The technical series communicating the journey from data to discovery through SensOre’s ML technology.
SensOre iNSIGHTS on Geological Prospectivity Modelling
Transforming Embedded Geological Information into Model-Ready Data
SensOre recognizes the potential of non-numeric data to be transformed to inform machine learned prospectivity models. We’ve developed advanced programmable text-mining solutions to convert geological data into numbers. Machine learning algorithms are then used to predict spatial adjacency for commodities and deposit types of interest for each point object. Knowledge extraction is driven by contiguity associations, determining the spatial relationships of specific words and phrases from SensOre’s proprietary and numerically coded geological dictionary with Au, Cu, Li, or Ni deposits. This reflects a cause-and-effect relationship between mapped geological objects and mineralisation and helps to fully utilise our geological knowledge and understanding of mineral systems of interest.
With statistical output visualisation, SensOre has constructed new geological prospectivity maps over WA for a range of commodities and deposit types including Cu-VMS, LCT Pegmatite, Ni Intrusion-Related, and Phosphate. SensOre’s geological prospectivity models are on track to be extended to other states and continental Australia as the SensOre data cube expansion evolves towards completion over the coming months.
SensOre’s insights into geological prospectivity can be used in exploration for terrane and region selection, and for project generation and ranking. Strategically, these maps can be used to probabilistically assess the geological prospectivity of any tenement for the commodities modelled, making them an invaluable tool for business development decision-making.
SensOre iNSIGHTS on Growing Australia Data Hypercube
Significant State-and Continent-Scale Expansion of Data Capture
SensOre Ltd is boldly changing the way exploration targeting is carried out by harnessing and fusing the vast quantities of underutilised geoscience and environmental data from the public domain into its Australian Data hypercube. SensOre’s most valuable (non-human) asset is its Data Hypercube. The data in the database resides in a common, globally scalable gridded geospatial architecture consisting of layers of geoscience data including geology, geochemistry, and geophysics. It is central to all SensOre models generated on open data and underpins our targeting services allowing SensOre to generate high-quality, data-driven exploration targets.
State-scale geoscience data is now ingested for WA, SA, and NSW
SensOre achieved a significant milestone of compiling, cleaning, merging, and ingesting the vast quantities of all openly available state-scale geoscience data across SA and NSW, adding to the completed data hypercube for WA. This was accomplished with the support of industry clients in SA and competitive government co-funding in NSW from the Critical Minerals and high-Tech Metals Activation fund. The Data Hypercube currently contains approximately 2,000 layers of geoscience data with more than 63 billion data points occupying the cells within the Data Hypercube.
The Data Hypercube includes SensOre’s Discoveries Database, an extensive metallogenic database of compiled and cleaned deposit and mineral occurrence data from many sources. This database is updated quarterly and is expanding to include more commodities. This database provides accurate point location, resource footprints, and mineral endowments and grades calculated from (mines, resource, reserves, and historical production), deposit depth including tested deposit depth and depth to top of deposit, mineral deposit type. The Discoveries Database is one of our most valuable data assets as it functions as one of our primary training datasets containing 61,660 occurrences for gold, nickel, copper, and lithium.
Combined, the Data Hypercube and the Discovery Database are deployed in SensOre’s machine learning (ML) workflows to target critical minerals, including Au, Ni, Cu, Co, PGE’s, Li and REE’s.
Continental-scale geoscience data expansion
A second significant milestone was achieved this year with respect to our continental-scale geoscience data compilations. We have made considerable advancements in acquiring, processing, compiling, and merging continental-scale geophysical and geochemical data. SensOre has ingested CSIRO’s ASTER, and hydrogeochemistry data.
Intrepid Geophysics has delivered their advanced processed continental merged compilations for magnetics, gravity and radiometrics data and approximately 54 derivative layers each for magnetics and gravity and 27 derivative layers for radiometrics. These data sets were added to our 430 m resolution Data Hypercube over the continent and are now suitable for application of machine learning algorithms as well as to our 80m resolution grids which aggregate to some 165 billion data cells over the continent.
Why are SensOre’s Data Hypercube expansions worth talking about?
- SensOre’s Data Hypercube expansion is addressing a protracted, industry-wide dilemma namely, the underutilisation, under-appreciation, and poor management of both new and legacy geoscience and environmental data that continues to obscure the potential utility of geoscience data.
- We’ve done the hard yards of compiling, cleaning, feature engineering and fusing massive amounts of geologically and environmentally significant data into a highly curated, proprietary database so you don’t have to.
- The construction of Data Hypercube represents several millions of dollars of investment and years of human resources dedicated to curating geoscience data conservatively estimated to have cost industry more than $20B to collect across three states.
How do you get access to these resources?
Contact SensOre to maximize your exploration success by utilising our propriety advanced machine learning capabilities. SensOre is here to help you get the most out of your geological data on your way to making a discovery.