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DIGITAL TRANFORMATION UNITED PHDSOFT AND SHELL AT RIO OIL & GAS 2018

Duperron Marangon Ribeiro, PhDsoft CEO, and Marcelo Mofati, Senior Partnership Advisor and Game Changer at Shell, joined Shell Talks at Rio Oil & Gas 2018 to speak about Shell Innovation Challenge. The great prize has just been awarded to PhDsoft.

PHDSOFT CEO, DUPERRON MARANGON RIBEIRO SPEAKS AT SHELL TALKS, ON RIO OIL & GAS 2018

Duperron revealed to a selected audience his view on the next steps of the Digital Transformation Era and how PhDsoft C4D Smart Digital Twin will contribute on it.

SHELL GAME CHANGER MARCELO MOFATI AT RIO OIL AND GAS 2018

Marcelo told participants more about Shell initiatives on Industry 4.0, Cloud Computing, Artificial Intelligence, Analytics and all the issues related to the companie’s Digital Tranformation efforts.


PhDsoft and Shell partnership has already been expanded to other areas of the company. Soon it will be possible to tell more about that.

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Interview: Digital wins in Brazil

Duperron Marangon Ribeiro, CEO of PhDsoft, talks to The Oil & Gas Year (TOGY) about the benefits of the company’s technology and the Brazilian market’s growing interest in digital solutions. PhDsoft’s risk management and asset integrity technology has been used in the Brazilian oil and gas industry by Petrobras and Transpetro, among others.

• On going a step further: “Some CAD software can tell you how to make your pipe or structure design to avoid interference between different lines of pipes, for instance. These products are focused on the design stage of the lifecycle of the asset. Sometimes they go to the manufacturing stage, but nobody actually goes to the stage after delivery to the client. That’s what PhDsoft is doing, and that’s why we have to have a four-dimensional model, or true digital twin.”

• On new tech: “We are going in the direction of using drones instead of inspection companies in the near future. The drones do close visual inspection with photos, and then we engage the technicians. Using artificial intelligence, you can automatically detect any damage or anomalies such as cracks or buckling.”

Most TOGY interviews are published exclusively on our business intelligence platform, TOGYiN, but you can find the full interview with Duperron Marangon Ribeiro below.

How is PhDsoft’s technology used in the oil and gas industry? 
PhDsoft is focused on oil and gas digital transformation. We provide engineering tools in the form of software. We are an engineering company and a software company at the same time, and we combine these two languages into one product.
We have a platform that delivers products for different vertical markets. Our technology is a digital twin, a predictive one. You can feed historical data into the software to predict how degradation is going to progress over time. Companies use our technology, mainly the artificial intelligence part, to foresee failures before they occur, so they can take action to avoid major issues.

What are the advantages of your C4D technology?

The market has many CAD [computer-aided design] and 3D products. Some CAD software can tell you how to make your pipe or structure design to avoid interference between different lines of pipes, for instance. These products are focused on the design stage of the lifecycle of the asset. Sometimes they go to the manufacturing stage, but nobody actually goes to the stage after delivery to the client. That’s what PhDsoft is doing, and that’s why we have to have a four-dimensional model, or true digital twin.
Assets change all the time because they degrade due to corrosion, fatigue or other failure modes. They are also repaired all the time, which generates thick inspection reports that are full of information. You can use these reports for any specific repair, but the next time you have to evaluate the structure, you are not able to use the previous inspection report. It has so much information, and even though you have highlighted points with problems, you no longer know what points have been solved because that’s not in the report.
PhDsoft has automatised that. We log every inspection and every repair, and they are automatically matched, so you can see what the current issue is and foresee problems. We integrate all this information, using historical data to foresee progress. Even when building the model itself, it’s important that it’s four-dimensional.
Take, for example, an FPSO. It’s an existing ship that has been modified and converted into an FPSO. You create new structures to hold the topsides, and because the original ship has to be returned to a good condition, you make a lot of repairs, on top of all the repairs the ship has already undergone during its lifetime. If you have the date from each document, the software can automatically consolidate the existing asset for you, despite lots of changes over time.
The other interesting part is that, software is usually an additional burden due to the feeding of data. We have made sure that the life of the people in charge of feeding the software becomes easier. When we build the inspection plan automatically, it means that people in charge of doing the inspection don’t have to make the final inspection report anymore. It’s already done.

Has the Brazilian market embraced this technology?
PhDsoft’s first customer was Transpetro, a subsidiary of Petrobras. The second was Petrobras’ exploration and production division. Afterwards came Shell, Modec and other companies such as Subsea 7.
Now, we are closely connected with Shell and we are going to do game-changing development with that company. It seems the sector is realising the gains that can be made from technology investments.
The interest in digital transformation is present in Brazil. The only thing is that specifically Petrobras, the major player in Brazil, is willing to do it internally. After all the problems the company had, it has decided to try to make most of its engineering development internally. The company is in fact using C4D right now to make life extensions for the P-38 and P-40 FPSOs. Maybe Petrobras will be willing to use C4D for the life extensions of other offshore platforms, as well.
PhDsoft made this technology much ahead of time, and we have been lucky to survive with it so far. We have a chance to progressively implement more and more features. Now the market is ready, and that’s very good.

What other new technologies will become more useful in these operations? 

We are going in the direction of using drones instead of inspection companies in the near future. The drones do close visual inspection with photos, and then we engage the technicians. Using artificial intelligence, you can automatically detect any damage or anomalies such as cracks or buckling.
You can also engage ultrasonic probes. When you get to that point, it’s absolutely necessary to have a digital twin because you don’t have access to GPS inside the tank. How can you then steer the drone to go to different places in the tank? You need a 3D model, and with laser positioning, you can check the distance to the different parts of the structure. The 3D model must be working simultaneously with the drone.

How are suppliers, such as paint and coatings companies, involved in these processes? 

Because they paint structures, companies need to check and survey. From time to time, they need to renew coatings.
PhDsoft evaluates the rust grade of the paint from photographs and we can foresee the progress of rust in the paint. We can also create paint specifications and determine how much paint is needed. The paint manufacturer could and should be involved because it can immediately quote the necessary amount of paint needed.

How can PhDsoft’s technology reduce costs and improve efficiency in hydrocarbons production? 
We create a workflow for the engineering, just as ERP [enterprise resource planning] has done for administration. In general, SAP and other ERP systems deal with administration, even though SAP handles some maintenance issues, as well. When you have this regular maintenance software, the asset is split into different parts.
When you have a large structure such as an offshore platform, you don’t have part numbers. You have to look at a 4D model, locate the problem and then manage it with your digital twin. That’s the primary difference and the reason why ERPs are not able to go further than they have today.
PhDSoft is expanding this boundary to do something similar to what ERPs do. When we make the digital twin, we can collect all the engineering elements into an information flow between the different stakeholders: the company itself, its different departments and services providers such as inspection, classification, repair, coatings companies and so on.
That reduces a lot of man hours, especially in engineering, because the process automates many of their activities. Companies can then use that time for more high-level activities. It also reduces man hours in administration and inspection. Inspectors don’t have to worry about building inspection reports anymore.
Downtime can also be reduced for ships or offshore platforms going to shipyards because they can arrive with the plates already cut. That’s less time in the shipyards and less human errors, and that reduces costs.

Is PhDsoft involved in any technology partnerships? 
IoT means integrating all information from sensors, robots, etc. Siemens is going to provide us with MindSphere, which brings all this information together, so we don’t have to worry about how to connect to specific sensors. It’s connected there, so we can take the information from sensors or robots. The only exception is drones, which we will have to connect with directly and then send information to MindSphere, because we are going to steer the drone automatically.
We also have another partnership with Dassault, which provides products that can make our technology even stronger. That company has regular CAD software – SolidWorks and Catia – but it also develops engines, some of which we are going to integrate with our technology to reduce the time to market.
We have also won the Shell Innovation Challenge and that company will provide us with the necessary resources to develop real-time data integration with our digital twin. That will lead digital transformation in the oil and gas market to industry 4.0. We are pushing the boundaries of integrity management technology a little further.

For more information on PhDsoft in Brazil, see our business intelligence platform, TOGYiN
TOGYiN features profiles on companies and institutions active in Brazil’s oil and gas industry, and provides access to all our coverage and content, including our interviews with key players and industry leaders.
TOGY’s teams enjoy unparalleled boardroom access in 35 markets worldwide. TOGYiN members benefit from full access to that network, where they can directly connect with thousands of their peers.

Source: TOGYiN (click here to read the original version)

What Is Digital Twin Technology – And Why Is It So Important?

While the concept of a digital twin has been around since 2002, it’s only thanks to the Internet of Things (IoT) that it has become cost-effective to implement. And, it is so imperative to business today, it was named one ofGartner’s Top 10 Strategic Technology Trends for 2017.

Quite simply, a digital twin is a virtual model of a process, product or service. This pairing of the virtual and physical worlds allows analysis of data and monitoring of systems to head off problems before they even occur, prevent downtime, develop new opportunities and even plan for the future by using simulations.

Thomas Kaiser, SAP Senior Vice President of IoT, put it this way: “Digital twins are becoming a business imperative, covering the entire lifecycle of an asset or process and forming the foundation for connected products and services. Companies that fail to respond will be left behind.”

How does a digital twin work?

Think of a digital twin as a bridge between the physical and digital world.

First, smart components that use sensors to gather data about real-time status, working condition, or position are integrated with a physical item. The components are connected to a cloud-based system that receives and processes all the data the sensors monitor. This input is analyzed against business and other contextual data.

Lessons are learned and opportunities are uncovered within the virtual environment that can be applied to the physical world — ultimately to transform your business.

Pairing technology pioneered in aerospace

NASA was the first to dabble with pairing technology — the precursor to today’s digital twin — as far back as the early days of space exploration.

How do you operate, maintain, or repair systems when you aren’t within physical proximity to them? That was the challenge NASA’s research department had to face when developing systems that would travel beyond the ability to see or monitor physically. And when disaster struck Apollo 13, it was the innovation of mirrored systems still on earth that allowed engineers and astronauts to determine how they could rescue the mission. Today, NASA uses digital twins to develop new recommendations, roadmaps, and next-generation vehicles and aircraft.

“The ultimate vision for the digital twin is to create, test and build our equipment in a virtual environment,” says John Vickers, NASA’s leading manufacturing expert and manager of NASA’s National Center for Advanced Manufacturing. “Only when we get it to where it performs to our requirements do we physically manufacture it. We then want that physical build to tie back to its digital twin through sensors so that the digital twin contains all the information that we could have by inspecting the physical build.”

Michael Grieves at the University of Michigan first wrote of the concept using the digital twin terminology in 2002. Today, machine intelligence and connectivity to the cloud allows us an unprecedented potential for large-scale implementation of digital twin technology for companies in a variety of industries.

Why is digital twin technology important?

Digital twins are powerful masterminds to drive innovation and performance. Imagine it as your most talented product technicians with the most advanced monitoring, analytical, and predictive capabilities at their fingertips. By 2018, companies who invest in digital twin technology will see a 30 percent improvement in cycle times of critical processes, predicts IDC.

There will be billions of things represented by digital twins within the next five years. These proxies of the physical world will lead to new collaboration opportunities among physical world product experts and data scientists whose jobs are to understand what data tells us about operations.

Digital twin technology helps companies improve the customer experience by better understanding customer needs, develop enhancements to existing products, operations, and services, and can even help drive the innovation of new business.

For example, GE’s “digital wind farm” opened up new ways to improve productivity. GE uses the digital environment to inform the configuration of each wind turbine prior to construction. Its goal is to generate 20% gains in efficiency by analyzing the data from each turbine that is fed to its virtual equivalent.

“For every physical asset in the world, we have a virtual copy running in the cloud that gets richer with every second of operational data,” says Ganesh Bell, chief digital officer and general manager of Software & Analytics at GE Power & Water.

All indications seem to predict we are on the cusp of a digital twin technology explosion. More companies will learn of real-world and pilot program success stories and will want to deploy their very own digital twins to gain a competitive advantage.

I write books, deliver keynote presentations and provide expert advice on big data, analytics, metrics and improving business performance. I have helped many of the world’s leading companies and governments on how to answer their most critical business questions using data a…

Bernard Marr is a best-selling author & keynote speaker on business, technology and big data. His new book is Data Strategy. To read his future posts simply join his network here.