Locating suitable 'hot rocks', however, is a manual, expensive exercise, and Durrant-Whyte said that NICTA was leading a team of university experts from four states to find better, automated ways to define geothermal targets, using machine learning techniques and advanced data analytics instead of drills.
Geothermal energy comes from the intense heat generated by rocks located several kilometres underground. It is abundant, renewable; and has zero carbon output, which the NICTA chief said made it an ideal energy source.
The ACRE initiative, Data Fusion and Machine Learning for Geothermal Target Exploration and Characterisation, is a two-year, five-million dollar program, and the ACRE Emerging Renewables Program will fund $1.9 million of this total.
'Australia has a wealth of geothermal energy resources, but they are difficult to locate and access,' Durrant-Whyte said. 'We will apply NICTA's considerable expertise in machine learning and big data analytics to create software to address these challenges.'
NICTA will work closely with the School of Information Technologies at the University of Sydney to develop machine learning algorithms, and the Schools of Earth Science at the Australian National University, University of Melbourne and University of Adelaide to apply these methods to the problem of geothermal target characterisation and exploration.
The project teams will also work with ASX-listed geothermal exploration and development companies GeoDynamics and Petratherm, as well as GeoScience Australia and the South Australian Department of Manufacturing, Innovation Trade Resources and Energy, who will provide geothermal sensor data sets and expertise in discovery and characterisation of geothermal targets.
Durrant-Whyte said the project was the first to be funded under the Australian Government's $126 million Emerging Renewables Program, which had been established to provide support for the development of renewable energy and enabling technologies across the innovation chain.