Field Automation and Low Oil Prices

  • September 22, 2015
  • Feature

By Daniel Atzori, PhD

North America’s onshore oil and gas industry is particularly sensitive to low global oil prices and increasing efficiency is more important than ever for operators to compete. It is therefore crucial to assess the potential of automation for increasing production and reducing expenses.This paper addresses topics such as surveillance, predictive analytics, Supervisory control and data acquisition (SCADA) developments, control systems – all part of the move to automate onshore oil and gas production in order to optimize production.

The present study provides the outcomes of a series of in-depth interviews conducted with leading personalities from the oil and gas industry, with the goal of exploring the potential of onshore automation.

The business case for automation

Automation is “fundamental” to optimize processes, especially in the current low oil prices environment, said Sujatha Kumar, president and owner at the management consulting, technology and automation services provider Ayatis.

Oil and gas companies traditionally approached exploration by “drilling one’s way to profitability”, instead of focusing on efficiency, said Nagaraj Srinivasan, vice president of Landmark (Halliburton), which provides software for the exploration and production of oil and gas reserves. In the past, process automation was an expensive proposition for oil and gas companies

 “Early adopters had to build custom software from scratch; few production workflows or data models were standard across the industry, so automation technology was not easily repurposed,” Srinivasan added.

Hence, “operational efficiency programs that are second nature for other manufacturing industries - aerospace, automotive, food processing - have lagged behind in our industry. They have not been considered essential by operators until recently,” Srinivasan said. But as industry pressures, practices, and technology are changing, “automation is starting to make financial sense for mainstream operators,” Srinivasan added. Particularly, in this climate, operators are pursuing the kinds of automation strategies that can aggressively eliminate nonproductive time and unnecessary costs from an increasingly lean system  “Low oil prices require low cost solutions,” added Srinivasan.

The oil industry estimates that digitalization can lead to an increase in efficiency from 3% to 5%, said Philippe Flichy, senior digital oil field advisor at Baker Hughes.


Automation involves having well controllers on each well, beam lift, electrical submersible pump (ESP) controller, gas lift controller and injection controls, said Joe Whitfield, manager of operations data management and technical data management and business analytics at Occidental Petroleum Corporation. “These units are used to control the starting and stoppage of the well, identify issues, generate alarms,” Whitfield added.

Operators’ main advantage from automation is visibility of processes, so that they can monitor them and react to situations in real time, Kumar (Ayatis) said. Operators need to be able to know what is happening in each of the production well sites in order to increase the efficiency of processes and equipment, said Kumar. Automated wells provide more information for surveillance and decision making, the enterprise architect of an oil company said.

Automation does not only allow to remotely control wells, “but the biggest advantage from automation is that you tend to have a continuous flow of information coming in from those wells,” he added.

“We use the automated wells that have continuous information for real-time monitoring, and so we can know when there is a problem, right away,” he said. The presence of more technologies downhole allows access to live data instead of calculations, said Holsey (GE Oil & Gas).

Regarding subsurface, the most promising developments concern continuous production surveillance applications based on fiber optic technologies, such as distributed temperature sensors and distributed pressure sensors, said Matteo Marongiu-Porcu, Senior Production Stimulation Engineer at Schlumberger.

These automatic systems, will be soon able to take measurements, adjust and take actions based on real-time feedback loops, Marongiu-Porcu added.

The systems will be particularly useful in North America’s unconventional shale plays, being developed with horizontal wellbores with possibly over one hundred clusters of induced hydraulic fractures, Marongiu-Porcu said.

Here, a system that allows to monitor and understand in real time the evolution of productivity is going to help considerably in understanding the causes of the often observed drastic productivity losses, as well as when and how to take decisions such the restimulation of suboptimal fractures or installation of artificial lift completions, Marongiu-Porcu said.

These applications are going to be extremely effective in understanding the time and the specific areas of the long horizontal wellbores that require refracking, as well as whether there are new areas of the wellbore that can be stimulated for the first time, Marongiu-Porcu added.

Predictive analytics

Automation can reduce both lost production and maintenance costs, according to the oil company’s enterprise architect. “It’s all about improved efficiency,” he added. According to him, automation’s savings come from identifying problems before they actually take effect.

The amount of lost production from downtime typically amount to 4%, hence total savings on a major facility can amount to millions of dollars, the enterprise architect said. “You can minimize the downtime by taking preventive maintenance before you have a serious failure,” he added. “By making an adjustment you can prevent a problem from happening,” the enterprise architect said. “You may still need to take a well down or a facility down, but you do it before it breaks. Because once it breaks, it becomes very, very expensive,” he added.

All equipment tends to degrade over time, and understanding the optimal time to schedule maintenance can help operators to increase efficiency levels, leading to increased production, he said. For example, every time maintenance is done on an electrical submersible pump, expenses can approximately amount to a quarter million dollars, the enterprise architect said. “If we can solve a major facility problem before it happens, we can save a lot of money,” he added.

According to Moazzam Shamsi, global solutions architect at Emerson, today the emphasis lies in the introduction of predictive diagnostics and predictive technologies into assets through wireless. This allows operators to increase visibility, allowing them “to take a better or more informed decision about what the asset performance is,” Shamsi said.

Artificial lift

An example of how automation can improve productivity is represented by artificial lift technology. According to Ron Holsey, president at GE O&G Rod Lift Systems, artificial lift can lead to a 20% power consumption reduction, a 25% failure and maintenance cost reduction and a 4% production increase.

Control systems and management by exception

According to Srinivasan (Halliburton), as the amount of operational data proliferates and the popularity of KPI [Key Performance Indicators] dashboards, alarms and notification systems grows to match it, human operators will manage by exception, allowing them to focus their attention on a small subset of actionable information. “Because of this, it is important to enable control systems to take routine actions wherever possible, and to create an operational climate where the engineer interacts with the field on an increasingly supervisory basis. As an example of how this may happen in the future, consider a field of wells, each of which consumes a quantity of lift gas that is specified by an integrated asset model,” Srinivasan added. “If a compressor fails, it sends a signal to its wells, notifying them that it can’t supply gas. The wells can then broadcast a request for gas over the network, obtain a ‘bid’ from a neighboring compressor, and send a request to the integrated asset model to recalculate the production forecast based on the control system’s rebalanced lift gas allocation,” Srinivasan said.

Hence, according to Srinivasan, training of operators needs to become broader-based. Traditional functional disciplines, such as production, completions, and reservoir engineer may make way for roles like asset steward or asset engineer. New operators must be trained to see the entire field as an interconnected system and to know how to monitor and respond to events in ways that optimize revenue

According to Srinivasan, this is very different from the practice of training operators to respond to alarms and keep process variables within specified tolerances. “That way of thinking will become antiquated as intelligent control systems take over,” Srinivasan said.


If operators are able to conduct their operations with a higher level of automation and streamlined processes, they can not only remotely monitor and manage their processes but also optimize their workforce and improve the safety of their process and personnel, Kumar (Ayatis) added. According to Flichy, automation could bring “incredible savings” in terms of human lives, downtime and cost of repairing.

Standardization and data integration

The biggest challenge in real time data consists in having the right level of analytics to be able to process and interpret the data, Kumar said. There are so many analytical platforms in the market, but the problem is there is not a single way of easily interpreting the data According to Srinivasan (Halliburton), today standardization on several fronts is helping drive down the cost of automation, offering a solution for lower labor costs, higher operational efficiency, and better reservoir outcomes.

Though the industry has not converged on a single production data standard, the wide adoption of respected standards PPDM [Professional Petroleum Data Management] and PRODML [Production Markup Language], makes it easier to write workfloworiented, scalable and repeatable applications and information management software, Srinivasan (Halliburton) said.

“Additionally, industry guidelines on production workflows like well integrity management and increased collaboration within companies and even between companies, like we’re seeing in Malaysia with the Petronas-led Coral 2.0, is encouraging companies to adopt some similar best practices,” Srinivasan (Halliburton) added. “Even though automation software will continue to require configuration - each production network is unique, after all - it is starting to require less customization,” Srinivasan (Halliburton) said.

Smart hardware is becoming easier to integrate into field operations as oil and gas operators have banded together to set industry-specific standards for manufacturers, said Srinivasan.

SCADA and the Internet of Things

There is currently a lot of interest in the industry concerning the Internet of Things, Flichy (Baker Hughes) said. The Internet of Things is bringing “distributed intelligence over the chain,” Flichy added. SCADA systems are poised to join the Internet of Things, or the Industrial Internet

This is shown by the recent formation of the Industrial Internet Consortium, a body dedicated to developing standards for real-time communication with field sensor arrays across all industry verticals, Srinivasan (Halliburton) added. “Industrial automation companies who produce SCADA systems are hard at work making their hardware network-aware,” he said. According to Srinivasan, data modeling standards will become even more important as the Internet of Things evolves.

“Not only do we need to have standards for describing upstream operational data, but we also must develop standards for consuming the raw signals from a growing array of diverse, network-connected sensors and devices,” said Srinivasan (Halliburton). “This raw data may come over established, wide area networks, but it will also oftentimes need ad hoc, temporary networks, which we’re not good at standing up in the oil field today. We then need to develop reliable, ‘plug and play’ protocols for recognizing new devices as they come online and consuming the data they offer in our engineering and business process management applications,” said Srinivasan (Halliburton).

“Think about how we now plug a Bluetooth peripheral, such as a keyboard, into a laptop computer. The keyboard joins the network, the computer immediately knows its capabilities, and the user simply begins typing,” he said.

Data modeling standards, pervasive networking, a plug and play architecture for oilfield equipment within digital oilfield software platforms and a push to move routine decision making capabilities down to the individual device level, are all challenges and opportunities that will be faced in the coming years, Srinivasan added. With the Internet of Things, any major piece of equipment will increasingly be equipped with its own built-in sensor and built-in computer, to the extent that “the Internet of Things will replace SCADA,” said the oil company’s enterprise architect. Hence, instead of communicating via proprietary automation gear, communications will take place via the Internet of Things, he added. More information will be available and it will be incorporated in the surveillance solutions, the enterprise architect said.

However, the Internet of Things presents several risks that cannot be underestimated. “Of course, the elephant in the room is the security aspect,” Flichy added. “Security is one of the biggest concerns these days in the industry, because systems need to be more connected and more open. That automatically brings the concern of security. There is a lot of investment going on, by all the players of the industry, not just us, to ensure that the systems are as secure as possible,” Gilabert (Schneider) said.

Future automation strategies

The concepts of data analytics, efficient data visualization and machine learning can represent an important leverage to bring the automation in oil & gas industry to the next level, said Marko Maucec, an independent consultant and reservoir advisor. “We need to make our oil and gas operations profitable even at low commodity prices and knowing and understanding more about the data we measure, is a fundamental step forward,” Maucec added. According to Maucec, automation strategies and approaches will continue to be improved, irrespective of oil price levels.

“Instrumentation, sensors and other DAQ [Data Acquisition] technology will probably continue [to] evolve at its current pace,” Maucec said.

What will change concerning the future automation strategies for digital oil field applications is how data will be used and optimized in order to maximize extracted information and knowledge, “which can often be very non-intuitive,” Maucec added. According to Maucec, data analytics, as well as predictive and prescriptive data-driven modelling, will be used for decision making processes, optimization of production, improving asset value and returns, enhancing safe and environmental-friendly operations, improving production and recovery rates, reducing down and nonproductive time and increase operational efficiencies and productivity across major business units.

However, according to Maucec, due to exponential growth in the volume and complexity of acquired data, the industry will need to solve challenges concerning how to collect, classify, integrate and maintain data efficiently and how to automate analytical tools for them to become compatible with digital oilfield technology. Other challenges include the integration of disparate data sources regardless of origin, time scale or structure, the efficient and effective use of acquired data and the provision of visualizations of “what-if predictive modelling,” Maucec said.


In the current low oil prices environment, automation is crucial to optimize production, allowing operators to achieve higher levels of operational efficiency. By implementing effective surveillance and predictive analytics strategies, automation can contribute to substantial savings, through areas such as improved maintenance and downtime reduction.

While standardization and data integration are driving down the costs of automation, the Internet of Things is poised to revolutionise SCADA systems, bringing significant new opportunities, as well as new security threats. In a low oil prices scenario, automation will enable a reduction in costs by making sure that the focus is only on the areas that need attention, Gilabert (Schneider) said. Furthermore, an effective optimization strategy through automation needs to focus not only on volume metrics, such as increasing production and reducing downtime, but also on cost minimisation, said Gilabert.

And as noted by Flichy (Baker Hughes), the oil and gas exploration industry is supporting a certain degree of new data processing power, but only human beings have the holistic approach to understand every element of these complex systems. Shale Operators Gather to Debate Low Cost Automation

Challenge and Drive Towards Operating by Exception

As shale operators manage an ever-increasing portfolio of producing wells in isolated locations across North America, automation proves critical to addressing the industry’s capacity challenge, achieving ‘operation by exception’, lowering cost position and minimizing production downtime. However, defining a costeffective approach to automation as part of a holistic strategy and tackling complex standardization challenges inherent within almost all automation projects are major hurdles ahead.

Shale operators are demanding an entirely new approach to automation and consequently shaking up this long established market. With less formalized automation departments, major capacity challenges and a current squeeze on Capex, operators are searching for an Opex-driven automation approach that allows flexibility in future technology adoption. In light of this, the service provider community are at a crucial ‘reactionary phase’, transitioning from a product orientated to service orientated strategy.

To address these major automation challenges and hot-off-the-press industry developments, top experts will gather at the industry-leading Field Automation Summit in Denver this November to tackle the major hurdles head on and aim to tailor an automation strategy that is both cost effective and scalable for each E&P organization.

“As a result of the fast-paced shale developments, the level of automation in production operations is nowhere near the level being adopted during the drilling process. Production operations automation is at risk of being left behind, with major cost implications”.

“With the shale industry now at a crucial juncture, the next 6-12 months will highlight pivotal developments which will impact the entire SCADA, controls, automation, measurement, IT and engineering community – hence the need for the Field Automation Summit.”

Philip Chadney, Director - Field Automation Summit, Upstream Intelligence

The Field Automation Summit 2015 will allow you to:

  • Deliver a game-changing automation strategy that harnesses an “operate by exception” approach and maximizes value from human capital
  •  Establish optimal automation to operate facility safely, address environmental issues and make sure data is available for operators to make the right decisions
  • Optimize your approach to standardization and streamline controls, program utilization, logic embedded and end-devices to maximize data integration
  • Understand how you can adapt and integrate your legacy SCADA systems so they can support the growing enterprise
  • Meet the communication infrastructure needs at isolated field locations by developing and expanding the local area network with suitable power, radio and Ethernet

Whitepaper produced in conjunction with: Field Automation Summit November 2015 Denver, Colorado Operate by exception and eradicate production downtime by unlocking a cost-effective automation strategy

For more information on the Field Automation Summit, please contact: Phil Chadney Sr. Project Director | Upstream Intelligence toll free US. +1 800 814 3459 ext 4341 e.

Key Contributors to this Report:

André Baken Founding Partner, Digital Oilfield Assessment Services (DOFAS Business Transformation)

Jim Crompton Managing Director, Reflections Data Consulting

Philippe Flichy Senior Digital Oil Field Advisor, Baker Hughes

Helenio Gilabert Director of Telemetry Systems, Schneider Electric

John Hedengren Assistant Professor, Brigham Young University

Ron Holsey Global Business Leader, GE O&G Rod Lift Systems

Sujatha Kumar President and Owner, Ayatis LLC

Chris Lenzsch Intelligent Solutions Manager - Big Data and Analytics, EMC

Marko Maucec Independent Consultant and Reservoir Advisor

Matteo Marongiu-Porcu Senior Production Stimulation Engineer, Schlumberger

Moazzam Shamsi Global Solutions Architect, Emerson Process Management

Nagaraj Srinivasan Vice President of Landmark (Halliburton)

Joe Whitfield Manager Operations Data Management - Technical Data Management & Business Analytics, Occidental Petroleum Corporation

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