Right now, there is a lot of discussion concerning humanity's carbon footprint and its impact on physical geography and global ecosystems. We are experiencing a shift in global climates, much of which has been attributed to the vast amounts of CO2 created through combustion fuel energy sources like Oil and Gas. The increased emissions are directly causing vast amounts of natural land to become unlivable and countless species to die off in alarming numbers. It has been called the beginning of the next extinction-level event but isn't a one-off catastrophe like a meteor striking the earth's surface. Scientists worldwide agree that we must stop global warming by minimizing greenhouse gasses, but this shift isn't without its challenges.
If we want to benefit the planet by reducing greenhouse gasses, the entire Oil & Gast industry must shift how they operate on a fundamental level. Embedded AI with advanced machine learning and big data IoT (internet of things) analysis is helping do just that by making the oil and gas industry more efficient and less destructive to the natural world.
Major oil and gas producers are digitally transforming their entire business, from IT systems to drilling, discovery, logistics, personnel management, and so much more. Let's see a few ways this is happening with AI.
Embedded AI is proving itself a powerful asset for operators in the oil and gas sector, and we're only scratching the surface of what AI will offer the industry next. The list is long and growing. From better-optimized drilling practices to equipment predictive maintenance, AI has a lot to offer:
When drilling and refining go down, it can cost operators millions of lost revenue and productivity in a short period. Through leveraging AI, O&G companies enhance their ability to predict when and where equipment needs to be serviced, through IoT sensors & AI analysis, so that unplanned downtime gets minimized and productivity isn't lost. For exploration & mining, an example is vibration sensors throughout a drill site, which measure the energy and movement in a space. AI gets trained to understand expected vibration levels and signs of a well near collapse. The system informs operators when a well is at risk of failure so they can reinforce its walls or move to a different site. Here, embedded AI decreases downtime and improves worker safety.
Overscheduling is a significant problem in the offshore oil industry. Some of this is due to weather delays that happen on the ocean. Others are due to poor scheduling of personnel transports to and from offshore drill sites. When so many pieces of equipment and workers must coordinate schedules to be in the right place at the right time, mistakes are common when left up to human managers or schedulers. Edge cloud operators using AI examination can determine when and where equipment & personnel should be at a given moment in the production cycle, reducing over-scheduling & scheduling conflicts without an HR manager setting schedules.
AI is proving a boon for leaders in Oil & Gas exploration. Because most global drill sites are hazardous, considering the enormous pressures of ocean water and rock, AI-assisted robotic equipment makes exploration less detrimental to the environment and more efficient. AI platforms are being utilized to investigate subsurface geological data to map underground oil & gas deposits accurately. In the past, it was more or less guesswork, sometimes a well would have a lot of oil, and sometimes it would not, but using AI now minimizes wasted time and energy as it prevents drilling operations in zones with low output potential without having to drill into large sections of the earth.
Equipment & machinery is critical to every area of O&G. When equipment fails, it can lead to costly downtime and lost revenue along every step of the supply chain, not to mention higher prices at the gas pump or to heat homes. AI can help validate production output quality and provide insights into failures in analytics.
AI-enhanced equipment failure detection is highly cost-effective compared to how machinery failure has been detected historically (which is waiting for it to stop working). Pattern recognition using machine learning allows AI to use videos recorded by cameras to notify operators if the equipment malfunctions or personnel is not wearing proper safety equipment. This helps prevent dangerous conditions for employees and helps minimize downtime due to failing equipment as it is detected and fixed before going down.
Oil & gas companies are some of the most targeted businesses for cyber-attack. This is for a few reasons. One is the vast number of sensors and connected devices used in the embedded IoT infrastructure of O&G companies. The more connected sensors and devices, the greater the number of attack vectors bad actors can exploit to compromise a system or steal sensitive data. AI-enhanced cybersecurity, with blockchain technology, is making every aspect of the oil & gas industry more secure. Whether from physical attacks or cyber threats, AI can analyze huge amounts of data in real-time and quarantine areas of a network compromised by a hack. Decentralized AI keeps cyber-security fluid and malleable, making it ideal for the increasing complexity of attacks facing O&G companies.
Many larger oil & gas companies have recently set lofty ambitions of achieving net-zero emissions. Of course, companies that extract combustion fuels from the planet will have a lot of work to do to meet that goal, and AI is helping them achieve them. Oil producers are deploying AI-enhanced software to measure and track the volume of emissions that escape from different points of the supply chain, like oilfield equipment or pipelines. Whether upstream or downstream, AI has some advantages to ensuring the least loss. Suppose AI detects a particular mile of a pipeline is experiencing leaks. In that case, the system can alert maintenance crews to resolve the issue and mitigate the further uncontrolled release of CO2.
When working in the O&G industry, there are several risks and dangers to employees that don't exist in other sectors. Considering the size of equipment, pressures, temperatures, chemicals, and violence risk when drilling, extracting, or refining oil & gas, worker safety is something every operator takes extremely seriously. AI in upstream oil and gas can monitor asset location, GPS worker location, pressure & temperature metrics, and even if an employee is wearing the proper safety equipment.
For instance, if temperatures in an underground drilling site are becoming too high for safe operations, the AI will alert operators to warn staff to stop what they are doing and get to safety. AI with machine learning can be trained to measure worker body temperature, preventing anyone from showing signs of a fever from entering the job site and putting themselves and their colleagues at risk. AI-powered robotic equipment also removes the need to put people in dangerous positions, and in the O&G industry, there are many.
When inventory doesn't match demand, companies lose clients and suffer a hit to their revenue or market share. AI allows companies to improve efficiencies in network planning and demand prediction analysis. For example, AI can measure expected fuel consumption during the summer vacation season in the USA based on current consumption at specific prices and previous years' analysis. AI can inform operators of the expected barrels per day they should be producing to match demand. This way, the global market has the right amount of Oil & Gas at any given moment. Or, if they want to raise prices, when and where to cut production & delivery.
Embedded AI is changing how O & G companies maintain and monitor, plan projects, train staff on complicated equipment, and manage the lifecycle of a project using digital twin (DT) technology. A "Digital Twin" is a virtual model of a physical object. It uses big data analysis to span an object's lifecycle and real-time data from sensors to simulate behaviors and operations the object (device) will be doing in the real world. For O&G companies, this is a massive boon regarding things like training new personnel.
Consider training a new team member on an oil container transport ship. In the past, you would have to individually train a new team member in a way that had little hands-on experience (book & classroom learning) and took time away from the person's day who was doing the training. With a digital twin, trainees can get a "real world" understanding of a particular object's safety requirements, functions, and operation by "doing it" in a digital environment. This way, when it comes time that they are working on the container ship, they already have experience in all of the different parts and safety requirements for the device or object. This saves companies vast amounts of time and cost to train new employees and has a massive benefit as new workers can be onboarded efficiently.
The oil and gas sector has some of the most complicated and interconnected supply chains of any industry. The supply chain is complex and extensive, from production to inventory purchase or sale, transportation to and from a refinery, then a port, and ultimately a gas station or delivered to heat a home. There are many moving parts with many different operators, making embedded AI ideal for streamlining these logistical behemoths. AI is useful for coordinating the operation teams with warehouse & shipping to ensure the correct availability is ready at different points on the chain.
AI supports planning and execution in midstream businesses and helps determine optimal routes, shipping times, and expiration dates. When oil tankers reach their final destination, a smart port outfitted with embedded AI efficiently unloads inventory and ensures staff and equipment are in the right place at the right time. Smart warehouses manage inventory in much of the same way and ensure operators are as efficient as possible with the least wasted time and cost.
IoE Corp has developed a completely decentralized artificially-intelligent edge-cloud platform ideal for the complicated digital transformation oil & gas companies require. Having in-house blockchain and AI expertise isn't common, even for the largest and most profitable companies like Exxon Mobil. For this reason, technology partnerships are the correct path forwards.
IoE Corp, professional services consulting, is already working with operators across infrastructure with the Eden platform and is likely a great fit to fast-track your digital transformation. Eden is open for partnership applications. Please fill out the form, and a partner outreach concierge will contact you soon to learn more about your specific pain points and problems to solve with the right tools.
