Learn what's new and what's news in today's digital landscape

What companies use to power their decisions, and how it can impact your business

International Mining


International mining detailed insight into Accenture’s capabilities in helping shape the future of mineral processing. The company sees the value of a connected mine in digging deep into the wealth of data available to provide integrated, end-to-end situational awareness and systemic management, and it has been one of the leading companies helping mines progress from structuring through to implementing data-led transformation with AI.

Riviera Maritime


Riviera Maritime Media’s Vessel Optimisation Webinar sheds light on how participating ship managers and ship owners are using IOT and data analytics solutions to improve sailing performance, reduce fuel emissions and benchmark their fleet performance. The webinar also shared the latest options available to ship owners in terms of telemetry, connectivity and comprehensive data platform solutions as well as the significant ROI achieved.

Riviera Maritime


An interesting panel of technical experts at Riviera’s “How operators use data to optimise engine performance” webinar discuss the powerful combination of engine condition monitoring with ship performance analytics to optimise their vessel, and the key procedures and technologies to successfully lower fuel costs, reduce emissions, minimise propulsion issues.



Using machine learning, researchers at Texas A&M University have developed an algorithm that automates the process of determining key features of simple hydrocarbon reservoirs. Simulating the geology of the underground environment using reinforcement Learning can greatly facilitate forecasting of oil and gas reserves, predicting groundwater systems and anticipating seismic hazards.



Data analytics paired with predictive maintenance can be a virtual goldmine for mining operations, with initial cost reduction and productivity gains amounting 10% to 20%. This article outlines the strategy adopted by miners such as Barrick Gold to save millions of dollars due to their newfound ability to detect and address failures early on, as well as reduce the number of failures from engine, brake or suspension by 30%.

Enterprise AI


Learn how Shell, C3.ai, Microsoft and Baker Hughes choose to solve complex industrial problems with smarter collaborations. The Open AI Energy Initiative aims to grow AI use across the energy and process manufacturing industries by creating new AI and physics-based models, monitoring, diagnostics and more to help solve critical industry needs.

PWE Magazine


The reliability of brake systems for key mining components is crucial to maintain peak productivity and throughput. Svendborg shares how clients can upgrade their systems to reduce the time and cost associated with on-site inspections and maintenance activities. Their solution combines IIoT and data analytics technologies to offer remote, real-time monitoring and predictive maintenance to their braking systems.



Discover what oil and gas majors are doing to optimise their assets, reduce non-productive time and lower operational costs. The article shares interesting example of the use of deep-learning models for optimized drilling and production, predictive maintenance solutions to forecast equipment breakdowns before they can have an adverse impact on their KPI and bottom line to adopting AR/VR for subsurface studies, training, maintenance and planning.

Maritime Logistics


ABS classification society SVP discusses how a digital strategy applied to an FPSO can impact its entire value chain, from equipment and inventory to operational efficiency, including optimization of inspections and onboard activities. Coupling these digital solutions with traditional risk-based inspection and maintenance planning techniques has shown a 10:1 ROI opportunity over the total asset life due to optimized repair and inspection planning.



Plantservice editor shares six case studies illustrating some of the numerous ways predictive maintenance and Prescriptive maintenance are transformative. Clear benefits in preventing costly unplanned downtime and lower costs have improved financial justification and driven adoption in a wide range of industries.

Oil & Gas Engineering


Dr Kanokogi from Yokogawa shares how harnessing data analytics and AI can augment decision making when dealing process abnormalities in petrochemical plants. Two case studies illustrate the power of Artificial intelligence in identifying the main factors contributing to abnormal situations and pointing out the specific sensors indicating the causes. The operators can then concentrate on much smaller number of manageable elements to solve the problem.

Algorithm X lab


It’s a matter of time before Machine learning is heavily embedded in every oil & gas project. AI and data analytics technology is perfectly adapted to augment engineers in tackling the complexities of Oil and Gas projects from geological modelling, drilling operations to asset operation and maintenance. Predictions by McKinsey suggests that adopting AI and machine learning in oil & gas supply chains could gain $50 billion in savings, increasing profits.

Reliability Connect


A great example of one of the world’s largest gold miner integrating an asset optimization system with IIOT wireless sensors to monitor critical assets throughout their operations. The wireless Predictive Maintenance program paid for itself within six months and demonstrated increases in asset reliability, personnel efficiency and production. Discover how asset data is automatically collected and analysed with machine learning algorithms to predict equipment problems.

Oil & Gas Engineering


CEO of Deepwater Subsea shares how his firm help its oil & gas clients avoid BOP downtime and incidents. Using Seeq software’s unique analytics capabilities, SMEs at the monitoring center apply their domain expertise to help detect BOP system anomalies. What’s more is that this innovative service allowed the operators to obtain approval from Bureau of Safety and Environmental Enforcement to extend BOP testing intervals from 14 to 21 days, saving them $10 million annually per rig.

The Maritime Executive


Engine manufacturer Wärtsilä is leading the way with its remote support with condition monitoring systems including Expert Insight, Wärtsilä’s unique predictive maintenance product, which utilises artificial intelligence (AI) and advanced diagnostics. The solution is expected to deliver an estimated 50 percent reduction in unplanned maintenance requirements, and an improvement of 2 to 5 percent in fuel efficiency.



Shell’s Data Science Manager shares with AI expert Bernard Marr what it takes to successfully scale a data strategy within large organisation. The key is to think about project application that are going to have a significant business impact immediately and use that to inform the KPIs that really matter to the business. Then, line up to that, which data really matters and how to invest in data quality, data standards, and technology to support doing this at scale.



Well trajectory planning is a high-stake and complex multi-disciplinary work activity for Oil & Gas operators. White space energy co-founder Norbert Dolle proposes a collaborative game-based approach to well trajectory planning supported by Artificial Intelligence. Using AI as a virtual player, this approach leads to a complete overview of the option space, and associated trade-offs across different business drivers, at a fraction of the time that it takes manual workflows to give similar insight.



Today, technology options and how they’re delivered is simply incredible. What once required dedicated real estate, skilled employees and loads of time can be fulfilled remotely via the cloud or by dedicated companies that charge a subscription fee for a service. Organizations have more options because they can afford the latest and greatest technology without having to find a large bucket of funds upfront to pay for it; this frees up cash for investments and other projects that drive revenue and growth.



This article intends to provide business leaders in the oil and gas space with an idea of what they can currently expect from AI in this industry. 4 Software vendors share how they helped early adopter operators implemented advanced predictive analytics, which combines engineering, data science, and computing power to enable engineers forecast yields, predict failure events and maximize industry assets.

Harvard Business Review


John Deere went from selling machinery to become a data driven company. Learn how John deer is innovating through the internet of things and data analytics to help farmers improve their operations, bottom line, and ability to feed the world. Data, including crop management data and machine operation data, is collected from sensors embedded both in the machines and in the field. The value created for farmers is improved productivity, increased efficiency, decreased downtime, and reduced costs to ultimately maximize profitability.

Offshore Engineering


Eric Haun shares how industry innovators are leveraging advanced sensor technologies, big data, and real-time analytics to foresee and prevent costly component failures. According to a study published in 2018 by the Oil and Gas Authority, Technology Leadership Board, the adoption of data analytics and digital technologies for asset maintenance and operations could increase production and lower maintenance costs, presenting a value of £1.5 billion ($1.8 billion) annually to the UK continental shelf (UKCS) alone.

Plant Services


In every industry and across the world, companies driven to improve reliability at their facilities are testing and investing in new ways to optimize their assets. Their efforts are paying off in greater uptime, efficiency, safety, and cost savings. Experts at seven different industrial companies describe their PdM and RxM progress, including successes that are helping keep their programs alive. Here are their stories, followed by some examples of AI enabling solutions.



Wärtsilä follows through on their data strategy with the deployment of their updated Condition Monitoring Service. The service allows Wärtsilä not only to automatically detect a possible future failure but also to schedule and carry out the required maintenance in a way that minimises stoppages and costs and maximises operational efficiency for the customer. The CMS can be installed on all kinds of vessels. Going forward, Wärtsilä intends to expand the scope to include all types of rotating equipment.



Raghav Bharadwaj debates how AI-enhanced data search and discovery might soon be applied in the oil and gas industry across many business functions, such as production and maintenance. There are several marquee commercial offerings using NLP, that enable oil and gas companies to organize their internal data in ways which make it easy for employees to search and discover patterns that could optimize their business processes and solve issues more efficiently.



As machinery becomes more complex, Artificial Intelligence and automation stand greatly to enhance the performance of CBM systems, relying less on the rigid rules of engineering and more on the flexibility offered by ML algorithms. Wartsila share their point of vue on how the combination of raw processing power of an AI system with the deep understanding of equipment experts can create the CBM system of the future to support their customers in managing their complex assets.



Flicq CEO Karthik Rau is laying the groundwork for an innovative IoT technology that uses smart sensors and proprietary algorithms to address operational and technical challenges in the construction industry. The technology uses data processing at the “edge” to provide information about the health of mechanical assets like pumps, elevators, and HVAC compressors which can be used to increase uptime and reduce maintenance costs.

Hart Energy


SparkCognition VP of Oil & Gas explains how AutoML opens up the full potential of predictive maintenance to the oil and gas industry. Auto ML platforms help organisations scale predictive maintenance projects by ingesting operational sensor data and automatically build machine learning models that predict the operating state and remaining useful life of a given asset. This reduces the time required to create models by orders of magnitude.

Marine Link


Ship owners and operators, machinery OEMs and regulatory entities are embracing much needed technological innovation to manage aging and ever complicated maritime assets. Walter Mitchell makes his case on how predictive analytics platforms can greatly assist shipping operators by allowing for more precise planning of maintenance and capital replacement. The result is that the life of the machine can be extended, yielding stronger control over maintenance and capital equipment replacement budgets.



Microsoft articulates how they collaborated with Rolls Royce to target big data use cases in predictive maintenance and fuel efficiency. As the rapidly increasing volume of data coming from many different types of aircraft equipment IOT overtook the airlines’ ability to analyse and gain insight from it, Rolls-Royce implemented the Microsoft Azure platform to fundamentally transform how it uses data to better serve its customers.