IT in Manufacturing


Predictive analytics for artificial lifts

September 2020 IT in Manufacturing

Machine learning and artificial intelligence applications in artificial lift systems have seen a growth in importance recently and are no longer a nice to have, but essential tools for design, optimisation and failure prediction. Real-time optimisation techniques that help to optimise the production, however, do not necessarily holistically consider the equipment reliability and best operating range.

Whenever a failure occurs, the reasons could be attributed to more than one condition and hence, Root Cause Analysis is often a complicated process involving visual inspection and laboratory analysis to confirm the reason for the failure. The best operating envelopes for the lift system are also at the discretion of the optimisation engineer, who may not visit often enough to account for changing operating conditions. This may lead to the system operating in a conservative fashion leading to reduced production. As an example, a rod pump might operate at a lower speed anticipating high rod stresses based on historical operation. In some instances, the systems might not be designed for the desired operating environment and may pose a threat to its reliability. There is a need for a technology which would serve as a guide to overcome these challenges using real-time diagnosis and provide foresight into future operations and potential problems that may increase operator costs.

Emerson’s predictive analysis for artificial lift using the Knowledge Net (KNet) Machine Learning Platform is an engineered solution for predicting failures or abnormal working conditions before their onset. The solution utilises historical data from the wells to build a solid offline well model, which then gets trained on the real-time data as the well comes on to production. As the lift systems are subject to many complex events that might lead to a potential failure, the principal component analysis helps in the elimination process. With a comprehensive Failure Mode Effect Analysis and Root Cause Analysis library, the solution captures, in real-time, the abnormality and translates it into a potential run time deviation. With a prior indication, the condition can be corrected or interventions planned more efficiently. The dynamic modelling of key performance indicators based on system intelligence help in driving asset performance to identify the priorities relevant to the existing conditions. This widens the scope from mere well performance to complete asset performance enhancement.


Credit(s)



Share this article:
Share via emailShare via LinkedInPrint this page

Further reading:

Looking into the future of machine vision
Omron Electronics IT in Manufacturing
Artificial intelligence (AI) is driving a significant transformation in all areas of industrial automation, and machine vision is no exception. Omron’s AI-powered machine vision systems seamlessly integrate state-of-the-art algorithms, enabling machines to analyse and interpret visual data meticulously.

Read more...
Driving digital transformation in the truck industry
Siemens South Africa IT in Manufacturing
Tatra Trucks, a leading truck manufacturer in Czechia, has adopted the Siemens Xcelerator portfolio of industry software including Teamcenter software for product lifecycle management and the Mendix low code platform to help increase production volume and strengthen its ability to manufacture vehicles that meet specific customer requirements.

Read more...
Opinion piece: Digital twins in manufacturing – design, optimise and expand
Schneider Electric South Africa IT in Manufacturing
Digital twin technology can help create better products, fast. It can also transform the work of product development. This strong statement from McKinsey reinforces how far digital twins have come in manufacturing.

Read more...
Asset tracking is key to driving operational excellence and sustainable growth
Schneider Electric South Africa IT in Manufacturing
Asset tracking plays a critical role in the success of industrial businesses. By effectively managing and monitoring assets, companies can optimise their operations, ensuring that resources are used efficiently. This leads to improved productivity and reduced costs.

Read more...
Siemens democratises AI-driven PCB design for small and medium electronics teams
Siemens South Africa IT in Manufacturing
Siemens Digital Industries Software is making its AI-enhanced electronic systems design technology more accessible to small and mid-sized businesses with PADS Pro Essentials software and Xpedition Standard software.

Read more...
Predicting and preventing cyber-attacks with AI and generative AI
IT in Manufacturing
The speed at which cyber threats are evolving is unprecedented. As a result, companies need to implement state-of-the-art technology to protect their data and systems.

Read more...
Real-world lessons in digital transformation
IT in Manufacturing
Synthesis has helped businesses across multiple industries with their digital transformation by solving their unique integration challenges.

Read more...
Enhancing cyber security for industrial drives
Siemens South Africa IT in Manufacturing
The growing connection between production networks and office networks as part of IT/OT integration and the utilisation of IoT have many benefits for industrial companies. At the same time, they also increase the risk of cyber threats. Siemens ensures that your know-how and plants are protected at all times.

Read more...
Immersion cooling systems for data centres
IT in Manufacturing
The demand for data centres in Africa is growing. The related need for increasing rack densities brings with it escalating cooling requirements.

Read more...
Transforming pulp and paper with automation and digitalisation
ABB South Africa IT in Manufacturing
The pulp and paper industry in South Africa is undergoing a significant transformation from traditional manual processes to embracing automation technologies. Automation in pulp and paper mills aims to improve various production stages, from raw material preparation to final product creation.

Read more...