How The Internet Of Things, Big Data And AI Are Changing Oil And Gas Industry.
In times when the carbon footprint is a frequently discussed topic, the oil and gas sector is among the first who have to take green concerns into account.
Many countries want to decrease both dependency on foreign energy supplies and the level of CO2 emissions. Oil and gas companies, in turn, produce energy locally but also have a high carbon footprint. The industry operations account for?9% of all emissions —both CO2 and non-CO2. Thus, efficiency in energy consumption and energy production are the main priorities for businesses.
Going smart with IoT in oil and gas can definitely add to efficiency. Discover new opportunities whether you’re an upstream, midstream, or downstream business. Check out IoT oil and gas use cases right below.
How to Add Efficiency on Board
You can improve only what you can measure. Add IoT, cloud computing, and artificial intelligence to your business to make your processes smarter.
For upstream companies?
If you’re an upstream business searching and producing natural gas fields and crude oil, your list of requests is huge. These include:
With IoT, you can save time and money with remote control during research and drilling, get more value from extracted materials, and reduce downtime of equipment. Additionally, you can protect workers from incidents if you equip them with wearables.
For midstream companies?
If you’re a midstream team taking care of transportation, you want to send materials to a refinery by tanker ships, pipelines, and trucking fleets on time and without extra expenses. This process needs to be seamless, high-quality, and efficient. IoT on board will save the budget on optimized logistics, better cargo quality, and fewer breakdowns. And also sensors may help you follow the strict regulations of each region you operate in.
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For downstream companies?
If you're a downstream company, you want to distribute and sell the product faster and at the best price. No matter what you offer—natural gas, diesel oil, petrol, gasoline, or heating oil. IoT with predictive analytics in the pipeline will help you forecast demand, find customers with fewer effort, and calculate the best price.
In general, the IOT Services?allow upstream, midstream, and downstream businesses to cooperate more effectively. And even more, going smart with IoT brings companies a more appealing public image. This gives companies a competitive advantage.
As a result, many oil and gas companies take part in decarbonizing the economy. Businesses like?Total and Shell?set targets to drive down carbon emissions—towards zero. Others diversify investments into renewables, energy efficiency, and biofuels. Businesses such as the “first offshore wind major” focus on renewable energy.
3 Core Aspects of Digital Transformation in Oil And Gas
Depending on the business goal, there’re many ways how IoT and related technologies can transform oil and gas companies. Here are the main ones:
1. Asset monitoring. With IoT, you can attach sensors to physical assets and remotely watch a variety of parameters through the app. This can be real-time, historical, and maintenance data. The collected data will help you track performance and detect issues, outages, or dangerous environmental conditions. You can boost efficiency in the fields.
2. Resource monitoring. Data helps oil and gas businesses see the potential of reservoir resources. For example, a network of thousands of seismic sensors can help find the best drilling sites for oil. It’s possible to map surface sites to see new drilling locations and improve the productivity of existing areas. Such a smart search drastically saves time and money. And it makes it possible to predict production volumes and avoid inefficient areas. Moreover, you can track how much customers consume and predict demand.
3. Smart predicting. AI-enabled systems help reveal hidden patterns and make predictions everywhere—from upstream to downstream areas. Smart algorithms detect unusual behavior in smart equipment and take immediate action. For example, you can predict downtime and so avoid costly repairs. It’s also possible to predict volumes of oil and gas production, measure needs, and calculate the price for end users. Regarding logistics, AI can predict time spent for transfer to the refinery. The superpower of AI is that?machine learning solutions?are only getting better over time.