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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

The process of advanced velocity determination combined with 3D and 2D velocity model construction results in precise and high-quality seismic images that are interpretable in both time and depth. An extensive range of interactive and batch tools for analyzing anisotropic models effectively addresses a wide array of seismic imaging challenges. By integrating interpretation and modeling solutions, the workflow is optimized, minimizing data loss while adhering to geological constraints. The construction of accurate 3D and 2D models is straightforward, making it feasible regardless of the complexity of the underlying structural geology. Furthermore, the system is designed to operate efficiently with highly parallelized capabilities, accommodating extensive 3D datasets and multi-line 2D datasets, whether on-premises or in cloud environments. Accurate seismic images and reliable depth models play a critical role in hydrocarbon exploration and production efforts. The Aspen GeoDepth velocity determination and modeling system provides an effective means for enhancing seismic imaging, facilitating the integration of various processes such as interpretation, velocity analysis, model construction, and time-to-depth conversion, ultimately leading to better decision-making in exploration projects. This comprehensive approach not only improves the quality of the seismic data but also supports more informed resource management strategies.

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

Screenshots View All

Screenshots View All

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

AspenTech

Country

United States

Website

www.aspentech.com/en/products/sse/aspen-geodepth

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

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