Elaine Maslin and Audrey Leon look at how digitalization stands to make a big splash in the offshore industry.
Embracing a digital vision. Image from DNV GL.
Often when digitalization is mentioned, you will get an eye roll and skepticism. And yet, this is an area that has already transformed the way we live, from how we communicate and consume media to how we navigate and control our home heating. The likes of Uber and Airbnb have businesses based purely on data, with market valuations of around US$50 billion and $30 billion, respectively.
As we covered last month (OE: May 2017), BP has set out a plan to digitalize its business by 2020 (that’s under three years away). It sees the value of digitalization, but also the huge breadth in scope such a term covers. Digital includes sensors, telecommunications networks, analytics, artificial intelligence and machine learning, simulation and optimization, and robotics, which, coupled with advanced condition monitoring and computational power, enables major changes to the way we work. It could even be block chain, which has the potential to be used to overhaul the way the industry tracks inventory, orders or payments, via a single distributed ledger.
“Digital technologies have more widespread potential than any other technology area to transform energy production, supply and end use,” BP says.
Just like Uber and Airbnb, the oil and gas industry already has a high volume of data. The often-quoted statistic is that a typical offshore facility has 30,000 sensors capturing millions of data points and yet fewer than 1% of it is used for decision making and only 40% of it is stored.
Justin Daarud, president, Americas, operations manager of Asset Integrity & Development Solutions, Lloyd’s Register, calls it the “big data burden.” When it comes to asset integrity, it can be hard to drown out the noise.
“We have owner/operators that collect a million points of data, just for inspection,” Daarud says. “We go in and look at that and say, ‘that’s great, but we only needed 10,000 of those pieces of information.’ How much time, resource and money do they spend taking all those readings? We only skim off the top of what is necessary.”
Those costs add up. Graham Bennett, vice president at DNV GL – Oil & Gas, adds: “Poor utilization of existing information is often a hidden cost, accounting for up to a fifth of operational budgets, while a single unscheduled downtime can cost millions of dollars per day.”
A digital twin. Image from DNV GL.
The digital twin
What has been lacking is a way to store, manage and then apply analytics to the information created in the oil field. Enter the digital twin. It’s perhaps one of the major industry buzzwords of the past year, led initially by GE Oil & Gas, but with others, such as Kongsberg, now introducing platforms that enable operators to have a “digital twin” of their assets. Here, all existing and live data about a facility (or multiple facilities) is kept and can be used for simulations, modeling, analytics, in order to prevent downtime, predict maintenance requirements, and optimize operations, from drilling to decommissioning.
“This virtual image of an asset is maintained throughout the asset lifecycle and is easily accessible from multiple locations at any time,” Bennett says. “It is a central part of the digital asset ecosystem and will enable a new generation of advanced predictive analytics, enabling real-time optimization. The concept integrates data from many different software products and will enhance information management and collaboration, where the experts and operators can work together, preventing costly mistakes and rework.”
With 4G – and soon 5G – networks opening offshore, electrification of subsea assets, fiber optic sensing and communications, remote vehicles (subsea, platform-based and airborne), and mobile devices to access information and analytics, the potential for smart, remote working and operations opens up.
Luca Corradi, Innovation Network Director, the Oil & Gas Technology Centre, says that computational power and analytics, which are helping to provide real-time predictive maintenance is one advance, but combine that with automation, which can act upon the predictive analytics, and machine learning, “and you have a totally different industry,” he says. “The convergence of big data, computational power, the cloud, telecommunications (4G and 5G), and the integration of IT and OT (operations technology), would make the big breakthrough. We are not there yet, but it’s coming fast.”
An area where these technologies are now coming into play is in the use of mobile devices, thanks to the arrival of 4G offshore. “A few years ago the conversation about mobility devices offshore was a non-starter because there wasn’t Wi-Fi, only satellite, which was limited. Now there is a 4G network. It is a different story.
Here, the potential is for augmented reality (AR) to take operations to a new level. “I could be next to a valve, point my phone at it and get a drawing, information about the last time it was maintained, what it looked like compared to now, make an order for a replacement, see inventory levels, etc.,” Corradi says. “I could be connected to a subject matter expert, who can see what I can see and we can have a discussion on the spot about it and talk through what to do about it.”
Augmented and artificial reality are also helping in training – getting staff ready for a job faster. “Massive progress is being made in using AR for training, reducing cost, also mission preparation – i.e. flying drone in a virtual FPSO hull before the real thing,” he says.
Take this vision a step further, adding machine learning and artificial intelligence, and you could have a robot helping to do these tasks, Corradi says. While the offshore industry is quite far behind others in its adoption of robotics, this means there’s massive potential to make a leap forward, he adds.
“Robotics could be used for inspection work, perhaps reaching into difficult or hazardous places, such as pressure vessels or separators, for example, where otherwise humans might have to go,” he says. “Snake- or crab-shaped robots might be able to inspect pipe-wall thickness, or carry sensors able to detect leaks, etc.”
There is already some experimental work in this area – topsides robotics. We’ve recently covered Total’s Argos Challenge (OE: May 2017), and work to develop inspection robots for North Sea installations (OE: April 2017). Others are creating robots to take the human off the drill floor, with deployment offshore Norway this year (OE: November 2016).
“Short-term, we will not have robotics operating offshore,” Corradi says. “Will we be there in 10 years? Possibly. Having a robot that can tap in to the cloud, use artificial intelligence, real-time, super-fast computation, and you potentially have something super-flexible and reactive that can interpret what’s going on and react to it.”
Living on the edge
Dealing with the shear amount of data available and getting it to where it can be used quickly, is still a challenge. This is where edge analytics comes into play. This concept decentralizes analytics.
“Today, we tend to think and build from the bottom-up, object-orientated software programs and Internet of Things ideas lead to a focus on individual data points and equipment,” says Liane Smith, vice president, Digital Solutions, Wood Group. “Data is gathered into centralized databases, whether on a grand scale in a central repository or distributed in different systems interfaced together. The prevailing concept is to pull data from objects to a data repository, which may create the bottleneck for maximizing value for the offshore industry of the future.”
Future data architecture could be very different. “Data generated by sensors in the future could have properties of being self-curating and self-evaluating,” Smith says. “Presently, we judge the significance of a data point or trend in hindsight, algorithms can clean up data as it goes into a historian, removing error signals and failed calibration of sensors, but we still have to collect the readings before reaching these conclusions. Data of the future will be aware if it is trusted and significant, so that we get what is needed and cut out all the noise. It could then be used at source for immediate action, and objects could transfer data and commands to other objects directly without the step of needing the centralized database.”
The dawn of edge analytics within the energy industry will combine engineering design and operational expertise into sensor systems thus allowing complex data analytics to be performed within the sensor array.
“Changing the mindset from thinking about objects and data parameters and one dimensional problems to complex interaction of all the components in a complete offshore installation will force further innovation in the whole concept of ‘data,’” Smith says.
Weatherford shared its thoughts on edge technologies in OE’s March 2017 issue, discussing the firm’s edge device WellPilot ONE, a life of well controller used for artificial lift.
“There are refrigerators now that can tell you when you need to buy milk. The fridge in this case has edge technology built into it,” said Steven Seale, global director – automation hardware, Weatherford Artificial Lift Systems, at the time. “Information from the fridge can flow up into the cloud and an online retailer can enable you to make a decision to buy the milk and have it delivered.
“There are some control algorithms that [Weatherford] has developed for the controller, and we are better able to manage the injection gas, and the performance curve of the well,” Seale told OE. “Therefore, we don’t inject too much gas into the well. We inject just enough to get to get the oil lift as you need it.”
Going digital, or automating, sounds easy enough, but it is a painful process, as illustrated by the long road towards a goal for automated drilling operations. This slow process hasn’t put Statoil off. It has been putting all the pieces of the puzzle together, through targeted investment, including putting robotic units offshore.
“We’re investing in companies that will bring automation to the business,” says Erik Jakubowski, Investment Analyst at Statoil Technology Invest. “Statoil has an ambition of automating drilling operations. Our contribution is investing in companies that provide a small or large piece of automation to the drill floor.”
Statoil Technology Invest is investing in companies including Sekal, which provides trend analysis and drilling process automation; Raptor Oil, which is developing a signal processing system using acoustic signals to enable faster transfer speeds from the well bore; and Intelligent Mud Solutions, which intends to automate measurement of drilling and wellbore fluids. Robotic Drilling Systems (OE: November 2016) is this year deploying drill floor robots on to the Deepsea Atlantic, which is drilling on the Johan Sverdrup field.
“The overall aim is drilling operation that’s more efficient, predictable, safer and cheaper,” Jakubowski says. But, full automation isn’t likely until after 2020, he says. While the pieces are there, the biggest big is having integration between all the pieces.
Digital by design
Leveraging IT can also improve design and construction, says Alistair Hope, Shell’s project director for the Brent decommissioning project. This involves building a catalog of standard design modules, platforms, etc., that can be more quickly packaged together, making concept engineering faster, and enabling more focus on interfaces.
“Instead of repeating design, we can leverage the cloud and modern IT to improve the way we do engineering,” Hope says. “I’m really excited about it.”
Shell has already been using this process in its unconventional shale gas facilities. “It reduces cycle times, modules plug together quite quickly. It reduces cost, increases consistency, and is better for safety and design as well. That’s a potential game changer, particularly if this is across the industry, instead of one operator. For subsea, that’s the way things are going, a standardized subsea catalog with an IT package that can put it together.”
This also feeds into the construction process. Compared to other industries, oil and gas industry construction productivity has fallen. Using IT for track and trace systems, for hire equipment, for example, or using bar code technology to automatically update construction and design models, “so you know exactly where you are in design and construction, which helps construction optimization,” Hope says. “You can foresee problems and clashes more easily and optimize as you go.”
Taking this a step further, during commissioning, how tight a bolt has been torqued (as an example) can automatically be fed into a cloud-based system, from the tool itself, instead of a spread sheet that might never see the light of day. “It would have had to be checked before you start production. Now, you can put a sensor in the torque wrench, which records data into the cloud and populates the system automatically. It is more consistent and takes less time.”
Duncan Baillie, business development manager, at oil and gas technology firm, Lux Assure, gives another example: “Subsea chemical analysis can now be conducted and automated for the pre-commissioning of pipelines. This not only reduces costs and improves safety by removing the need for divers and boat time, but increases efficiency of decision-making, as operators can access chemical analysis information quickly to sign off pipeline commissioning.”
Block chain can do a lot to simplify, automate and increase transparency from logistics to automating transactions. End users can find where a spare part is located, where it came from, what condition it’s in, and the information can become more sharable and traceable, editable, and could lead to potential savings.
Block chain will not remove stuck drill from pipeline, but if it can optimize the logistics, it could potentially improve a lot of inefficiency in entire system (in recording and tracking, and the duplicating information). There are companies supplying suppliers, supplying operators, and every time information goes into a different system, a mistake can be made or be late processing payment. Automating what can be automated would remove a lot of administrative costs.
Scott Lehmann, vice president, Product Management & Marketing at Petrotechnics, a software solutions provider, says the key is having a “common currency” so that data otherwise hidden away in silos and can be extracted and meaningful relationships between previously disparate data sources can be found. “Relating them in a common way allows us to see their combined risk impact in terms of barrier impairments and the potential of a major accident hazard such as fire and explosion,” he says.
“Ultimately, the promise of digitalization is to help everyone make better, more informed operational decisions that reduce risk, increase productivity and cut costs. The data has to be brought together in a meaningful and routine way.”
With so much digital data being collected in the industry, it can be hard to drown out the noise, and apply findings that truly benefit operations, but Lloyd’s Register has taken a hard look at analytics collection in order to help their clients make sense of it and enhance their operations.
“Engineering based decision programs – which include, for example, risk-based inspection or reliability-centered maintenance, take specific sets of information: operating issues, maintenance procedures, etc., and they take the best out of it all and try to eliminate the over necessity or over-collection of information,” Daarud says. “We have seen an 80% reduction in unnecessary inspections in delivering a higher quality asset integrity management program that is safer and way more cost-effective.”
Additionally, last year, Lloyd’s Register acquired a company called RTAMO, which specializes in a cloud-based software aimed at optimizing maintenance programs (OE: January 2017).
“[RTAMO] optimizes how to manage the mechanical and maintenance integrity of assets, and it avoids unnecessary shutdown to manage one piece of equipment – it helps reduce over maintaining and the subsequent backlog. Many operators find it hard to justify their maintenance strategy and by evaluating and manipulating the data you can alter the maintenance plan and potentially extend the frequency by a month or two, if not longer. This results in a host of opex benefits such as reduced hours, eliminating unnecessary tasks, and less maintenance. This approach ultimately reduces the maintenance budget by 30-40% for an entire asset or facility,” Daarud says.
In a Houston press conference in mid-May, Carri Lockhart, senior vice president – US Offshore, Statoil, also highlighted the important role automation could play within the offshore space, in terms of facility management.
“We have driverless cars in Silicon Valley, California,” she says. “Can we implement some of this technology offshore? It may not be that you go completely automated – perhaps, just some pieces of equipment that help run the facility to a certain threshold.” Lockhart said that operational excellence and execution is one of four tenets Statoil has for offshore to compete with onshore resources. “If you can keep things running and plan your work out, and have high reliability, it’s actually some of your best barrels coming out of the ground.”
What would Lockhart like to see automated specifically? “The whole thing,” she said, with a laugh.
“To me, if you can have a computer make on the fly adjustments that keeps your kit running, if you have a computer that can run the analytics that say you need to be between this threshold and that because that is the optimal performance, it’s very fluid. It keeps the equipment from breaking down as much... But, doing this holistically, and having each system integrated and automated, it’s pretty powerful. Automation is hugely exciting. It is a different challenge.”
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