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2013

Geothermal Data Portal

Final Report to ARENA

Lachlan McCalman, Olena Velychko and

Marie Connett

National ICT Australia

Geothermal Data Portal

Report on the Subterranean Data Portal created for the Measure

“Data Fusion and Machine Learning for Geothermal Target

Exploration and Measurement”

(Contract Number 2410, 2012-2014)

Lachlan McCalman, Olena Velychko, and Marie Connett*, National ICT Australia Limited

Address for correspondence: [email protected]

This report

1

comprises additional data brought into the portal for the purposes of the Measure, as of the date 30. November 2013, subsequent to completion of the milestone as of 7. September 2012.

Executive Summary

:

For the purposes of supporting data fusion and machine learning for geothermal target exploration and measurement, we developed a data portal using combined datasets obtained from Geoscience Australia, DMITRE, Geological Survey of

Victoria, University of Melbourne, University of Adelaide, Australian National

University and private company collaborators including Geodynamics, Petratherm and Hot Rock Ltd. We developed a portal system that could provide all available data from any sensors given a particular region in a single, machine-readable format suitable for the inference software.

Traditionally, datasets are stored in a variety of text-based and binary formats depending on the type of sensor (ArcGIS, ERS, SEG-Y etc.), in different projections and with idiosyncratic labeling systems. We saw the need for an open data format that would be flexible enough to allow different kinds of sensor or simulation data to be stored together and represented in a self-describing way. The format should be universal enough that a variety of open-source tools for reading it already existed.

Following a period of testing we determined that the HDF5 data format

( www.hdfgroup.org

) meets all these requirements and was chosen as the portal’s output.

The file importers we developed also add metadata attributes such as the bounding box, sensor type, creation date, and description to a database, used by the back end to facilitate queries and requests.

Communication with the portal occurs via a simple HTTP-based interface. Software can easily implement control of the portal directly, and we have also written a web front end that allows the user to interact with a graphical user interface of tick boxes

1 Copyright © 2014 National ICT Australia Limited (NICTA) (ABN: 62 102 206 173). With the exception of any material protected by a trademark, and where otherwise noted, this work is licensed under a Creative Commons Attribution-Non Commercial 3.0 Australia License .

Data Fusion & Machine Learning for Geothermal Target Exploration & Characterisation Page 2

Geothermal Data Portal and map-based boundaries to select, visualise, and download available data-sets in a single HDF5 file, ready for input into our data fusion software or for viewing by others including the project participants and government policymakers.

Even though we anticipate our inversion software directly interfacing with the portal system, we developed a userfriendly map-based web interface to facilitate members of the geothermal community exploring the available data.

The interface has standard functionality such as an interactive map that can be panned and zoomed with the mouse, or geo-referencing can be done by insertion of latitude and longitude coordinates. Geo-referenced visualisations of the datasets and their bonding boxes are automatically overlaid when selected. Regions of interest can be chosen on the map either by clicking and dragging with the mouse or entering co-ordinates directly. Checkboxes for each available dataset allow the user to determine the contents of the output file, which is collated on the server when the user hits ‘download’. See Figure at left for a screen-shot of the portal web interface, currently usable at geoportal.research.nicta.com.au

; in future we envision that this may move to be served by

Geoscience Australia, one of the collaborators in the measure, and with the agreement of Geoscience

Australia we have developed appropriate software to serve the data for the use of our inference engine within the Virtual Geophysics Laboratory, making use of national computing infrastructure and cloud computing resources.

The portal back end connects to this database and uses it to serve requests for a collection of datasets in a particular region. The communication protocol is an HTTPbased REST interface, a stateless protocol using URL requests easily implemented in a variety of languages. When a request is received by the back end, it opens the associated HDF5 files of all requested datasets, crops them to the region of interest

(which may be delineated by latitude and longitude or political entities such as states, see figure below), then re-writes a new HDF5 file that contains all these data of the different types in a single file. That output file is then sent to the user as a download.

Data acquisition and conversion into the portal system is ongoing as new datasets become available through our collaborators that are useful for carrying out the measure. Datasets with existing support include all public gravity station data, surface geology and fault lines from all states, and high-resolution gridded magnetics, topographics and radiation. Additional development has recently enabled

Data Fusion & Machine Learning for Geothermal Target Exploration & Characterisation Page 3

Geothermal Data Portal the upload and download of complete seismic lines.

Introduction

:

The delineation and description of underground bodies and characteristics proceeds by expert extrapolation from locations where rock property data can be collected directly, via emergent structures, excavations, drillholes and the like, combined with data from a variety of sensors that measure, often indirectly, seismic movements and properties such as small gravity and magenetic variations. Sensors are often not placed in regular formations and data often are not collected at regular frequencies, contributing to the need to apply sophisticated mathematical techniques to interpret the data.

Traditionally, geophysical datasets are stored in a variety of text-based and binary formats depending on the type of sensor (ArcGIS, ERS, SEG-Y etc.), in different projections and with idiosyncratic labeling systems.

Thus, we saw the need for an open data format that would be flexible enough to allow different kinds of sensor or simulation data to be stored together and represented in a self-describing way. This would facilitate the combined use of different types of data describing underground bodies and characteristics in more sophisticated statistical analysis, taking into account the uncertainties associated with each sensor type and data point.

Data assimilation has required a high level of collaboration with the Measure participants in industry and government relating to data management, and relies on acquiring access to appropriate geophysical datasets. The first step of our data acquisition was to establish, with the geosciences experts participating in the project, the sensor modalities and data types that would and could be relevant to the inference problem. We then requested each collaborator to enumerate which datasets fitting into these categories they possessed. We then travelled to all the partners and collected a representative sample of the datasets from this master list. Gravity magnetics and drill-hole sampling of density and susceptibility were our initial research targets, and we acquired a significant amount of data in these modalities, including 2.5 million ground-station gravity observations from Geoscience

Australia, all of the PEPS-SA petrophysical drill-hole database, and two large gravity surveys in the Cooper Basin in SA, and Magdela in Victoria, which we are using in combination with drillhole measurements to analyse the performance of our algorithms.

We subsequently acquired and converted additional data types including magnetics,

2- and 3-D seismic lines, magnetotellurics, depth-to-basement models, various drillhole measurements, rock properties characteristics, and micro-seismic data relevant to the geothermal exploration problem in Australia.

Data portal front end

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Geothermal Data Portal

We developed a portal system that could provide all available data, from any sensors, given a particular region, in a single, machine-readable format suitable for the inference software. This portal is a web-based system that stores datasets and allows users to download data from multiple sensors in a single file cropped to the desired region.

The portal that we developed uses

NICTA’s Subspace

TM

software, developed within the Cesium core geospatial browser functionality and using a 3D model of the Earth to display datasets. This works in a modern browser such as Google Chrome® or

Firefox®. It is a particular feature of the software that no additional programs or plugins are needed to run it.

In the user interface “front page” (see Figure above), on the right hand side, there is a list of all datasets stored in the portal. Choosing a particular dataset shows its bounding box on the model. It is possible to select several datasets simultaneously by ticking multiple boxes as shown.

It is also possible to download data for a particular region rather than the full dataset.

The Select tool can be used to specify the region. After selection has been made using one or more boxes or via coordinates, clicking the Download button will start downloading data from all the selected datasets cropped to the desired region. The data will come up as a single HDF5 file (with all the licensing information associated with the data specifying its allowed use also incorporated in the same file).

GeoServer Dataset Format

The GeoServer accepts datasets in the form of HDF5 data files, and returns datasets in JSON or HDF5 format. The output format resembles the input format as closely as possible.

The data management system and data format were developed in consultation with our collaborators, particularly with DMITRE and Geoscience Australia. For input we chose to standardise on the open, self-describing file format HDF5, which is both simple and efficient to read and write with a variety of languages and applications, and is flexible enough to describe any of the data types we will use in our inference algorithms. We demonstrated the portal system based on this format to our partners and received positive feedback. In fact, since we made that choice, Geoscience

Australia elected to use a very similar format to deliver Landsat data.

HDF5 itself is a binary hierarchical, filesystem-like format for homogeneous and heterogeneous arrays and tables. It contains an internal type system, a robust API implemented in a variety of languages including C, Python, R, Java and MATLAB.

Internally, arrays are represented contiguously, whilst table data is indexed using B-

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Geothermal Data Portal trees. When serving data in the form of HDF5 files, the tables and arrays are included in the output file just as they were in the input files, though the paths to those dataset within the output file may differ to the path the origin dataset was located at in the input file. Hence the format of the datasets is consistent across the input and output files.

The structure of the datasets in which the GeoServer has taken input, and in which any further input is expected (from the Measure Participants, any future Participants joining the Measure, and any other source wanting to contribute data), is dependent on the type of input datasets (Points, Polygons, Lines, Site Data or Geocodes), which are described in detail below.

Points

A point cloud dataset comprises a table named "points", with 2 mandatory columns

('latitude' and 'longitude'), and an arbitrary number of additional data columns, defined at the discretion of the user(s).

Lines/Polygon Structure

Each Line/Polygon dataset consists of a single table and two arrays, as follows:

• The table is named 'records' and holds one row per group of polygons/lines having common properties. Columns are an arbitrary number of properties for that group. The only mandatory columns are 'bbox' (which stores the bounding rectangle for that group) and 'shapetype' (which is an integer of value “3” for

“line”, value “5” for “polygon”).

• The first array is named 'vertices' and is an ordered list of all the vertices in the poly/line group, made up of (longitude, latitude) pairs. Vertices next to each other are “connected” if they're in the same ‘part’ (see below).

• The second array is named 'parts' and contains integer indices into the

'vertices' array, and is used to designate the start points for each part of the poly/line group.

The row count for the 'records' table must match the number of parts in the 'vertices' array and the length of the 'parts' array.

Site Data

Site Data is similar to point cloud data, but is adapted for the case when the user has multiple datasets that refer to the same points but wants to be able to query them as separate datasets, without wanting to duplicate the latitude and longitude data or rely on the latitude and longitude data for each dataset being duplicated correctly. It

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Geothermal Data Portal works in conjunction with the GeoCode datatype described in the next section.

A dataset of Site Data consists of a single table, named "site_data", containing only one mandatory column, 'site_id', and an arbitrary number of data columns defined at the discretion of the user(s).

GeoCodes

GeoCodes are used in conjunction with Site Data to provide multiple datasets that refer to the same point cloud and that can be queried independently. Geocodes essentially map latitude and longitude to site IDs that are unique identifiers for each point in the cloud. They can be strings or integers or whatever comparable data type the user desires, as long as they match what is in the 'site_id' column of the Site

Data datasets to which they apply.

GeoCode data are provided with a single table, named "geocodes", containing three mandatory columns, 'latitude' 'longitude' and 'site_id', and no other columns.

Attributes

The “group node” at which each dataset is contained in the HDF5 file must have two attributes that pertain to the dataset:

• Bounding Box (min/max latitude/longitude/depth)

• Data type (point cloud, lines, polygons, site data, geocodes)

Time series data can be stored in the HDF5 file, and time series data is distinguished from static geospatial data by the presence or absence of the following three attributes:

• Time Field - The name of the column in the dataset that defines the passage of time for the time series.

• Min Time - The earliest date/time found in the time series

• Max Time - The latest date/time found in the time series

Also, any additional metadata that the user wishes to attach to datasets can be attached as attributes to the user’s “group node” containing the dataset, and such additional metadata will be included in the output HDF5 file. For example, we have attached metadata regarding the licensing and confidentiality of the data as desired by some Measure participants.

Datum and Projection Information

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Geothermal Data Portal

By default, the data sets are assumed to be in the GDA94 coordinate system. This can be overridden on a per-dataset basis by specifying a 'coordinate_system' attribute on the group node.

Input Structure

A dataset to the GeoServer is defined by the HDF5 file that contains it, and the path to the dataset in that HDF5 file. A user may upload, to the GeoServer, an HDF5 file containing multiple datasets. The paths inside an HDF5 file to the individual datasets contained in that HDF5 file are entirely at user discretion, and when adding a dataset to the server, the user specifies the HDF5 file (or uploads it if it is a new HDF5 file) and the path inside that HDF5 that points to the dataset.

Output Structure

When compiling a data package for download, the user specifies the “bounding condition” (in the form of a geospatial bounding box and time bounds if applicable) and the datasets for inclusion. For each dataset to be included in the download, the user must specify a data group (e.g. 'data_group') and a name (e.g. 'dataset_name').

The GeoServer will then crop the desired dataset and add it to the output HDF5 file at the path

‘/data_group/dataset_name/’ (this example assumes the previous example values for the data group and name) and import all the attributes for the dataset from the input HDF5 file to the group node (at the above path).

Data Portal software testing

During development we have demonstrated the portal system to the geothermal companies and the state and federal government participants. Additionally, we took up specific feedback from all these participants at an advisory meeting on 25.

October 2012 at which representatives of all these participants were present in person or by teleconference. Using that feedback we put in motion upgrades to the portal and the Subspace

TM

browser softweare, so that it can be used for all kinds of geospatial data within an ordinary browser without any specialized plug-in software necessary (unlike most 3D software and geospatial software with 3D capabilities), so that it can be used at desktop by all participants.

Some of the additional feedback that was given at that advisory meeting, that influenced the design of the portal, was as follows: a) The companies desired an authentication system to allow non-public datasets to be made available to a subset of portal users. We agreed that this may be attractive to more industry participants, and found a way to implement it relatively straightforwardly within the standard file structure, so this has been implemented in

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Geothermal Data Portal the new portal back end. b) Many of the scientists present thought it would be good to also display results of our inversions directly in the portal. As will be described in a subsequent report, we have been adding this functionality, which is beyond the scope of the original description but was seen as a way of making the portal even more useful to the participants. c) Ability to upload data to the portal over the web interface -- we have also been implementing this because it is viewed as generally useful for all end users and uses, making it straightforward to bring in more data.

In addition to these specific points, the general feedback from the collaborators was quite positive. The main utility of the portal relates to its ability to feed data to our multi-sensor fusion algorithms, so pending completion of those algorithms, the main utility of the portal is to hold the data provided and to recombine it, but we continue to welcome their input and they are coming up with ideas for use of it beyond the scope of the Measure, which may be useful to consider for future Projects.

Datasets available for download from GeoPortal

The first step of our data acquisition was to establish, with the geosciences experts participating in the project, the sensor modalities and data types that would and could be relevant to the inference problem. We then requested each collaborator to enumerate which datasets fitting into these categories they possessed, and collected a representative sample of the datasets from this master list. Gravity magnetics and drill-hole sampling of density and susceptibility were our initial research targets, and we acquired a significant amount of data in these modalities, including 2.5 million ground-station gravity observations from Geoscience Australia, all of the PEPS-SA petrophysical drill-hole database, and two large gravity surveys in the Cooper Basin in SA, and Magdela in Victoria, which we are using in combination with drillhole measurements to analyse the performance of our algorithms.

We subsequently acquired and converted additional data types including magnetics,

2- and 3-D seismic lines, magnetotellurics, depth-to-basement models, various drillhole measurements, rock properties characteristics, and micro-seismic data relevant to the geothermal exploration problem in Australia.

Data acquisition and conversion into the portal system is ongoing as new datasets become available through our collaborators that are useful for carrying out the measure. Datasets with existing support include all public gravity station data, surface geology and fault lines from all states, and high-resolution gridded magnetics, topographics and radiation. Additional development has recently enabled the upload and download of complete seismic lines.

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Geothermal Data Portal

Gravity:

Onshore Bouguer anomaly o Location: continental o Acquired from: GEOSCIENCE AUSTRALIA

Onshore and offshore Bouguer free air anomaly o

Location: continental o Acquired from: GEOSCIENCE AUSTRALIA

Onshore gravity o o

Location: continental

Acquired from: GEOSCIENCE AUSTRALIA

GSSA gravity measurements (Australian gravity database raw measurements) o o

Location: continental

Acquired from: GEOSCIENCE AUSTRALIA

Magnetism:

Magnetic field intensity anomaly o o

Location: continental

Acquired from: GEOSCIENCE AUSTRALIA

Magnetic survey p1175 (*new!) o o

Location: (-26.99359, 140.990906); (-25.486457, 141.397958)

Acquired from: GEOSCIENCE AUSTRALIADDS/ Queensland o

Department of Natural Resources and Mines

Comments: part of Cooper Basin magnetic survey

Drainage:

Australian drainage map o o

Location: continental

Acquired from: GEOSCIENCE AUSTRALIA

Elevation:

Digital elevation map o

Location: continental o Acquired from: GEOSCIENCE AUSTRALIA

Radiation:

Unfiltered radiation dose rate gridded o Location: continental o Acquired from: GEOSCIENCE AUSTRALIA

Potassium concentration o Location: continental o Acquired from: GEOSCIENCE AUSTRALIA

Uranium concentration

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Geothermal Data Portal

 o o

Location: continental

Acquired from: GEOSCIENCE AUSTRALIA

Thorium concentration o o

Location: continental

Acquired from: GEOSCIENCE AUSTRALIA

Temperature:

Temperature map o

Location: continental o o

Acquired from: GEOSCIENCE AUSTRALIA

Comments: OzTemp sparse subsurface temperature data

Surface Geology:

(all acquired from GEOSCIENCE AUSTRALIA)

NSW fault lines

NSW surface geology

NT fault lines

NT surface geology

QLD fault lines

QLD surface geology

SA fault lines

SA surface geology

TAS fault lines

TAS surface geology

VIC fault lines

VIC surface geology

WA fault lines

WA surface geology

Density:

(*new!)

Cooper basin drillhole density measurements o Location: (-28.25634722, 140.0265364); (-27.48792028, 140.9199625) o Acquired from: GEOSCIENCE AUSTRALIA(?)

GSSA density measurements o o

Location: continental

Acquired from: GEOSCIENCE AUSTRALIA

Seismic horizons:

(*new!)

Cooper basin seismic C Horizon o

Location: (-29.00916, 139.47030); (-24.95703, 142.5297) o o

Acquired from: GEOSCIENCE AUSTRALIA

Comments: 3D surface of the seismic C Horizon for Cooper Basin

Cooper basin seismic Z Horizon

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Geothermal Data Portal o o o

Location: (-29.00916, 139.47030); (-24.95703, 142.5297)

Acquired from: GEOSCIENCE AUSTRALIA

Comments: 3D surface of the seismic Z Horizon for Cooper Basin

Granites:

(*new!)

Cooper basin granites model o o

Location: (-29.00915, 139.4704); (-25.08418, 142.5297)

Acquired from: GEOSCIENCE AUSTRALIA o

Comments

:

3D surface of the granite model for Cooper Basin

Topography:

(*new!)

Cooper basin topography o

Location: (-29.00915, 139.4704); (-25.08418, 142.5297) o Acquired from: GEOSCIENCE AUSTRALIA o Comments: 3D surface of the topography for Cooper Basin

Seismic lines:

(*new!)

(all acquired from SARIG data portal, all lines are from the Cooper Basin area)

75-JAA

 o Location: (-28.11598, 140.1223); (-28.03249, 140.288)

75-JAB o Location: (-28.0431, 140.2491); (-27.98899, 140.2834)

75-JAV o Location: (-28.10474, 140.316); (-27.75916, 140.3348)

80-JWA o Location: ( -27.93231, 139.8913); (-27.78736, 140.109)

80-JWB o Location: (-27.94212, 139.9086); (-27.87084, 139.9607)

80-JWC o Location: (-27.91772, 139.8653); (-27.77845, 140.068)

80-JWE o Location: (-27.94049, 139.9414); ( -27.747, 140.2476)

80-JWF o Location: (-27.93507, 139.9367); (-27.852, 139.9983)

80-JWG o Location: ( -27.93932, 139.9567); (-27.8219, 140.0534)

80-JWH o Location: (-27.8639, 139.9711); (-27.78697, 140.0323)

80-JWH o Location: (-27.90227, 140.024); (-27.85341, 140.0627)

80-JWK o Location: (-27.87602, 140.0337); (-27.81228, 140.083)

80-JWL o Location: (-27.84964, 140.0283); (-27.74771, 140.1068)

80-JWR o Location: (-27.83375, 140.0417); (-27.71582, 140.1367)

80-JWS o Location: (-27.78046, 140.1411); (-27.68678, 140.2216)

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Geothermal Data Portal

80-JWT o Location: (-27.71459, 140.1464); (-27.61756, 140.2782)

80-JWW o Location: (-27.63662, 140.2443); (27.6129, 140.2669)

80-JWX o Location: (-27.68123, 140.2303); (-27.62812, 140.2871)

80-JXB o Location: (-27.8486, 139.9848); (-27.77753, 140.0412)

80-JXC o Location: (-27.76239, 139.952); (-27.73134, 140.0022)

80-JXD o Location: (-28.21817, 139.862); (-28.15909, 139.8932)

80-JXE o

80-JXF

Location: (-28.23401, 139.8424); (-28.16996, 139.8915) o Location: (-28.23443, 139.8012); (-28.153, 139.8534)

80-JXG o Location: (-28.20005, 139.7778); (-28.13398, 139.8264)

80-JXH o Location: (-28.22085, 139.7979); (-28.16604, 139.8426)

80-JXJ o Location: (-27.50976, 140.3511); (-27.47061, 140.4117)

80-JXK o

80-JXL

Location: (-27.4904, 140.3272); (-27.44875, 140.3912) o Location: (-27.46241, 140.3264); (-27.4304, 140.3757)

80-JXM o Location: (-27.48315, 140.3287); (-27.39176, 140.41)

80-JXN o Location: (-27.02982, 140.7691); (-26.90777, 140.9975)

80-JXP o Location: (-27.34729, 140.8143); (-27.23529, 140.8725)

80-JXQ o Location: (-27.32821, 140.7527); (-27.27147, 140.872)

80-JXR o Location: (-27.28882, 140.7898); (-27.20585, 140.9654)

80-JXS o Location: (-27.32716, 140.9088); (-27.18258, 140.9909)

80-JXT o Location: ( -27.20127, 140.8847); (-27.1402, 141.0104)

80-JXW o Location: (-27.26051, 140.8267); (-27.13595, 140.8977)

80-JXX o Location: (-27.27654, 140.8421); (-27.21455, 140.979)

80-JXY o Location: ( -27.29584, 140.8947); (-27.16846, 140.966)

80-JXZ o Location: (-27.21601, 140.7988); (-27.11536, 140.9997)

80-JYA o Location: (-27.25634, 140.8783); (-27.15364, 140.9363)

80-JYB o Location: ( -27.25447, 140.5153); (-27.03076, 140.9833)

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Geothermal Data Portal

80-JYC o Location: (-27.16816, 140.7807); (-27.09771, 140.8194)

80-JYD o Location: (-27.23007, 140.638); (-26.93957, 140.6505)

80-JYE o Location: (-27.22559, 140.6156); (-27.22546, 140.7566)

80-JYF o Location: (-27.25274, 140.7103); (-27.1808, 140.7132)

80-JYG o Location: (-27.20535, 140.6145); (-27.20493, 140.7524)

80-JYH o Location: (-27.28184, 140.6703); (-27.03444, 140.6772)

80-JYJ o Location: ( -27.16073, 140.5783); (-27.09675, 140.7049)

80-JYK o

80-JYL

Location: (-27.16997, 140.5155); (-27.1204, 140.6419) o Location: (-27.24135, 140.5199); (-27.15777, 140.5628)

80-JYM o Location: (-27.23431, 140.4912); (-27.20853, 140.5566)

80-JYN o Location: (-27.23868, 140.4176); (-27.07289, 140.5031)

80-JYP o Location: (-27.24693, 140.34); (-27.17927, 140.4832)

80-JYQ o Location: (-27.19033, 140.5259); (-27.14973, 140.6286)

80-JYR o Location: (-27.20004, 140.5749, -27.1371, 140.6073)

80-JYS o

80-JYT

Location: (-27.24742, 140.6027); (-27.18358, 140.6034) o Location: (-27.11027, 140.6349); (-27.02434, 140.8216)

80-JYT o Location: (-27.08557, 140.6344); (-27.02412, 140.7676)

80-JYW o Location: (-27.13705, 140.7124); (-27.05112, 140.7156)

80-JYX o Location: (-26.95293, 140.5747); (-26.91886, 140.648)

80-JYY o Location: (-26.97017, 140.6133); (-26.92932, 140.6151)

80-JYZ o Location: (-27.03463, 140.5833); (-26.91405, 140.5877)

80-JZA o Location: (-27.03378, 140.5781); (-26.97556, 140.7029)

80-JZB o Location: (-27.08196, 140.6971); (-27.02363, 140.6983)

80-JZC o Location: (-27.04225, 140.4905); (-26.97651, 140.5269)

80-JZD o Location: (-27.01854, 140.4385); (-26.97921, 140.5022)

80-JZE o Location: (-27.06102, 140.4426); (-27.00497, 140.4702)

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Geothermal Data Portal

80-JZF o Location: (-27.04645, 140.4523); (-27.00672, 140.5156)

80-JZG o Location: (-27.49055, 140.3098); (-27.45424, 140.3669)

80-JZH o Location: (-27.5621, 139.6869); (-27.39792, 139.9276)

80-JZJ o Location: (-27.50352, 139.8628); (-27.39311, 139.9512)

80-JZK o Location: (-27.60596, 139.7989); (-27.47451, 140.0134)

80-JZL o Location: (-27.67592, 139.8668); (-27.59306, 139.9092)

80-JZM o Location: (-27.69213, 139.7942); (-27.53169, 140.0539)

80-JZM o Location: ( -27.6382, 139.8824); (-27.52997, 140.0566)

80-JZN o Location: (-27.62617, 139.8269); (-27.45703, 139.9547)

80-JZP o Location: ( -27.52268, 139.7539); (-27.44568, 139.8129)

80-JZQ o Location: (-27.68974, 139.6877); (-27.48306, 139.8953)

80-JZQ o Location: (-27.60502, 139.6879); (-27.48342, 139.8151)

80-JZR o Location: (-27.72793, 139.7877); (-27.6521, 139.9174)

80-JZS o Location: (-27.76894, 139.6594); (-27.61486, 139.8519)

80-JZT o Location: (-27.65374, 139.6239); (-27.41172, 139.9413)

80-JZW o Location: (-27.581, 139.7759); (-27.43931, 139.9745)

80-JZX o Location: (-27.68511, 139.7321); (-27.60285, 139.8807)

80-JZY o Location: (-27.77549, 139.6698); (-27.67368, 139.7454)

80-JZZ o Location: (-27.75049, 139.6899); (-27.59233, 139.878)

80-KAC o Location: (-28.10156, 140.5835); (-28.10086, 140.6918)

80-KAD o Location: (-28.13646, 140.5903); (-28.09449, 140.6036)

80-KAE o Location: (-28.13633, 140.6052); (-28.1339, 140.6524)

80-KAF o Location: (-28.14155, 140.6285); (-28.07409, 140.6379)

80-KAG o Location: (-28.08868, 140.5994); (-28.08815, 140.6914)

80-KAJ o Location: (-28.11964, 140.5816); (-28.11711, 140.68)

80-KAK o Location: (-28.15032, 140.604); (-28.0813, 140.6249)

Data Fusion & Machine Learning for Geothermal Target Exploration & Characterisation Page 15

Geothermal Data Portal

80-KAX o Location: (-28.24361, 140.5789); (-28.19688, 140.6879)

80-KAY o Location: (-28.20744, 140.5931); (-28.17674, 140.6645)

80-KAZ o Location: (-28.19504, 140.5863); (-28.17031, 140.6466)

80-KBA o Location: (-28.18592, 140.5729); (-28.15983, 140.6337)

80-KBF o Location: (-28.2728, 140.593); (-28.22727, 140.6179)

80-KBG o Location: (-28.2895, 140.6023); (-28.22355, 140.6382)

80-KBH o Location: (-28.28482, 140.5849); (-28.17121, 140.6471)

80-KBJ o Location: (-28.28135, 140.6204); (-28.21546, 140.6563)

80-KBK o Location: (-28.27666, 140.603); (-28.16271, 140.6652)

80-KJE o Location: (-27.63499, 139.8002); (-27.47393, 139.9237)

80-KJF o Location: (-27.57687, 140.5202); (-27.51516, 140.6217)

80-KJG o Location: (-27.53801, 140.5652); (-27.49129, 140.6421)

80-KJH o Location: (-27.56419, 140.5789); (-27.4768, 140.7238)

80-KJJ o Location: (-27.48323, 140.6136); (-27.43827, 140.6953)

80-KJK o Location: (-27.46726, 140.6272); (-27.42265, 140.7087)

80-KJL o Location: (-27.4489, 140.6533); (-27.39819, 140.7451)

80-KJM o Location: (-27.57209, 140.5272); (-27.42383, 140.5299)

80-KJN o Location: (-27.56293, 140.5562); (-27.42917, 140.6782)

80-KJP o Location: (-27.57578, 140.5934); (-27.43193, 140.729)

82-LBA o Location: (-28.24168, 140.2855); (-28.21203, 140.305)

82-LBB o Location: (-28.23541, 140.2929); (-28.20516, 140.3163)

82-LBC o Location: (-28.23308, 140.2953); (-28.20323, 140.322)

82-LBD o Location: (-28.23031, 140.3029); (-28.2013, 140.3257)

82-LBE o Location: (-28.23472, 140.2876); (-28.20468, 140.3252)

82-LBF o Location: (-28.23192, 140.2854); (-28.19418, 140.3337)

82-LBG o Location: (-27.97947, 140.0122); (-27.96437, 140.0413)

Data Fusion & Machine Learning for Geothermal Target Exploration & Characterisation Page 16

Geothermal Data Portal

82-LBH o Location: (-27.97462, 140.0124); (-27.95746, 140.0456)

82-LBJ o Location: (-27.9705, 140.016); (-27.95275, 140.0504)

82-LBK o Location: (-27.96574, 140.0216); (-27.94932, 140.0534)

82-LBL o Location: (-27.96102, 140.0244); (-27.94453, 140.0561)

82-LBM o Location: (-27.95466, 140.0322); (-27.94028, 140.06)

82-LBN o Location: (-27.94825, 140.0357); (-27.9366, 140.0583)

82-LBP o Location: (-27.98172, 140.0197); (-27.92983, 140.064)

82-LBQ o Location: (-27.97736, 140.0178); (-27.93382, 140.0488)

82-LBR o Location: (-27.97604, 140.0141); (-27.93716, 140.042)

82-LCB o Location: (-28.23007, 140.5938); (-28.16666, 140.6284

82-LCC o Location: (-28.22205, 140.6124); (-28.1596, 140.6465)

82-LCD o Location: (-28.21833, 140.6318); (-28.17413, 140.656)

82-LCE o Location: (-28.22406, 140.6016); (-28.19688, 140.6652)

82-LCF o Location: (-28.21545, 140.597); (-28.18669, 140.664)

82-LCG o Location: (-28.20161, 140.5893); (-28.18077, 140.6377)

82-LCH o Location: (-28.18859, 140.5838); (-28.1688, 140.6281)

82-LCJ o Location: (-28.19998, 140.4603); (-28.19945, 140.5442)

82-LCK o Location: (-28.18565, 140.465); (-28.18301, 140.5825)

82-LCL o Location: (-28.17663, 140.4963); (-28.16671, 140.6184)

82-LCM o Location: (-28.15602, 140.5402); (-28.15532, 140.5829)

82-LCN o Location: (-28.20703, 140.501); (-28.15962, 140.5069)

82-LCP o Location: (-28.20815, 140.5318); (-28.16227, 140.5356)

82-LCQ o Location: (-28.20412, 140.5525); (-28.14731, 140.5527)

82-LCR o Location: (-28.20319, 140.5628); (-28.14769, 140.5631)

82-LCS o Location: (-28.20062, 140.5735); (-28.14786, 140.5738)

82-LKB o Location: (-28.28793, 140.3031); (-28.22061, 140.3724)

Data Fusion & Machine Learning for Geothermal Target Exploration & Characterisation Page 17

Geothermal Data Portal

82-LKC o Location: (-28.27483, 140.3674); (-28.22256, 140.4281)

82-LKD o Location: (-28.27448, 140.3439); (-28.22304, 140.4096)

84-SRQ o Location: (-28.17587, 140.4179); (-28.17451, 140.5365)

84-SRR o Location: (-28.19278, 140.4247); (-28.18963, 140.5371)

84-SRS o Location: (-28.20727, 140.526); (-28.16046, 140.5268)

84-SRT o Location: (-28.21003, 140.5105); (-28.16718, 140.5112)

84-SRW o Location: (-28.21683, 140.4843); (-28.1362, 140.4883)

84-SRX o Location: (-28.22092, 140.4664); (-28.14851, 140.4724)

84-SRY o Location: (-28.21861, 140.4499); (-28.15693, 140.4538)

84-SRZ o Location: (-28.22684, 140.5247); (-28.21135, 140.5611)

84-SSA o Location: (-28.24667, 140.5245); (-28.22707, 140.5709)

84-SSD o Location: (-28.275, 140.5436); (-28.19895, 140.585)

84-SSE o Location: (-28.275, 140.5436); (-28.19895, 140.585)

84-TPJ o Location: (-28.05756, 140.2606); (-28.05592, 140.3219)

84-TPQ o Location: (-28.09692, 140.2697); (-28.04921, 140.273)

84-TQL o Location: (-28.01903, 140.2566); (-27.85549, 140.3842)

84-TQM o Location: (-28.02089, 140.2271); (-27.82265, 140.24)

85-YLT o Location: (-27.90916, 140.177); (-27.90838, 140.3067)

87-AYH o Location: (-28.05356, 140.2498); (-27.9646, 140.3909)

88-BNA o Location: (-28.03674, 140.233); (-27.94593, 140.3397)

88-BNB o Location: (-28.16314, 140.1521); (-27.98233, 140.3298)

88-BNC o Location: (-28.06255, 140.2525); (-28.0088, 140.3345)

88-BNG o Location: (-28.05465, 140.1656); (-27.92566, 140.3261)

89-BYP o Location: (-28.03717, 140.2549); (-28.01008, 140.2848)

89-BYQ o Location: (-28.03434, 140.254); (-28.00648, 140.2857)

94-EYB o Location: (-27.91001, 140.2809); (-27.8287, 140.3752)

Data Fusion & Machine Learning for Geothermal Target Exploration & Characterisation Page 18

Geothermal Data Portal

94-FBX o Location: (-27.70815, 140.2764); (-27.70295, 140.778)

95-FXL o Location: (-28.12757, 140.1544); (-28.00484, 140.3301)

Data Fusion & Machine Learning for Geothermal Target Exploration & Characterisation Page 19

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