AI (Artificial intelligence) refers to the use of computational and other forms of artificial representation to mimic intelligent human behavior. Applications of AI range from expert systems and NLP (Natural language processing) to speech recognition and machine vision.
How does Artificial Intelligence Work?
There has been a massive spike in the public’s fascination with AI, thus companies are rushing to advertise how their products and services benefit from the innovation. Most instances of the term “artificial intelligence” (AI) are referring to a specific subset of AI, such as machine learning. Yet, the scope of AI extends much beyond those specific talents.
The development of artificial intelligence (AI) requires a set of tools comprised of both hardware and software. This paves the way for the development and education of machine-learning algorithms. Some of the more popular programming languages for AI work are Python, R, and Java. The term “artificial intelligence” (AI) does not refer to a single programming language.
In general, AI systems function by taking in large amounts of labeled training data, analyzing that data to find correlations and patterns, and then applying those correlations and patterns to forecast the future. With this approach, which involves analyzing human text chat samples, a chatbot can be trained to have natural interactions with humans. Millions of examples could help a computer algorithm learn to identify and label objects in photos.
Industries and Technology
The advent of artificial intelligence (AI) is having a profound impact across practically all business sectors and fostering innovation at every turn. Nearly every industry is exploring new applications for artificial intelligence (AI) technology.
A few of these methods are exceptionally innovative, ranging from financial technology to educational technology to even agricultural technology. These cutting-edge uses of artificial intelligence are helping propel the entire field of AI into the future.
Use of AI (Artificial Intelligence) in the Oil and Gas Industry
One may argue that every industry could benefit from AI; nevertheless, even if this were true, the oil and gas supply chain might be the one with the highest potential for AI’s use. Despite being highly profitable, working in the oil and gas business is among the most dangerous occupations there are. With AI in the workplace, efficiency, output, and safety are all improved.
The following are five ways that AI is helping the oil and gas supply chain solve various problems it faces.
Improved Quality Assurance and the Detection of Defects
One of the difficult issues faced by personnel in the oil and gas supply chain is detecting faulty pipe threading or flaws in error-prone devices. Flaws discovered at the end of the production line wind up costing the firm and the budget money due to issues that occurred earlier in the process.
Consider the potential cost of resuming production with a broken oil pipeline or piece of machinery. These losses far outweigh the expense of implementing AI systems. The role of AI in facilitating the growth of the oil and gas industry has been important.
The role of artificial intelligence in the expansion of the oil and gas industry is best illustrated by a computer vision-based system that can be used to check the quality of production and give engineers more insights into the analytics behind problem-solving. Defect Detection systems powered by artificial intelligence are very cheap and efficient compared to the standard methods now used.
Maintain a High Level of Safety and Protection Standards
The risk of injury in oil and gas processing plants is substantially higher than in other production facilities due to the extremely hazardous working conditions. When weighed against the potential for harm at other manufacturing sites, this is significantly lower.
As well as dealing with fluctuating temperatures and potentially dangerous gas levels, personnel in the oil industry must also keep track of numerous moving parts. Additionally, they are frequently subjected to noxious fumes. Physical injury, legal implications, and monetary penalties may result from disregarding necessary safety requirements.
At the Tesoro Martinez Refinery in California, two workers were harmed when sulfuric acid spilled. Something spilled, leading to the mishap. The accident occurred when acid was let loose. When explaining what happened, Tesoro authorities acknowledged the accident might have been avoided if workers had followed basic safety procedures.
Companies have a legal obligation to follow the government’s security standards. Your financial status will be severely impacted if you do not meet these requirements. Surprising amounts of data may be used to track potential dangers, but the success of safety measures still relies heavily on human intervention. Here’s an example: As a result, it may be necessary to physically inspect the premises or to keep an eye on the cameras.
This verification does not run constantly throughout the day. Computer-vision technology enabled by artificial intelligence (AI) can be used to keep a close eye on the workplace and catch any violations before they become serious problems. Using the video’s data, an AI algorithm will analyze the situation and provide recommendations for how to prevent more harm. Even the smallest violations of compliance can be flagged by artificial intelligence (AI) systems and reported to upper management.
Decrease the costs of both production and maintenance
After being extracted using drilling rigs, crude oil or natural gas is first carried to a central storage facility. From there, it is transported by pipelines to its ultimate destination. Parts used in the oil and gas industry are vulnerable to a wide range of issues, such as material deterioration and corrosion, due to the extreme temperatures and environmental conditions encountered throughout the industry’s operations.
Corrosion can induce the deformation of components, which can result in a loss of threading or even a weakening of the pipeline itself. Corrosion might also decrease the threads’ efficiency. If you don’t fix this, it could result in severe damages that would cease manufacturing immediately.
Corrosion engineers are essential to businesses because of the work they do in keeping track of the condition of components and taking preventative measures to stop corrosion. The fact that this is one of the most pressing issues confronting the sector is a major one. The use of AI to aid in the growth of the oil and gas industry might significantly simplify the process of resolving all these issues. The Macondo Incident is one example, popularly known as the BP Oil Spill.
One of the most significant oil and gas accidents ever was largely considered to have occurred. In the research papers written after the post-analysis was complete, inadequate performance of the maintenance function was mentioned as one of the key variables contributing to the occurrence. It was important to do inspections to ascertain the present state of the components as part of the procedures for maintaining the equipment. The safety system was also discovered to have been unplugged at some point, which likely contributed to its lack of functionality.
Artificial intelligence (AI) based solutions may one day be able to prevent this kind of tragedy from happening. To anticipate the risk of corrosion occurring and warn pipeline operators, artificial intelligence (AI) and internet of things (IoT) technology may evaluate several criteria using knowledge graphs and predictive intelligence. This opens the door for IoT and AI systems to detect and prevent corrosion. Furthermore, knowledge graphs allow organizations to analyze the downtimes of various pieces of machinery and predict when it will be necessary to carry out repair actions.
When businesses function in this way, they are better able to manage corrosion risks through preventative measures. With this plan, businesses may adjust and get ready for outages ahead of time.
Use Analytics to Help Make Better Decisions
Companies can employ data engineers to analyze data to draw insights manually, but this is a limited option in terms of time and cost. In addition, no data engineers could get through all the data produced in a single day of operations.
AI systems that power Big Data can extract intelligence and meaning from vast amounts of operational data. With artificial intelligence, massive data sets may be broken down into more manageable chunks of information, which can then be analyzed to look for trends or discrepancies and used to inform forecasts.
AI algorithms examine numerous data streams from various sensors and pieces of machinery located in multiple plants or from the entire body of data pertaining Because they lack the appropriate analytics tools, oil and gas companies cannot capitalize on the massive amounts of data stored in data silos, even though they deal with a lot of data coming from the manufacturing processes.
Because of these profound insights, geoscientists can have a better awareness of the overall processes and activities, which in turn enables them to make more informed strategic decisions. Because of this, the operations become more efficient, costs are cut, and there is even less of a chance that they will fail.
Integrate Helpful Voice Chatbots into the Systematic Platform
Chatbots and virtual agents benefit field operators and adding a component that enables operators to take chatbots with them into the field allow them to benefit from chatbots and virtual agents. The following is a list of different applications for voice assistants designed for field workers. Because operators are constantly moving from one location to another, they must have full use of both hands.
Chatbots that are speech-enabled can provide operators with assistance in the form of queries and status reports, all through hands-free voice commands. Chatbots are a fantastic source of information since they can pull real-time data, manage duties such as dialing for support, and deliver proper instructions gleaned from the internal knowledge base.
The upkeep of intelligent chatbot results in the creation of a centralized location for historical data. The use of a chatbot can help new employees get up to speed more quickly. When compared to other fields of work, staff turnover in the oil and gas industry presents the most significant obstacle for the business.
In each of the situations described above, operators can receive supplementary aid when making decisions and accessing vital data in real-time. Operators confronted with a faulty piece of machinery can ask a chatbot any inquiry, including how to rectify the problem.
Some other helpful uses of artificial intelligence in the Oil and Gas Industries are:
- Backoffice Process Optimization
- Smart Inventory Management
- Surface Analysis/Geological Assessment
- Optimizing Production and Scheduling
- Reducing Well and other Equipment Downtime
- Using Digital Twins for Asset Tracking and Maintenance
- Artificial Intelligence led Cybersecurity
- Tracking of Emissions
- Logistics Network Optimizations and Logistics
Use of AI in other industries
Detecting and Preventing Fraud
The ability of artificial intelligence to recognize patterns enables it to play a critical role in the development of financial technology. Financial and credit organizations are using AI to detect fraudulent
activity and secure their clients’ money and data. It could be several days before a cardholder realizes that there was an unusual transaction made on their account. On the other hand, an AI can rapidly recognize suspicious conduct and take appropriate action. For instance, it may recognize that a transaction does not correspond to the usual things that a person buys and question why this occurred.
Artificial intelligence is also able to identify strange IP addresses or shipping addresses. When the AI detects questionable purchase activity like this, it will put a hold on the transaction to validate whether it is legitimate before allowing it to proceed.
In Food Sector
It might surprise some people to learn that AI is completely transforming the food business. Researchers have developed a robot that can autonomously recognize ripe apples in an orchard using computer vision and deep learning.
The robot can then pick the apples from the trees on its own. By utilizing a specifically developed claw, the robot can successfully gather one apple every seven seconds. Gathering pretty much any other kind of fruit or vegetable might also benefit from applying this technique. The agriculture industry will be able to better supply the rising demand for fresh food around the world with the assistance of farming robots.
Anticipating the Need for Maintenance
It is necessary to perform routine maintenance on industrial vehicles such as those used in the construction industry to keep them operating. On the other hand, considering the size and complexity of these vehicles, significant repairs can be exceedingly expensive.
AI is making maintenance much more straightforward, safer, and cheaper to perform. AI can monitor a vehicle’s performance over time and identify fluctuations in that performance that may suggest the need for repair with the use of sensors connected to the internet of things (IoT). Tune-ups can be performed on vehicles by their owners or operators before more significant repairs are required.
Enhanced focus on quality control
It is getting harder to keep up with demand since an increasing number of companies are having trouble finding qualified workers. To satisfy the needs of their customers without lowering their standards, manufacturers require a workable answer.
Artificial intelligence is seeing a transformative effect on production lines and factories all around the world. Computer vision and sensors embedded in Internet of Things devices allow artificial intelligence to examine products for quality flaws. Even a single AI-enabled camera might be mounted on a robot arm to scan a large object.
Artificial intelligence has been trained to recognize both the unaltered version of the thing as well as significant indicators that the item is flawed. Because of this capability, quality control may be efficiently automated, which increases both the efficiency and the quality of production.
Teaching Appropriate Social Behaviors
AI companions for children are becoming a commonplace phenomenon, even though the concept may sound like something out of a work of science fiction. Children are benefiting from the use of robots powered by AI in the development of their social and life skills.
For instance, natural language processing (NLP) enables the Moxie robot to have convincing conversations with youngsters. It teaches essential life skills as well as critical social abilities such as consideration, empathy, and respect. Moxie will even play games with youngsters, such as sketching and meditating with them. More robots like Moxie will inevitably be developed as internet education and homeschooling gain popularity.
The Process of Designing Buildings
Generative design is one of the most interesting next-generation applications for artificial intelligence (AI), and it is currently being utilized to design revolutionary new structures and buildings. When given a set of parameters, AI algorithms may often come up with unique solutions to architectural difficulties.
One example would be identifying the optimum support system with the least amount of materials. Even architects are finding that generative design facilitates the development of original and artistic new construction concepts. In addition to being employed in the creation of buildings, generative design is also used in creating robots, dwellings on Mars, and numerous other consumer products.
In short, it could be said that AI has played a significant role in increasing the market growth of oil and supply chains. Robots driven by autonomous artificial intelligence would be an excellent answer for exploration, as they would make the procedure more straightforward and more accurate data would be gathered.
Drones are being used by leading oil and gas corporations to capture seismic photos, while algorithms for processing photographs extract information from the images. The results of these analyses are used as the basis for subsequent research. This procedure reduces the risk to human life while maximizing the data’s reliability.
How will artificial intelligence impact upstream oil and gas?
Exploration of oil and gas reservoirs necessitates 3D imaging of the field and data processing from petrophysical and geophysical studies, including seismic surveying at the scale of the pool. AI lowered the time required to process these 3D photos, a normally time-consuming task.