How AI and Annotation are Changing the Oil and Gas Industry

In the never ending search for growth and efficiency savings the oil and gas industry is turning to computer vision based AI models. Machine learning technologies can help to stabilise profits in an unpredictable world and changing market. The digitization of the industry also promises to improve worker safety and prevent costly and environmentally damaging accidents during production.

AI systems that operate in the oil and gas sector must be capable of functioning reliably in varied and complex environments. In order to achieve this level of functionality AI developers must train their models with precisely annotated image and video data. Experienced annotation providers, like Keymakr, are collaborating with computer vision leaders to secure the future of an evolving industry.

This blog will focus on some of the promising applications for AI in the oil and gas industry. In each instance we will show how professional annotation services can help support innovation.

Exploration

Computer vision can be used to improve the exploration process, increasing the likelihood of a successful drilling operation. Machine learning has been applied to images from seismic studies. These images are created by bombarding the ocean floor with soundwaves to construct a detailed picture of the earth’s subsurface. AI models can be trained with these images, allowing them to identify potential areas of promise for oil and gas exploration. By automating analysis of this nature AI developers hope to improve the efficiency and accuracy of drilling in a diverse range of locations.

Quality and precision are essential qualities for training data. In the case of subsurface analysis mistakes made by AI models could result in enormous costs, or leave potentially promising locations undrilled. Annotation service providers are best placed to deliver accurate datasets due to robust internal quality control processes.

Drilling

AI can also play an important role once oil and gas deposits have been located. Drilling operations on land can cover large areas involving many rigs and industrial facilities. Monitoring and inspecting these locations can involve extensive amounts of travel, which is inefficient and could lead to problems being missed.

Osprey Informatics is one of the companies hoping to automate this monitoring workload with the help of computer vision AI. Their monitoring systems are able to recognize specific events and send reports to field managers, allowing them to assess whether a site inspection needs to be made.

This technology can significantly reduce the need for time consuming visits, whilst maintaining high levels of vigilance across large scale drilling operations.

Video annotation is an important component of the training data for these kinds of monitoring systems. Professional annotation services can relieve developers of this labour intensive task, and accelerate annotation with proprietary platforms.

Predictive Maintenance

Damaged or malfunctioning equipment can result in accidents that endanger human life and create harmful pollution. Problems with drilling hardware can also shut down oil and gas production resulting in millions of dollars worth of losses.

AI powered predictive maintenance systems can help to prevent these costly failures by monitoring equipment and providing operators with advanced warning of potential issues. This technology can analyse equipment for defects that may be invisible to the human eye, or it can be deployed to recognise deviations from normal behaviour in drilling subsystems.

Security is always a pressing concern for AI developers working with images and video featuring sensitive operational information and technology. Experienced annotation providers follow strict standards when it comes to protecting private data, often deploying encryption to ensure it remains secure.

Advanced annotation services

Streamline your machine learning project with Keymakr. Take advantage of cutting-edge annotation tools and an experienced, in-house team of annotators.