Predicting Oil Spill Risk Using Remote Sensing
Avatar photo Nash Prado

Predicting Oil Spill Risk Using Remote Sensing

Digital Elevation Model | Infrastructure | Monitoring | Oil

Introduction

In the aftermath of the Norilsk, Russia oil spill from May 29, 2020, Proimagery analyzes what happened and proposes a strategy to mitigate future risk to similar sites. Governments, NGOs, and companies leverage insights from remote sensing (eg. satellite imagery) to detect and respond to environmental disasters.

What happened?

On May 29, 2020, a fuel storage reservoir failed at a power plant outside Russia’s northernmost city of Norilsk. This failure caused the leaking of more than ten thousand tons of oil, contaminating the Ambarnaya river. Contaminated river water then flowed into lake Pyasino and its surrounding subsoil. The BBC has reported extensively on it here.

The following image slider shows a timelapse of the magnitude of the oil spill at Norilsk between May 30, 2020, and June 8, 2020, using data captured and processed by Proimagery.

 

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Time series of images captured from May 30, 2020, to June 8, 2020, shows images of the blood-red color of Ambarnaya river in Norilsk, Russia due to an oil spill that happened on May 29, 2020

 

How Proimagery used remote sensing to detect the extent of the oil spill

In addition to visually inspecting time series data for the region, the Proimagery team used remote sensing techniques to scientifically quantify and pinpoint the extent of the spill on the Ambaryana river. Using object-based image analysis, the Proimagery team processes multiple satellite images captured over the surrounding area to determine and pinpoint affected regions.

 

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Oil spill extent derived from satellite images using object-based image classification

 

What could the company do to mitigate its risk?

The best practice in the mining industry is to forecast potential risk using Digital Elevation Models and Computational Fluid Dynamics and terraform the area appropriately to ensure potential spills do not impact the local environment. The cost and quality of Digital Elevation Models and the computation fluid dynamics models have dropped remarkably in the past several years to make this both technologically possible and cost-efficient.

 

Conclusion

The Norilsk oil spill has come and gone, and will forever change the environment. Proimagery was able to detect and quantify the extent of the damage using satellite imagery. Proimagery highly recommends utilizing a computational fluid dynamics-based model to predict risk on a go-forward basis for any company in this industry.

 

March 2021 Update

Now that the oil spill has been contained and damage assessed, it is possible to estimate the total environmental impact. It has been classified as one of Russia’s worse environmental disasters to date. The fuel spill saw 21,000 tons of diesel pour into rivers and lakes in Russia’s Arctic north. Russia’s President Vladimir Putin declared a state of emergency in Norilsk shortly after the incident. Norilsk Nickel, the mining firm responsible for the spill has paid a record $2 billion fine related to this incident. The fine was paid in full in March 2021.