AEG Great Basin Chapter Student Night—Thursday, April 8, 2021 at 6:30 PM, PDT

Association of Environmental and Engineering Geologists (AEG) 

A message from AEG: This is the first joint meeting of the AEG Nevada Student and the AEG Great Basin Chapters presenting the 2021 Student Night. The chapter officers have contributed countless hours to make the meeting webinars possible, and Student Night marks the end of the official meeting season 2020-2021. We wish to thank Professor John Louie, AEG Student Chapter Advisor, for his expert guidance and commitment to the students and both chapters.

Introducing Machine Learning Techniques to Geothermal Exploration in Nevada 

Connor M. Smith, University of Nevada, Reno, M.S. Geophysics Student  

Machine learning techniques are being introduced to the Nevada geothermal play fairway analysis to generate geothermal potential maps to evaluate geothermal resource potential and support the exploration of undiscovered blind geothermal systems in the Great Basin region. Here, we leverage data from the play fairway study and a newly established inventory of training data to support 1) unsupervised modeling to evaluate the influence of certain geological and geophysical features/feature sets and 2) supervised modeling to produce detailed favorability maps. Unsupervised feature evaluation is based on clustering results from principal component analysis and non-negative matrix factorization. Supervised favorability mapping relies on artificial neural network modeling. The results from the joint integration of learning methods produce robust geothermal potential maps and identify unique signatures for geothermal favorability within tectonic domains of the play fairway study area. 

Analysis of the 2016 Deep ReMi Survey in Reno, NV 

Authors: Michelle Scalise, John Louie, Aasha Pancha, Ken Smith 

Michelle Dunn Scalise, University of Nevada, Reno, Ph.D. Geophysics Student 

Advancements in high-performance computing has enabled seismologists to simulate ground motion through structurally complex 3D earth models. As the bandwidth of these computations increases, it is necessary to resolve the 3D velocity models used to simulate ground motion to finer scales. Towards improving the resolution and accuracy of the Reno-Sparks community velocity model, a series of Refraction Microtremor (ReMi) lines have been collected across the urban basin. Originally designed to determine the shear-wave velocity of the upper 100 meters for geotechnical applications, ReMi surveying has been expanded to sample velocity structure to greater depths, by expanding array lengths and the use of 120 sec records during data analysis. Previously, this was adapted to seven NEHRP-sponsored ReMi lines by Optim, mostly 3 km long, that imaged the basin floor at 0.5-1 km depth. The performance and limitations of this “Deep ReMi” technique have not yet been fully explored. In 2016, the longest Deep ReMi survey was conducted, which transected Reno in a 22 km north-south trending line and a 15 km east-west trending line. These data sample deep basin velocity structure, which so far are only approximately constrained by gravity analyses. Current models suggest the Pliocene to Quaternary lakebeds, alluvium, and outwash is underlain by Tertiary volcanic and sedimentary rocks, which are underlain by Mesozoic basement. The 2016 Deep ReMi data help constrain the thickness of these units to build a more robust velocity model, with velocity profiles compared to adjacent Deep ReMi surveys and analyzed in the larger context of the Reno- Sparks community velocity model. These data highlight the limitations of the 2016 survey and inform future survey design. Results provide insight into the feasibility of generating new velocity models with a low-cost passive method practical for urban settings.

Unmanned Aerial Vehicle Mapping and Paleoseismic Investigation of the Bonham Ranch Fault Zone, North of Reno, Nevada 

Conni De Masi, University of Nevada, Reno, Ph.D. Geology Student 

The recent increase in centimeter to sub-centimeter resolution topographic datasets obtained with an Unmanned aerial vehicle (UAV) for structure-from-motion (SFM) models raises the possibility of mapping detailed offset geomorphology and constraining the spatial characteristics of active faults. Here, we applied this method to acquire high-resolution imagery and generate topographic data along the Bonham Ranch fault, which is in the Smoke Creek Desert located north of Reno, Nevada to help identify between fault scarps and lake shorelines. A digital terrain model (DTM) with a resolution of 0.080 m and an orthophoto with a resolution of 0.016 m were generated from these images. 

Our preliminary results indicate that one scarp follows contour lines matching ancient shorelines associated with the Younger Dryas high stand at an elevation of ~1200-1220 m along the western margin of the basin. The sinuosity of the scarp, relatively flat morphology of the upper and lower surfaces, long incision of streams across the upper surface, and lack of vertical deformation within stream cut outcrops, indicate a lacustrine shoreline origin. Two scarps located along the edge of the Smoke Creek playa strike N-S, and are characterized by linear sections, and steep scarps. Several stream exposures across these scarps show vertically offset lacustrine stratigraphy including a white tephra, indicating a tectonic origin. Faulting is also inferred to be the origin of another scarp that cuts across the Younger Dryas shoreline. A scarp profile along this trace indicates that the scarp is up to ~3 m high. Additional morphologic, stratigraphic, and tephra correlation studies are planned and intended to develop constraints on earthquake timing, recurrence, and slip rate for the Bonham Ranch fault zone.

Computing Permeability of Porous Medium: Lattice-Boltzmann Modeling of Air Through Glacial Firn 

Justin Toller, University of Nevada, Reno Ph.D. Geophysics Student 

Three dimensional imaging combined with computational fluid dynamic simulations have greatly improved our ability to study the microstructure and permeability of glacial firn. This is of great importance when determining the gas age–ice age difference, an essential parameter which is necessary in comparing temperature fluctuations with levels of past greenhouse gasses. Since the depth at which pore space closes off is poorly understood, we aim to increase modeling accuracy of gas transfer simulations. By improving the mathematical models of gas transport through firn, we aim to significantly improve our understanding of the gas age–ice age difference, and in doing so, improve our understanding of ice core paleoclimate records. To accomplish this, we aim to combine 3D reconstructions of glacial firn microstructure, obtained through micro-CT scans and model the airflow through the lattice-Boltzmann technique.

Meeting details:

Due to the current pandemic and health safety requirements the in-person meetings are temporarily suspended until restrictions are lifted. To sign up for this Zoom meeting, please contact an AEG officer listed below.

Contact information for the 2020-2021 AEG Great Basin Chapter officers:

CHAIRPERSON: Merrily Graham, 360-606-1838,
VICE CHAIRPERSON: Kelsey Sherrard,
TREASURER: Chris Betts,
SECRETARY: Kathleen Rodrigues,
Individual Sponsors:  Diane Ferris Ferree and Doug & Merrily Graham

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