Introduction
The presentation will provide an overview of the IntelliView DCAM. It is a new and efficient method for automating detection of leaks and other mission-critical events at aboveground oil and gas production, transfer and storage facilities as well as offshore platforms.
The DCAM utilizes thermal and color imaging with deep machine learning and patented artificial intelligence that specifically targets liquids and wet hydrocarbons. This intelligent edge-based vision system replaces manual monitoring and detect leaks, sprays and pooling in real time – including small releases typically missed by traditional systems. Alerts are accompanied by video evidence and delivered through multiple channels. Implementing this technology solution improves the operator’s monitoring capabilities and provides the visibility needed to respond quickly, aiding in the reduction or prevention of adverse environmental, safety and business impacts.
Learn About:
- The features, capabilities and customization options of AI-powered imaging for leak detection
- Applications in the oil and gas industry and how major operators are deploying the technology
- The potential and field proven benefits of the system in the areas of environmental performance, safety, operational efficiency and cost reduction
Background:
Upstream and midstream surface piping typically found at pump and pig trap facilities, block valve sites, terminals and offshore platforms, are exposed to the environment and vulnerable to mishaps and mechanical failures. This makes them prone to leakage. However, such infrastructures are economically challenging to monitor, despite availability of various leak detection methods and technologies, due to their design (bends, joints and connections) and remote location.
Traditional non-visual systems are limited by their ability to provide high confidence actionable insights and require a high degree of accuracy and reliability. Technologies like CPM and acoustic sensors, for example, are effective for line of pipe monitoring but their performance can be hindered by errors from pressure transients, which cause excessive false alarms and smaller leaks to be missed. Alarms often need to be verified through site visits. And although periodic inspections and aerial surveys provide visual data, their operational infrequency and unsuitability in bad weather introduce detection delays.
With emissions regulations becoming more stringent and increasing self-accountability in the oil and gas sector, there is a need to improve leak detection capabilities and response times of operators. IntelliView addresses these monitoring gaps with an AI driven IIoT technology platform that was developed through extensive research and over 350,000 hours of filed use. Commitment to continued innovation and customer-driven enhancements ensures the challenges of the future are addressed.
Speaker Bio:
Tariq Ahmed
Chief Marketing Officer & Board Advisor
Tariq is an entrepreneur and business professional with over 15 years of experience in key roles of sales, business development, engineering, technology and innovation with Oil and Gas majors National Oilwell Varco and Schlumberger. He holds an engineering degree from Ryerson University, an executive MBA from the University of Toronto and master certificates in Technology Commercialization (from the University Texas) and Petroleum Engineering (Texas A&M). Tariq has actively served on IntelliView’s advisory board since early 2020.