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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

The AbaData TRIAGE Pipeline Integrity solution represents a cutting-edge risk management tool aimed at assisting energy operators in the proactive monitoring, evaluation, and reduction of threats within their pipeline systems. Utilizing advanced technologies such as big data analytics, machine learning, and integrated GIS mapping, it revolutionizes conventional integrity programs into forward-looking, data-centric workflows that enhance safety measures and regulatory compliance. By analyzing over four decades of pipeline performance data from more than 500,000 kilometers of infrastructure and examining thousands of historical failure incidents, the system effectively identifies potential risks at an early stage. Additionally, it achieves approximately 95 percent accuracy in automatically mapping pipeline connectivity and flow allocation, which minimizes the necessity for manual checks and accelerates decision-making processes. The platform’s predictive analytics capabilities further aid in recognizing failure trends based on historical data, upstream well activity, and environmental factors, enabling teams to prioritize necessary inspections and mitigation efforts. This comprehensive approach not only optimizes operational efficiency but also reinforces the integrity and reliability of pipeline systems.

Description

Identify patterns in operational data that can forecast deterioration and potential failures long before they occur. By employing accurate failure pattern recognition, you can reduce the frequent occurrence of false positives typically associated with traditional model-based approaches. Utilizing low-touch machine learning, you can swiftly distinguish between normal and abnormal behaviors, ensuring equipment protection starts within weeks rather than extending into months. The integration of Aspen Mtell with Aspen Cloud Connect™ provides connectivity to devices that support OPC UA. This method of recognizing operational patterns not only serves as an initial defense against asset decline but also enhances existing maintenance strategies through the deployment of AI-driven agents across various sites or throughout the entire organization. By focusing on precise failure pattern recognition, the challenge of high false positive rates in model-based solutions is effectively mitigated. Moreover, the rapid identification of operational behaviors facilitates timely equipment protection, ensuring that organizations can respond proactively to potential issues as they arise.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

AbaData
SAP Store

Integrations

AbaData
SAP Store

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

AbaData

Founded

2004

Country

Canada

Website

www.abadata.ca/pipeline-integrity

Vendor Details

Company Name

Aspen Technology

Founded

1981

Country

United States

Website

www.aspentech.com/en/products/apm/aspen-mtell

Product Features

Oil and Gas

Compliance Management
Equipment Management
Inventory Management
Job Costing
Logistics Management
Maintenance Management
Material Management
Project Management
Resource Management
Scheduling
Work Order Management

Product Features

Preventive Maintenance

Condition Monitoring
Inspection Management
Maintenance Scheduling
Mobile Access
Predictive Maintenance
Purchasing
Reminders
To-Do List
Vendor Management
Work Order Management

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