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Description
Evaluate and analyze complex layered data sets to construct a comprehensive understanding of large-scale landscape scenarios. In partnership with the British Geological Survey, GeoVisionary excels in the integration and visualization of varied data sets, enabling collaboration across different fields through a unified tool within the same spatial framework. Strategically plan and define field activities while assessing potential risks to optimize time efficiency during ground operations. Teams on-site are equipped with the most thorough information available and can relay updates to local staff and remote specialists regarding their findings and ongoing tasks. By merging extensive data from various origins, it enhances comprehension of diverse spatial information. Combine multi-resolution terrain data from different sources to quickly generate slope and aspect maps. Engage effectively with your audience and facilitate visualization without the need for coding, ensuring that complex data is accessible and understandable for all stakeholders involved. This collaborative approach fosters better decision-making and drives innovation in landscape analysis.
Description
Paradise employs advanced unsupervised machine learning alongside supervised deep learning techniques to enhance data interpretation and derive deeper insights. It creates specific attributes that help in extracting significant geological information, which can then be utilized for machine learning analyses. The system identifies attributes that exhibit the most variation and influence within a geological context. Additionally, it visualizes neural classes and their corresponding colors from Stratigraphic Analysis, which reveal the spatial distribution of different facies. Faults are detected automatically through a combination of deep learning and machine learning methods. Furthermore, it allows for a comparison between machine learning classification outcomes and other seismic attributes against traditional high-quality logs. Lastly, it generates both geometric and spectral decomposition attributes across a cluster of computing nodes, achieving results in a fraction of the time it would take on a single machine. This efficiency enhances the overall productivity of geoscientific research and analysis.
API Access
Has API
Yes
API Access
Has API
No
Integrations
No details available.
Integrations
No details available.
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
Virtalis
Founded
1989
Country
United Kingdom
Website
www.virtalis.com/products/geovisionary
Vendor Details
Company Name
Geophysical Insights
Founded
2009
Country
United States
Website
www.geoinsights.com/products/
Product Features
Virtual Reality
Application Development
No
Augmented / Mixed Reality
No
Collaboration
No
Content Creation
No
Cross-Device Publishing
No
Drag & Drop
No
Immersive Training
No
Process Simulation
No
Product Visualization
No
Social Sharing
No
User Interaction Tracking
No
Virtual Meetings
No
Virtual Prototyping
No
Product Features
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No