Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Rapid structural and stratigraphic analysis and visualization across multiple surveys allows for seamless collaboration among users in a unified digital space. This system ensures accurate facies predictions derived from well data by integrating geological, geophysical, and seismic insights across various scales. It offers a thorough, cohesive approach to seismic interpretation, featuring top-tier workflows for facies classification and volumetric visualization. The solution supports interpretation and visual integration from regional to prospect scales. Team members can easily share projects and data without any risk of duplication, fostering a more efficient collaborative environment. Enhanced interactivity and consistent views significantly speed up the interpretation process, leveraging the capabilities of modern workstations with their advanced graphics, ample memory, and rapid connectivity. Additionally, the design prioritizes usability with a straightforward, intuitive interface that streamlines workflows, reducing the number of clicks required for task completion. As a result, users can focus more on the analysis rather than navigating complex software features.
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
API Access
Has API
Integrations
No details available.
Integrations
No details available.
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Aspen Technology
Country
United States
Website
www.aspentech.com/en/products/sse/aspen-seisearth
Vendor Details
Company Name
Geophysical Insights
Founded
2009
Country
United States
Website
www.geoinsights.com/products/
Product Features
Product Features
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization