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Fleet Space announces new ExoSphere features

Published by , Editorial Assistant
Global Mining Review,

Fleet Space Technologies, a leader in space-enabled mineral exploration, has announced three new features to their mineral exploration technology, Exosphere by Fleet® – designed to enhance and accelerate data-driven global mineral exploration efforts with machine learning (ML) capabilities and real-time survey diagnostics.

Fleet Space announces new ExoSphere features

The introduction of new ML-powered features and real-time sensor diagnostics to ExoSphere enables faster on-site targeting decisions and provides access to greater subsurface insights before, during, and after every survey.

ExoSphere is rapidly becoming an essential tool for the exploration industry. Bringing together Fleet Space’s satellite constellation in low Earth orbit and patented seismic array technology, ExoSphere delivers 3D subsurface models of a survey area in days with near-zero environmental impact. Over 35 global exploration companies have used the technology to complete hundreds of surveys for a wide range of commodity types across 5 continents, including Rio Tinto, Barrick Gold, Core Lithium, among many others.

“A future with near instantaneous access to subsurface insights that can lead to the next wave of mineral discoveries needed for the energy transition is within our grasp due to rapid advances in space technology,” said Co-Founder and CEO of Fleet Space Technologies, Flavia Tata Nardini. “Technologies like ExoSphere, and the ML-enabled, real-time features we are building for it represent a major leap forward in the potential scale and speed of data-driven exploration while also reducing environmental impact.”

Historically, the process of gathering and evaluating the different forms of data inputs for a survey area can take years or months before they are used as part of an exploration strategy, let alone inform on-site targeting decisions. This leads to extended planning cycles and limits the ability of on-site exploration teams to make quick operational decisions needed to hone in on promising new opportunities on their tenements. With ExoSphere’s 3D subsurface models and ML-enabled features, exploration customers will be able to leverage a variety of new subsurface insights on-demand to accelerate and enhance their data-driven exploration efforts.

Customers using the ExoSphere platform will now be able to access Geological Sketch – a powerful visualisation tool that allows them to convey their understanding of the geology and lithology of their project. Using this visualisation, Fleet Space’s in-house team of geophysicists can refine the customer’s 3D model with a wider range of insights before, during, and after their survey is complete – enhancing model accuracy while also unlocking new insights to inform their targeting decisions.

Understanding basement depth is critical, as it is an important indicator of the economic potential of a project. In the coming months, ExoSphere will have a ML-enabled feature that will provide a projection of the basement depth based on customers’ ANT survey results. Customers will also be able to upload other insights they have about the lithology and geology of the area to enhance the prediction on the ExoSphere platform. This gives customers an efficient way to evaluate and visualise the potential basement depth of a project as part of their data-driven exploration efforts.

Fleet Space’s patented, space-enabled seismic sensors - Geodes - have been deployed in many of the harshest conditions on Earth, from the Australian red lands to the Canadian permafrost. As part of their deployment, customers will soon be able to review the diagnostics on each individual Geode used as part of a survey in real-time to determine if any corrective measures should be taken to optimise their performance while in the field. Real-Time Diagnostics is a powerful tool for onsite teams to make quick adjustments to the Geodes without the need to remove them from the survey area, which is common with other methods.

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