The global mining industry is experiencing a tectonic shift. Volumes around geospatial data management have exploded recently thanks to increased production, technological advancements, and requirements for more advanced data analysis; some types of seismic data, for example, double in size every three to four years.
However, getting all that spatial data, vector data, raster data, and other complex data types from the field to centralized storage and geospatial technology applications is often a time-consuming and expensive task.
But it doesn’t have to be. Mining companies who need to analyze geological data as fast as possible can benefit from cloud-native file transfer from the field. Let’s explore how.
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Transfer Geospatial Data From Sensor to Storage
Move geospatial datasets of any size with MASV’s fast, secure, and compliant cloud-native file transfer.
What New Technologies Have Changed the Mining Industry?
We’re on the cusp of a technological revolution in mining, especially when it comes to how sensors and AI play with geospatial data management. Megacompany BHP, for example, is a leading producer of iron ore, copper and metallurgical coal and potash. It has also placed a large bet on data and AI as fundamental to the future of mining, from autonomous vehicles to AI-powered ore sorting.
“AI systems analyze vast amounts of mining data gathered by on-site sensors and other monitoring systems to identify patterns and make informed decisions, leading to increased efficiency, reduced costs, improved safety, and minimized environmental impact,” the company says.
Other disruptive technologies affecting geospatial data management in the mining industry include:
- Exploration and resource assessment: Advanced technologies have revolutionized how mining companies explore and assess potential sites, leading to more accurate predictions of resource quantity and quality. This is traditionally a large, costly and risky part of the mining business.
- Automation and robotics: The integration of automation and robotics is transforming mining operations, increasing efficiency, reducing human intervention, and enhancing safety in hazardous environments.
- Predictive maintenance: Innovations in predictive maintenance and machine learning optimize equipment performance by predicting failures before they occur, reducing downtime and maintenance costs.
- Operational optimization: Mining operations are further optimized through data-driven insights, improving processes such as drilling, blasting, and mineral processing to maximize productivity and profitability. Video and sensor data can now be used to understand almost immediately what’s happening underground – as long as the data gets where it needs to be for analysis in a timely manner.
- Cloud technologies: Mining companies can securely store and access vast amounts of geospatial data in the cloud, enabling real-time monitoring, analysis, and decision-making from anywhere in the world. A cloud geospatial database, for example, facilitates collaboration among geographically dispersed teams, enhances scalability, and streamlines processes such as resource planning and equipment maintenance.
Fundamentally, at the centre of all this innovation is data.
How MASV Enables Delta Scan
Learn how Delta Scan, a specialized engineering inspection, digitization, and BIM company, used MASV to get geospatial data from the remote African countryside to storage.
The Future of Mining: Geospatial Data Management From Multiple Sources
In the age of big data and AI-driven analysis, knowing where to dig involves gathering a mind-boggling volume of environmental data and location data during exploration and surveying, then performing data integration and processing on those datasets.
Such intense geospatial data management means geological and mining companies deal with a vast array of different data sources and file formats. These sources include location information from scanned maps, satellite images, and Global Positioning System (GPS) data from spatial databases to discern geographic features and other geospatial information.
- Remote sensing: Remote sensing technologies such as satellite imagery, aerial photography, LiDAR (Light Detection and Ranging), and drones are used to collect data on surface topography, geological structures, and land cover to help identify potential mineral deposits or geological features.
- Geographic information systems (GIS): GIS software is used for geospatial data analysis to analyze and visualize spatial data related to geology, topography, mineral resources, and land use. GIS technology enables geologists to create maps, model geological features, and integrate various datasets for geological surveying.
- Geophysical surveys: Geophysical surveys, including seismic surveys, electromagnetic surveys, gravity surveys, and magnetic surveys, are used to study subsurface geology and detect anomalies that may indicate the presence of mineral deposits or geological structures.
- Ground penetrating radar (GPR): GPR uses radar pulses to display subsurface structures and detect buried objects. It is commonly used in geological surveys to map geological layers, identify faults, and locate mineral deposits.
- Core drilling: Core drilling involves extracting cylindrical rock samples from the subsurface for detailed analysis, sometimes involving drill bits fortified with industrial diamonds. Core samples provide valuable information about rock composition, mineralization, and geological structures.
- Geochemical analysis: This involves collecting and analyzing rock, soil, and water samples to determine the presence of minerals and elements associated with mineral deposits. Techniques such as X-ray fluorescence (XRF) and inductively coupled plasma mass spectrometry (ICP-MS) are used to assess geochemical composition.
- Seismic imaging: Seismic imaging techniques, including reflection seismology and seismic tomography, are used to create detailed images of subsurface structures by analyzing the propagation of seismic waves. Seismic surveys help geologists map geological layers, faults, and potential hydrocarbon reservoirs.
- Mineral exploration software: Specialized software tools such as 3D modeling software, mineral exploration software, and data processing applications are used to analyze geological data, interpret survey results, and generate models of mineral deposits.
All the techniques above generate vast volumes of data that need to be processed in a way that reveals not only where to dig, but a complete view of the economics, politics, and ethics of a potential project.
This is where cloud can be particularly useful, given its vast storage and compute capabilities. Analyst firm Global Data says public cloud and infrastructure-as-a-service are key areas for future investment for mining firms.
AWS and Azure are the main public cloud players in this sector.
The Next Big Challenge In Mining Tech: Data Workflow
Given that mining operations occur over broad, and frequently remote, geographic areas, data connectivity in the field is a common issue.
- Underground mines and tunnels are extremely challenging environments to deploy network systems, which can be an immediate impediment to effective data workflows. After all: If the data can’t get uploaded offsite, the data workflow is blocked.
- Satellite connectivity has changed what’s possible in terms of data workflows from remote locations, but bandwidth demand and intermittent connectivity remains a perpetual factor.
One data transfer option includes transferring enormous datasets with on-premises point-to-point data transfer tools and a relational database management system – but this requires a dedicated, high-bandwidth internet connection. In remote locations, that’s usually a non-starter.
For this reason, hard disk drive (HDD) based workflows are common across mining and geospatial operations. Although HDD-based workflows are reliable and cheap, they’re simply not fast or flexible enough to accommodate data processing and insights in near real-time – it often takes days or weeks for geographic data to be saved to hard drives, shipped, downloaded, and processed.
The need for cloud-native technology in geospatial data management
As an industry, mining and other professionals working in geospatial data management need to upload and process data as quickly as possible. Turnaround times around data collection must be fast and efficient – and that means workflows must move to the cloud.
A fast-emerging category of software-defined data workflow products, such as MASV, can help. MASV is a cloud-native data transfer service that can send and receive file packages of unlimited size at unparalleled speed and reliability – even from remote locations, MASV can saturate your bandwidth for maximum data delivery in the shortest time.
MASV for Near-Real-Time Geospatial Data Management and Transfer
Built on a private, accelerated transfer network on an AWS backbone, MASV was originally built to ingest and deliver massive file packages of unlimited size in a simple web browser without software installations, plugins, firewall exceptions, or training.
For the challenging data workflows around geological and geospatial data, however, the MASV Desktop App takes file transfer to the next level. It offers file transfer automations (and automated ingest to storage), along with additional reliability and speed tools including double the throughput compared to a browser and a 10Gbps bandwidth optimization.
- The MASV Desktop App also offers relentless reliability, with the ability to auto-resume progress after interruptions, pause-and-resume on command, and validates file integrity with checksum verification.
- MASV Multiconnect channel bonding can be configured to send data over as many internet sources as you can connect for bandwidth multiplication and failover. MASV clients regularly bond multiple Starlink, cellular, and terrestrial internet connections in the field.
- Advanced data workflows, including MASV-to-many uploads, can be configured in minutes and deployed in perpetuity: Simply drop the data into a MASV Watch Folder and your no-code automation transfers the data along a preconfigured path. Files can also be downloaded automatically..
- For organizations with enterprise security or compliance needs, MASV offers a complete, SOC2/ISO27001 enterprise onboarding program, accessible by emailing [email protected].
MASV can be configured to deliver to the storage destination of your choice, including multiple cloud and connected on-prem storage locations. MASV makes it as easy to upload to an Amazon S3 or Microsoft Azure as it is to configure automated delivery to your office NAS or enterprise on-prem storage.
Getting started with MASV is simple, free and self-serve: Anyone can get started for free and start building rock-solid data workflows right away.
💡 Note: A complete set of help documentation is available here. For organizations with in-house development teams to assist with data workflows, MASV also offers a complete set of API and developer tooling.
Reliable, Fast Data Transfer – Anywhere
MASV can move mountains of data from any location – even a remote mountaintop.