How can IoT ensure that Oil pipelines run smoothly?
Ever since the economic downturn in 2008-2009, the oil and gas industry has been confronted with the herculean task of maintaining a high level of performance to attract investment. The Internet of things (IoT) is proving to be the performance enhancing drug to help O&G companies get back on track and achieve safety, efficiency and visibility across the enterprise like never before. How can the Internet of Things, be the game changer for ensuring smooth operations of oil pipelines over a period of time? Here’s how.
1. Oil Pipelines: The Network and the Threat
Oil pipelines typically transport liquid at pressures ranging between 600-100 psi. At such high pressures, they become highly susceptible to ruptures. Flaws leading to such ruptures are required to be detected and monitored at all times, given the age of some of these pipes. While a derailed tanker train can only spill as much as oil as it is carrying, a ruptured pipeline can continue to pump.
2. The dynamics of IoT
Larger ruptures often start as pinhole leaks that can be easily missed during visual inspection until they become serious. The industry is incorporating sensors to monitor pressure, flow, compressor condition, temperature, density and other variables.
- Acoustic sensors can detect a breach of variation in the acoustic signature.
- Fiber optic sensors detect deformations in the pipe walls.
- Sensors are also sent down the pipes for inspection.
The most popular device is a robotic instrument called a smart pig. These are wire-wrapped straw used for cleaning out wax and other contaminants. The name comes from the squealing noise the original models made as they travelled down the pipe. Depending on the model, smart pigs detect cracks and weld defects through magnetic flux leakage or shear wave ultrasound, mechanically measure the roundness of the pipe to detect crushing, or measure pipe wall thickness and metal loss through compression wave ultrasound. The system that integrates this information on an operational level is called SCADA (Supervisory Control and Data Acquisition). It is used to gather and monitor data and then to perform activities like turn a valve or change the set point on a flow controller. SCADA is common in industrial operations that require real-time control of system operations.
In industrial implementations, the IoT develops on top of the already existing system, allowing for a move from “monitor and respond” to a predictive and proactive approach supporting improved decision making.
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3. IoT Implementation in ensuring pipeline safety
In late September 2015, three huge fires – the Valley, Butte and Rough Fires – were close to the pipeline and facilities of Pacific Gas & Electric Company (PG&E). PG&E used TAMI (Tactical Analysis Mapping Integration) to monitor the movement of the fire lines and the wind direction, and it provided alerts whenever the fire line was within a certain distance of a facility. This helped PG&E in triggering an isolation plan which they had already built using data from TAMI. This helped ensure the safety of the pipelines.
To continuously monitor hundreds of thousands of miles of pipelines is an arduous task as it requires responding effectively to ruptures and other malfunctions. The IoT revolution has helped ease the burden on O&G companies.
Allerin is a trusted software solutions provider that creates and develops the technology used in IoT enabled devices for oil pipelines to run smoothly over a sustained period.
#BringItOn
We are working with Oil & Gas companies to address all the issues as described here... Great article!
Open to Opportunities in AI Sales | Adaptable and Keen to Leverage My Experience and Skills in a Thriving Industry
8 年Excellent article and this is also the reason @Dashboardlimited makes good use of Internet of Things and apply the technology in pipelines
Vice President at Goldman Sachs
8 年Excellent insight, Thanks for sharing !
Principal Machine Learning Lead @Cleareye.ai Gen AI | NLP | Vision | Recommender Engine | Spark ML Sklearn Pandas Machine Learning | Deep Learning | GNN | Mlflow | Azure ML | Sagemaker
8 年Great Article Naveen