed Acoustic Sensors in Sparse Geophone Arrays using Transfer Learning in a Convolutional Neural Network
Fault detection from 3D imaging of vertical DAS profile
Classification of Oil Production Using Stochastic AVA Inversion via Machine Learning

Reservoir modeling with geostatistics & machine learning

Machine-learning-based methods for estimation and stochastic simulation

Visualizations & Value of Information

Our Applications

Oil & Gas Unconventional & Offshore
Geothermal exploration
Groundwater

Recent Activities

Congratulations BaNE & Adam!

2nd Place for Geothermal Visualization Competition

https://www.energy.gov/eere/articles/and-winners-2019-geothermal-student-competition-are

PAPERS & Conference Proceedings

Luo, B., Trainor-Guitton, W., et al., “Preliminary Analysis of Distributed Acoustic Sensing at the Kafadar Commons Geophysical Laboratory,” Seismological Society of America, Seattle, Washington on 23-26 April 2019
Trainor-Guitton, W., Guitton, A., Jreij, S., Powers, H., and Sullivan, B., 2019, 3D Imaging of Geothermal Faults from a Vertical DAS: Energies, v. 12, doi: 10.3390/en12071401.
Sullivan, C.B. and Trainor-Guitton, W. (2018), Illuminating the Value of Geophysical Imaging through Visualization and Virtual Reality, Abstract presentation (No. 141) at the 31st annual Symposium on the Application of Geophysics to Engineering and Environmental Problems, Nashville, TN, 25-29 Mar., https://doi.org/10.1190/SAGEEP.31
Sullivan, C.B. and Trainor-Guitton, W. (2018), PVGeo: an open-source Python package for geoscientific visualization in VTK and ParaView, Abstract (NS53A-0542) presented at 2018 AGU Fall Meeting, Washington, D.C., 10-14 Dec., Earth and Space Science Open Archive. https://doi.org/10.1002/essoar.10500751.1
Grasmick*, J., Mooney, M., and Trainor-Guitton, W. (2018). Incorporating Geological and Geotechnical Spatial Variability into TBM and Ground Settlement Risk Assessment. North American Tunneling 2018 Proceedings.
Boyd*, D.L., G. Walton, and W. Trainor-Guitton. 2018. Improving geological models through statistical integration of borehole data and geologist?s cross-sections. In 52nd U.S. Rock Mechanics Geomechanics Symposium, 17-20 June 2018, Seattle, Washington.
Jreij*, SF, Trainor-Guitton WJ, SimmonsJL. Determining the added value of surface distributed acoustic sensors in sparse geo-phone arrays using transfer learning with a convolutional neural network. 2018 SEG International Exposition and Annual Meeting, SEG 2018. 2019.
Powers*,H., Trainor-Guitton, W., and Hoversten, G.M., 2018. Classification of total oil production of wells in seam life of field from stochastic AVA inversion attributes via machine learning: in SEG Technical Program Expanded Abstracts 2018, 2131-2135.
Dhara*, A., Trainor-Guitton, W., and Tura, A., 2018, Machine learning based methods for estimation and stochastic simulation, in SEG 2018 Annual Meeting, Expanded Abstracts.
Trainor-Guitton, W., Jreij, S., Guitton, A., and Simmons, J., 2018, Fault Classification from 3D Imaging of a Vertical DAS Profile, in SEG 2018 Annual Meeting, Expanded Abstracts.

Introduction to Data Science Course @ Kyushu University: Dec 10-13, 2019