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December 2, 2019 at 10:22 am #37124
#News(General) [ via IoTGroup ]
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How the IoT Is Collapsing Different Oil and Fuel Theft Methods
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Oil theft is one of the biggest hiccups that affect the oil industry drastically in terms of financial losses.
Since oil and its refined products are fungible substances, it is very easy for thieves to steal them without being detected.
Around $133 billion worth of oil is stolen annually and sold illegally on the black market.
This crude oil is then processed in artisanal refineries to produce low-quality petroleum products.
Due to artisanal refining techniques and oil smuggling, the price of petrol and diesel is continuously soaring.
Oil spills caused by improper oil extraction and transportation methods contaminate the environment to a large extent.
These implications may become severe based on the method that thieves use to steal oil.
Pipeline vandalism and illegal oil bunkering are among the methods that thieves use to steal fuel.
Oil companies need to take preventive steps to ensure that petroleum-based products remain secure.
Its implementation is helping oil refineries and companies to tackle financial losses and meet the demands of end consumers.
With collective usage of traditional oil dyeing or molecular marking methods and the Internet of Things, oil-stealing practices can be tackled.
Let’s examine several methods that thieves use to steal oil, and the ways in which they can be countered:
Pipeline Vandalism and Tapping
Pipeline tapping is one of the major challenges that oil refineries face.
This method is mainly prevalent in African countries.
In Nigeria alone, oil pipeline vandalism has increased by 77 percent within a single month.
“Oil mice” (thieves) drill a hole in a pipeline and install illicit taps to divert oil and other refined products.
Since pipelines are buried in complicated and remote geographical locations, it becomes very difficult for refineries to keep an eye on them.
Also, pipelines can run for several kilometres, making inspection and maintenance tasks more complex and rigid
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AutoTextExtraction by Working BoT using SmartNews 1.0299999999 Build 26 Aug 2019
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