IoT has served and revolutionised the transformation of traditionally non-digital industries, reformulating business models and supporting the development of new markets.
For the Oil & Gas industry, reliance on established traditional processes has long withheld the adoption of new, modern digital technologies. As one of the biggest industries globally, the oil and gas market is expected to witness continuous growth of 20% up to 2024.
The supply chain is vast within this profitable industry, with many challenges being faced from upstream to midstream to downstream and distribution.
It has become paramount that traditional systems can no longer provide efficient maintenance, leading the oil and gas industry to question- adopt IoT driven solutions or lag behind?
Challenges the oil and gas industry face
A critical reasoning for evolution in any traditional industry surrounds the changing needs of the market and the new challenges faced in alignment.
In recent years, oil and gas companies have seen rising investment and consumer demand as the need for resources skyrocket. To meet these high demands, the industry has seen a need to adapt to outstanding performance in all areas of the supply chain. Optimal machine operation, round-the-clock monitoring, and real-time analytics need to be addressed to avoid downtime that can have a detrimental hit on costs and productivity, especially within traditional systems.
Additionally, a lens in on climate change has been an influential factor for the oil and gas industry. As the biggest user of energy and natural resources, oil and gas must gain greater transparency on their environmental footprint and insert solutions to avoid critical environmental damages like oil leakages.
IoT as a solution
Equipment Maintenance
Machinery and equipment play a large role throughout the oil and gas industry from extraction to deployment. Oil & gas factories are of a massive scale, with multiple types of machinery used among the length of the supply chain. Therefore any equipment malfunctions need to be predicted and managed in real-time, even before they happen.
The costs of equipment downtime are damaging to profit; it has been estimated downtime can cost a company up to $260,000 an hour. Installing IIoT driven solutions to oversee predictive maintenance of equipment enables automated forecasts to alert operators whether a given machine is due to fail, allowing fixtures to be made before the damage is done.
Machine Learning is a strand of predictive monitoring that conjures frequent patterns in equipment conditions and uses intelligent algorithms to make informed and accurate decisions.
Pipeline and Tank Monitoring
Pipeline leakages have accounted for substantial environmental impacts to the surrounding environment. In oil and gas plants located in the ocean, as little as 1 litre of oil can contaminate 1 million litres of water, causing devastating impacts to wildlife.
24-hour visibility of tank and pipeline conditions mean any changes can be immediately identified and addressed. The critical use case areas for sensors within pipelines range from acoustic detection of sound wave signals that initiate a crack in the pipes, to magnetic wave detection of the pipeline’s surface to indicate any signs of erosion or damage, etc.
A distinguished issue sensor-based solutions face within the oil and gas industry is emulsion build-up, particularly in upstream areas of the supply chain. The sensor unit’s active sensing is affected as the emulsion accumulates on the surface of the sensor, preventing the sensor from working correctly and processing data. Here, robustly built sensors are critical to deploy within the oil and gas industry to provide uninterrupted continuous data 24/7.
IoT Sensor Image Processing
Today sensor Technologies and signal recovery electronics are transforming and developing the parameters of what can be measured with accuracy in the oil and gas industry.
The premise of modern IoT device connectivity is based on the usage of sensor Technology to monitor, communicate and signal intelligent processes.
Tomographic Technology is an emerging technology within the oil and gas industry; essentially, this technology conducts a forensic analysis of matters in the flow of oil and gas, so operators can get a better product quality, reduce costs.
Asset Tracking
IoT has presented itself as a formidable use case in tracking non-digital assets across long-range areas.
A growing number of companies deploy sensor technologies connected to wide area network gateways, such as LoRaWAN and NB-IoT- the oil and gas industries are just one of these as an industry with remote factories.
The key to any supply chain is the distribution of end-products to the location of the market. As an international industry, oil and gas container transportation can vary from long-distance ship cargo to lorry drop-offs. Possessing visibility of the oil and gas containers as soon as they leave the factory and enter the store is critical to ensure transparency if any assets get lost. So, discrepancies can be evaluated, and the location of a particular container can be pin-pointed.
Big Data Analytics
The beauty of IoT is the ability to gather influential data to learn, compare and deploy. Like all other industries, the analytics generated from connected devices in the oil and gas enables smarter decisions to be made from information that could otherwise be overlooked.
The Future of oil and gas
For the oil and gas industries IoT is progressively becoming a widely recognised standard to integrate into the supply chain. The demands of oil and gas show no signs of slowing down in the petroleum and Industrial arena, while the digital driven market proves to provide cost effective and sustainable solutions- it looks like the long-term solutions of IIoT are here to grow in this lucrative industry.
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