Development of novel computational techniques for phase identification and thermodynamic modeling, and a case study of contact metamorphism in the Triassic Culpeper Basin of Virginia

This dissertation develops computational techniques to aid in efficiently studying petrologic systems that would otherwise be challenging. It then focuses on a case study in which the transition from diagenesis to syn-magmatic heating led to a recrystallization and sulfur mobilization. A Markov-chain Montecarlo-based methodology is developed to allow for the assessment of uncertainty in calculated phase assemblage diagrams. Such phase equilibria are ubiquitous in modern petrology, but uncertainties are rarely considered. Methods are discussed for visualizing and quantifying emergent patterns as phase diagrams are re-calculated with input data modified within permitted uncertainty bounds, and these are implemented in a new code. Results show that uncertainty varies significantly across pressure-temperature space and that in some conditions, estimates of stable mineral assemblage are known with very little confidence. A Machine-Learning (ML) based methodology is developed for automatically identifying unknown phases using Electron-dispersion spectra (EDS) in concert with a Random Forest Classification algorithm. This methodology allows for phase identification that it is insensitive to overfitting and noisy spectra. However, this tool is limited by the amount of reference spectra available in the dataset on which the ML algorithm is trained. The approximately 250 EDS spectra in the current training database must be supplemented to make the tool more widely useful, though it currently has an excellent success rate for correctly identifying various sulfide and oxide minerals. An analysis of paragenesis associated with Central Atlantic Magmatic Province (CAMP) intrusions helps to better constrain the dynamics of magma emplacement, while also providing a method for estimating the amount of sedimentary sulfide-sequestered sulfur mobilized as a result of magnetite formation associated with igneous activity. This method demonstrates that dike emplacement can trigger liberation of sedimentary sulfur with no direct cooling impact on climate.

Name thesis:degree_name

Doctor of Philosophy

Level thesis:degree_level

doctoral

Discipline thesis:degree_discipline

Geosciences

Department dc:contributor.department

Geosciences

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2024

Author dc:creator

• Prouty, Jonathan Michael

Chairs dc:contributor.committeechair

• Gill, Benjamin C.
• Caddick, Mark James

Committee members dc:contributor.committeemember

• Eriksson, Kenneth A.
• Bodnar, Robert J.
• Pollyea, Ryan

• contact metamorphism
• mineral paragenesis
• thermodynamic modeling
• markov-chain montecarlo simulation
• machine learning

Statement dc:rights

• Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International

Licence dc:rights.uri

• http://creativecommons.org/licenses/by-nc-nd/4.0/

Language dc:language.iso

en

Dc Identifier Other

vt_gsexam:41277

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/120911