My research focuses on the study of heat and fluids deep within the Earth's crust and upper mantle.  Much of the work is large scale, looking at continental to global scale patterns of heat flow and crustal radioactivity, or regional utilizing electromagnetic soundings and laboratory measurements to understand crustal hydration.  Lately, my work has drifted into global geochemistry and data analytics, specifically looking at temporal evolution of granites and the sources of variability in radiogenic heat production.

For more information, you can check out my personal website: http://dhasterok.wixsite.com/world-of-wonder/

Several projects have required the compilation of large datasets including the Global Heat Flow Database (http://www.heatflow.org) and a global geochemical database (https://doi.org/10.5281/zenodo.2592822).  I also have been releasing some of the codes that I used to analyze and process the data on GitHub (https://github.com/dhasterok), which includes links to codes for global geochemistry, protolith prediction, and global plate and province models.

Here's a video about the Global Geochemical Database that my group has compiled.

Honours projects

Which came first: chemical stratification or crustal thickness?

Subduction related volcanic arcs are among the most important tectonic settings for the chemical stratification and bulk composition of the continental lithosphere.  Within volcanic arcs, most element concentrations appear to correlate with crustal thickness, dominated by the processes of fractional crystallization and assimilation.  These relationships have led to new tools for estimating crustal thickness in extinct arcs.  However, many important aspects that potentially affect the accuracy of these relationships are not well characterized.  For example, the relationship between volcanics—from which these relations have been developed—and deeper plutonic rocks may respond differently to differentiation within the crustal column.  Many shallow volcanics have been eroded in extinct arc terranes, variably exposing the plutonic rocks at different depths.  Since crustal thickness estimates are currently derived from these deeper exposures, it is crucial that we improve our understanding of chemical differentiation within arcs.  Your task will be to explore the chemical stratification in several obliquely exposed volcanic arc systems using a global geochemical database.  You will produce geobarometric models to place geochemical analyses in a vertical context and then compare the behaviour across several arcs as a function of depth.  If we are lucky, we’ll be able to answer the question posed by this project.

A background in geochemistry, tectonics, and/or data analytics would be useful for this project.

Depths of Erosion

Geophysical data are commonly used to estimate rock compositions within the crust, which works in a general mafic versus felsic sense.  But knowing whether rocks are igneous or sedimentary is also required to develop reliable models of crustal construction and evolution.  Furthermore, trace element distributions are characteristically different for igneous and sedimentary systems.  As shown in the figure below, previous geologic models characterize most of the crust below the surface as metamorphic…a basically useless designation.

Your task is three-fold:

1. construct a multidimensional map of rock type, age, and maximum depth of burial;
2. develop a model for the proportion of igneous and sedimentary protoliths within the crust; and 
3. use your model to produce a model of heat production variations with depth within the crust.

Your results will be used to help develop more accurate models of lithospheric composition and improve estimates of crustal temperatures.  And as part of this study, you will gain experience with GIS software and its application to large datasets (big data).  Learn to do basic computer coding using Matlab or Python to statistically analyze the world’s largest academic geochemical dataset.

A background in tectonics, metamorphic petrology, and/or data analytics would be helpful for this project.

The Impact of Fluid Flow on Crustal Radioactivity – pushing heat around during tectonic reworking

Crustal radioactivity affects crustal temperatures and thus has a potential influence on a wide range of crustal and lithospheric processes including melting, magmatism, and strength.  High crustal radioactivity may also be indicators of possible mineralization.  Models of crustal radioactivity imply that it decreases with depth, more so than one would expect from a changing bulk composition, but why?  Possible explanations include fractionation and crystallization processes, assimilation of enriched crustal material during ascent, and fluid redistribution.

The aim of the project is to explore the potential for fluid redistribution.  Fluids, depending upon their composition, have the potential to mobilize heat producing elements (K, Th, and U) and redistribute them to different locations or stratigraphic depths.  In this project, you will study the magnitude of the redistribution on several crustal-scale shear zones in Australia by collecting in-situ radioactivity and major element chemistry profiles across these shear zones.  The project results will improve regional and global modelling of heat production distribution and temperature models of the crust and lithosphere that has undergone tectonic reworking.

A background in igneous/metamorphic petrology and/or geochemistry would be helpful for this project.

Compositional controls on physical properties: new constraints from laboratory measurements

One of the limitations to developing geophysical models of the crust is minimal control on physical property determinations on rocks directly relevant to the subsurface.  As part of this project you will be measuring the physical properties on samples with known compositions from the South Australian drill core library.  The goal of this project is to develop a set of robust, compositionally based models to predict a number of physical properties including, density, seismic velocity, thermal conductivity, and heat production.  With such models, it will be possible to estimate the distribution of physical properties in the subsurface, providing a priori constraints for gravity, seismic and heat flow investigations.  Your model may even be able to predict the conductivity of minerals within the rocks themselves.

You will gain experience with petrophysical measurement techniques.  You will develop a sampling strategy that adequately samples a wide array of rock compositions among both igneous and sedimentary rocks.  To analyse the data you will learn basic computer programming for data analysis and data management.

A background in geology, geophysics, and/or physics would be helpful for this project.