How AI / ML plays a key significance in the oil and Gas Industry – Express Computer

  • Lauren
  • August 25, 2022
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By Sujit Patel, MD, and CEO, SCS Tech
Digital Transformation solutions for the utility sector integrated with intelligent analyticsprovide insights both in form of visual graphics and debriefing reports. Artificial intelligence (AI) is one of the key technologies that will propel organizations through Digital Transformation. Though AI serves all industries in varying degrees, the industry that stands to gain the most could be the Oil & Gas sector. Oil & Gas production is one of the most lucrative albeit risky sectors to work in. The use of artificial intelligence improves productivity, and security, monitor controllable losses in real-time, boosts equipment and resource availability, and enhances business processes.
The system provides operation and management support to monitor the important KPIs. The unified data platform for utilities disseminates data in real-time for incidence management, predictive analysis, root cause diagnostics, language localization, and intelligent debriefing report generation.
Here are some ways where AI is addressing different issues in the sector.1. Analytics-based decision support system Oil and gas firms deal with a lot of data produced by their processes, but often lack the proper analytics tools to make use of the enormous amounts of data stored in data silos. Companies can employ data engineers to manually analyse data to draw insights, but this is time and cost intrinsic. The alternative is to deploy applications that mine vast amounts of operational data for intelligence and meaningful insights. Artificial intelligence can segment the data and look for trends or discrepancies to extract predictions from massive data sets. AI algorithms analyze multiple data streams from various sensors and machinery of various plants in order to provide intelligent recommendations based on business requirements. These in-depth insights help geoscientists comprehend the operation and process as a whole, enhancing their capacity to make strategic decisions. This boosts operating efficiency while cutting expenses and even lowering failure risk.
2. Error detection and quality improvementA challenge in the oil and gas business is identifying faults in processes that are prone toerror or poor pipeline threading. Resources are used up by issues that result in errors during the production process. For instance, serious injury could result if an equipment or oil pipeline with a flaw is put into use. In comparison, the expense of using AI is significantly less than these losses. The use of a computer vision-based system can provide comprehensive analytics on any defects as well as confirm the production's quality. When compared to normal techniques, AI-powered defect detection solutions are relatively inexpensive and cost-effective.
3. Reduction in operation and maintenance cost
Before being transferred via pipelines, oil or gas that has been extracted using oil rigs isstored in a central area. Variable temperatures and external variables typically cause material degradation and corrosion in oil and gas component parts. The resulting component deformation and degradation can weaken the pipelines. If this problem is not solved, it could have disastrous consequences and stop all production. Companies need corrosion engineers to handle and monitor component health in order to prevent corrosion as this is one of the main problems the industry is currently facing. Artificial intelligence (AI) technologies can assist prevent such events.
Artificial intelligence (AI) and Internet of Things (IoT) technologies can identify corrosion indicators and warn pipeline operators of potential issues by analysing various factors with the aid of knowledge graphs and predictive intelligence. Companies can analyse insights and graphs to examine various machinery downtimes and estimate the ideal time to undertake maintenance operations by managing corrosion proactive in this way. Companies can make necessary adjustments to manage downtime.
4. Maintain high levels of security and safetyOil and gas facilities operate in such dangerous situations that the risk of harm issubstantially higher than in conventional manufacturing settings. Employees in oil refineries occasionally have to breathe harmful gases while working in a variety of temperatures and around numerous moving parts. Failure to follow adequate safety procedures can lead to accidents and financial penalties. Companies are required to abide by safety rules that are mandated by law.
The penalties for breaching these laws are severe. The majority of activities are still manual, such as manually monitoring camera feeds or carrying out physical safety sweeps, to guarantee that safeguards are still effective despite the plethora of data available to monitor safety risks. The current methods only guarantee that employees are following guidelines at the plant’s entrance, not all day long.
Ensuring that workers carefully follow safety regulations on the working site can be donewith the help of an AI-powered computer vision system. The video data is given to an AIalgorithm, which analyses it to send alerts and proactive recommendations. AI solutions can notify managers of even the smallest compliance infractions.
5. Chat-based assistanceField operators can benefit from virtual agents and chatbots, and by incorporating a voice-enabled component, they can carry chatbots with them wherever they go. Operators needto constantly travel from one place to another and must keep their hands free. The use ofhands-free speech commands to interact with voice-activated devices will be a big help toask queries and get status updates. Chatbots are great providers of information becausethey can pull real-time data, handle jobs like responding to support queries, and giverelevant instructions from an internal knowledge base.
Compared to other industries, employee transfer in the oil and gas sector is the biggestbarrier for the company. Maintaining intelligent chatbot results in the creation of a central repository for past and current data which can help new hires inducted at a fasterspeed. In each of the aforementioned scenarios, companies can receive additional guidance and real-time insights based on crucial data by deploying AI-based Digital Transformation tools and techniques.