Management Perspectives

The much-hyped oil and gas industry too is facing several challenges during the ongoing pandemic days. Weakening of the financial performance of several industry majors is the most daunting among the challenges being confronted by the industry. Consumer demands are changing, new energy resources are emerging, unconventional oil and gas resources are being developed, the significance of emerging economies like China and India is increasing, and a host of other factors are contributing to market depression.

Oil demand is peaking through lockdowns and travel bans, while prices have plunged well below the level needed to turn a profit. Companies are bringing down capital expenditure and thus try ingto drive down operating costs. Back in 2006, the average return on capital employed in upstream activities among oil majors stood at more than 27 per cent, a recent study by Boston Capital Group revealed. In 2019, that average was no more than 3.5 per cent. That is before the pandemic pummelled oil prices and forced severe spending cuts. The oil industry’s returns, the study showed, had become much less resilient to price movements. Harnessing the potential of digitalisation throughout the industry and achieving consequential economic and other gains is thought as a means of survival. The performance related data of the physical assets is collected in real time and then analysed, visualised, and utilised for taking business decisions that lead to greater efficiency. It uses the power of the industrial internet for enabling sensor guided remote operations, drones for remote data collection, robots for checking integrity of pipelines, etc, cameras for surveillance, cognitive computing for appraisal of exploration blocks, 3D printing for ondemand production of replacement parts, and data analytics for supply chain optimisation.

Facility management
The effective functioning of modern oil and gas facilities involves tremendous planning and scheduling with regard to procurement, production, quality control, safety and environmental care, off sites and utilities, marketing and logistics besides ensuring optimal use of raw materials, energy, and manpower. We have been using aspect specific systems and tools to address optimisation in each of these areas for prudent decision making to improve the bottom-line. Digitisation capabilities help to develop a holistic approach in the above decision-making process.

Digital transformation envisages the application of information technology (IT) or IT-enabled technologies to advance existing business operations, processes, models and strategies with the intent of making the company more productive, environmentally sustainable, competitive, and profitable.

Major industry segments such as manufacturing, power generation, oil and gas, aviation, transportation, etc, are taking advantage of the new industrial internet of things (IIoT) opportunity to unearth additional value from their operations. Various performance management and process optimisation tools employed in the facility generate voluminous data and there has been little effort in the past to holistically review the big data and optimise performance, sustainability, and safety at the enterprise level. The lack of a trusted platform to collate, segregate and analyse data was a major hurdle. The emergence of IIoT resolved this state of affairs and it has become handy to harness plant data through sensors and derive operational and other benefits including operational excellence, better manpower deployment and utilisation, cost reduction, product quality enhancement, and better safety and environmental standards.

Operational efficiency
Over the years, the oil and gas industry, as a whole, has witnessed considerable improvement in its operational efficiency. This has been possible because of their timely adoption of innovative and commercially proven retrofit and revamps technologies. Modern managements envision to strategically advance reliability, availability, operational efficiency of manufacturing systems and achieve increased production, yields, and ensure remunerative capacity utilisation.

With advanced automation, it is easier to do rigorous and real time plant monitoring, resulting in optimisation of all kinds of resources, better management through effective planning, and scheduling. Going further, highly connected open systems with real time domain and instant data integrated with enterprise resource planning (ERP) systems, operators gain command over the increasing complexities in the industry with regard to management of difficult to handle upstream, midstream, and downstream operations.

Even in well-optimised plants, there exists ample scope for improvement in operating efficiency through the adoption of digitisation and IIoT capabilities. Where to tap for further improvement indeed is a tough task. Technologies continue to develop; operating facilities adopt newer ones as and when they become technically proven and commercially viable and the operating results in the real-time plant environment follow them. Within the gaps of these developments lies further scope for optimisation.

A major technology company, through internal studies, has shown that 80 per cent of production downtime, much of which is due to operator errors, is avoidable. These errors cost the petrochemical industry approximately $ 20 billion a year. A well-developed preventive maintenance strategy can bring down operating costs which also account for downtime due to unexpected failures by 25 per cent. An advanced predictive maintenance program with the support of wireless technologies, IIoT and machine learning (ML) and artificial intelligence (AI) enables even greater savings. Under such challenging conditions, there is likely to be a growth of remote operations supported by modern, artificial intelligence platforms.

Current developments in wireless technology—smart sensors, intelligent connectivity, mobile technologies, data storage, analytics, and cyber security are increasingly contributing to advance the operability, productivity, maintenance, safety, and environmental stability in the industry. IoT intelligently connects physical devices, driving improved operating efficiencies, business growth and environment friendliness. Industry engages with the IIoT and uses a number of sensors of different designs to capture the operating parameters in real time and use the output for decision making to ensure that the operation of the facility adheres closely to the designer’s intent and enhance stakeholder value. Connected devices sense operation data and communicate the same to the datacentre where it is analysed with the support of big data analytics, artificial intelligence, and cognitive analysis. The output from the analysis is developed into actionable programs to operate the facility in the most optimised manner.

Across the value chain in the oil and gas industry, digitisation and IIoT are engaged to monitor variation in operating parameters, detect leakages, theft and tampering of pipelines, oversee security and integrity of installations and check physical condition and location. Real time monitoring of pumping and compressor stations along cross country pipelines helps to instantly assess inhibitory factors depressing operational efficiencies and expose corrosion. Such measures, taken in advance, improve productivity and thus reduce costs.

In recent years, the industry has been increasingly encouraged to use wireless sensor networks and supervisory control and data acquisition (SCADA) for monitoring oil and gas installations. Compared to IIoT, wireless sensor networks (WSN) have limited transmission range, storage capacity and power backup all of which need more improvements. On the other hand, SCADA systems are costly, difficult to maintain and not scalable. In its place, digital twins are capable of multiple access of a wideranging data of several equipment at a time at a lower cost. Thus, IIoT is capable of addressing the bottlenecks and improve productivity by enabling predictive maintenance in place of preventive maintenance, monitoring changes in operating conditions in real time and reducing downtime due to accidents. The IoT architecture for the above purpose comprises sensor (smart device), connectivity to the control centre (gateway), and control centre (server) responsible for application and analysis of data from sensors to generate information and support the decision making process.

Digital twins are coming up in a big way in the manufacturing industry offering to increase utilisation of capacities, improve product quality and output, forecast deviations from the designer’s intent with regard to processes and operating parameters, reduce specific consumptions of energy and feedstock, improve bottom lines, and achieve better workplace safety and environmental targets. A digital twin is a virtual model of an asset (compressor) or process (catalytic cracking), use IoT sensors to monitor and capture data from physical objects, process it in real-time in combination with historical data to provide an elaborate view on the performance of manufacturing equipment and plants. These models are combined with advanced visualisation technologies and data analytics to fast-track troubleshooting, forecast imminent failures, and innovate equipment and retrofit the same in an existing facility.

Often, a low turn down ratio arising out of overdesign in size and capacity of equipment is a generic problem associated with design. These data driven models in the virtual environment also provide the requisite inputs to better future designs. Digital twins are used in brownfield projects to guide the revamp and modernization of existing facilities to capture better operating efficiencies.

Shifting maintenance strategy
Historically, operators and maintenance men are trained by the original equipment manufacturer (OEM). They list out the immediate as well as long term maintenance requirements during daily inspection. OEMs on the other hand manufacture and deliver equipment with utmost reliability taking into account the facility owner’s requirement of balanced throughput, energy efficiency, asset integrity, safety, and long service life. Even with a highly optimised design, the shop floor performance of the equipment may experience certain voids needing design improvements or else to be overcome through a modified operating philosophy. Analysis of real time operating data captured by monitoring systems will help the operator to ascertain deviation in machine condition at the right instant, run a software modelling, and predict an imminent underperformance or failure.

The shift from reactive (‘run to failure’) to reliability cantered maintenance (RCM) was gradual and successfully avoided costly equipment failures. Today’s pro-active or predictive maintenance programs use advanced AI-based analytics to identify the predominant factors and monitor parameters to fix variations leading to failures-abrupt or incipient.

Moreover, advanced predictive systems are capable of accurately predicting remaining life of furnace tubes and likely failure time of rotating equipment. By this, the operator is empowered to extend equipment service life, avoid expensive repairs, and minimise unscheduled downtime.

Corrosion management
NACE International puts the annual cost impact of corrosion in the processing industry alone as US$ 50 billion. A 30 per cent savings on adoption of best practices in corrosion prevention will come to US$ 15 billion. Beyond economics, corrosion also adversely affects plant reliability, leads to accidents, damages assets and spoils the environment. Therefore, early detection of corrosion, its progress, and the impact of the vulnerabilities of varying process parameters have to be understood through advanced monitoring techniques.

Most of the present-day, non-destructive techniques for corrosion inspections are costly and are likely to invite added risk and downtime. Traditional inspection techniques are built on design data and operating parameters and are likely to evade remote locations such as buried pipes or equipment located in trenches or covered under insulation. Digital corrosion management techniques empower companies to go beyond traditional inspection and maintenance activities to achieve optimum performance all across the unit. By using a digitally enabled corrosion management approach, companies can develop a holistic, proactive, and cost-effective maintenance and inspection plan and strategies for corrosion abatement and inhibition.

Data security
In the digital world, data security is a prime concern and responsibility. Increased digitisation in the oil and gas industry, while improving profitability, raises concerns of cybersecurity risks. Organisations with good governance processes are able to practise security-by-design—building systems and processes able to respond to unexpected risks and emerging dangers. Employee awareness is also a crucial frontline defence.

The EY 20th Global Information Security Survey shows that rising digitisation and IIoT are increasing the complexity of the threat landscape. To protect critical information, an organisation must not only address the security of the traditional IT and OT environments, it must also deal with the added complexities from the IoT, while also integrating innovative digital business process disruptors, such as robotic process automation, blockchain, and artificial intelligence. Never before has it been so important to ensure that security efforts are integrated into every facet of an organisation’s operations.

EY Cyber Fusion lists three levels of cyberattacks and suggest remedies thereof.

Common attacks: These are by hackers and can be prevented with tools including antivirus software, intruder detection and protection systems, consistent patch management, and encryption technologies.

Prudent attacks: A prudent threat detection and response capability may be called as a security operation centre (SOC) and is an excellent defence against advanced attacks. SOCs are active defense guards—a deliberately planned and continuously executed campaign that aims to identify and remove hidden attackers and defeat likely threat scenarios targeting the organisation’s most critical assets.

Emerging attacks: In order to tackle emerging attacks, such as the rise in cyberphysical threats, in the oil and gas sector, companies need to build agility into their cybersecurity practices and approaches which reduces their reaction time.

Turnaround management
Turnarounds inevitably contribute to bulk of the downtime in operating plants. Completion of turnaround without time and cost overruns is dependent on ensuring the right and necessary information, supplies, equipment, and manpower at the right time. Therefore, a lot of planning and scheduling is to be done before shutting down a productive plant for cleaning and maintenance purposes.

Today, with the use of AI, real time modelling of maintenance and turnarounds, debottlenecking and troubleshooting become handy and the targets could be achieved almost within the schedule. The development of app-based software is a good way to enhance facility safety.

Wireless monitoring limits the risk of operating personnel being exposed to hazardous areas in the plant. Online monitoring of the loss of heat transfer efficiency of heat exchangers, energy and steam loss through faulty traps, and predicting end of run of reactor catalysts are well established through app-based software. Abnormal situation monitoring is yet another area where smart, wireless devices and sensors enable cloud computing of equipment data in various formats. Overheating, over pressurisation, and excessive vibration limits are set to identify normal and abnormal operations. In AI-based predictive solutions, deviations from the designer’s intent or a set fault threshold initiates warning to alert the operating staff.

Digital workforce
The oil and gas industry are widely distributed and engage thousands of workmen to work under extreme climatic conditions and hazardous installations. Effective coordination of the workforce at all levels with the objective of achieving greater productivity is a difficult task. Moreover, their safety and wellbeing (physical and mental) are also a concern. Digital workplace services combining cutting-edge technology and best-in class support services enable the workforce to work from anywhere, anytime and in a secured environment. Digital communication enabled workforce solutions, planning and prioritising daily workflows with mobile wearables, IoT and automated AI technologies encourage collaboration among supervisors and workmen and facilitate proactive problemsolving.

Thus, IIoT allows delivery of a large volume of data at greater speeds and at lower costs. A recent Gartner survey suggests that nearly half of all organisations implementing IoT technologies were currently using or were planning to use digital twins.

According to a recent research report, the market value of digital twins is estimated to grow from $3.8 billion in 2019 to $35.8 billion by 2025. Companies like Royal Dutch Shell are harnessing the power of digital transformation for over two decades to optimise their operations and drive enterprise-wide performance. Indeed, a wedding of operational technology (OT) and information and communication technology (ICT) resulting in a saving potential of the order of 25 per cent in avoidable costs. Besides, it is also another step forward in achieving the COP21 goals of the global climate change agenda.