The goal of the GNG research programme is to delineate potential supercritical resources in the Taupō Volcanic Zone (TVZ) in order to find the most prospective location(s) for accessing supercritical fluids. But, how do we identify a drilling target(s) when there are still substantive unknowns?
Geothermal systems vary in their characteristics (e.g. geology, temperature, depth, chemical profile), and it is challenging to ‘see’ beneath the surface and measure properties of the deep underground. To understand a geothermal system and assess its energy potential requires geoscientific measurement and interpretive techniques, exploratory drilling and testing, and mathematical modelling.
Since no single science discipline can provide ‘The Answer’ on where to drill, our research is interdisciplinary, combining geophysics, geology, petrology, geochemistry, numerical modelling, water-rock interaction, deep fluid chemistry and more. These data are helping us to understand the subsurface conditions, and what will happen in the future if the fluids are withdrawn from deep underground and returned.
But selecting a target for drilling to supercritical conditions is more than picking the most promising according to the science and resource knowledge. Other considerations include landowner support, ease of consenting/permitting, neighbouring land uses, public and cultural acceptance, access to infrastructure, and who is willing to invest in the exploration drilling project.
This abundance of constraints (scientific and otherwise) is not a bad thing. We need sound criteria to help us narrow the search, and to provide a means of ranking possible locations. The best site scientifically might be in a protected geothermal area where the regulatory regime prevents exploration and development, or in a location where resource access is contested, or the site is too far from existing infrastructure to attract investment.
What we do know is that there is great urgency, globally and nationally, to transition to low-carbon energy options, and decisions need to be made, even with time- and data-limitations.