How the Industrial IoT will Revolutionize the Oil and Gas Industry

In Episode 30 of The Connext Podcast:

• [1:03] What is the current outlook for the oil and gas industry?
• [4:54] How is RTI helping oil and gas customers?
• [11:19] What makes Connext DDS different from other connectivity software?
• [22:36] RTI and the university program

Related Content:

• [Blog] Exploring the Role of Blockchain in Industrial IoT Systems (Part 2)
• [Datasheet] RTI in Oil and Gas
• [Datasheet] RTI Connext 6
• [Infographic] RTI Connext 6
• [Video] Industrial Internet Technologies for Oil and Gas Applications in Two Minutes
• [Webinar] Data Centricity: The Key to Automating the Processes of a Drilling Rig
• [Webpage] RTI in Oil and Gas

Podcast Transcription

Steven Onzo: Hello everybody, and welcome to another episode of the Connext Podcast. This week we discuss how the industrial IoT is revolutionizing the oil and gas industry. I'm joined by Mark Carrier, RTI market development director for oil and gas. Mark, thanks for joining us.

In order to kick things off, can you tell me a little bit about yourself and what you do here at RTI?

Mark Carrier: Yeah. So it's kind of interesting because before I joined RTI, I was a customer of RTI for quite a long time. I joined as the market development director for oil and gas, process automation and ITS, the intelligent transportation systems. I have spent the last 15 years working in upstream oil and gas, I was a computer scientist leading several projects designing and architecting building several large highly distributed systems, everything from seismic systems to autonomous drilling platforms.

[1:03] What is the current outlook for the oil and gas industry?

Steven Onzo: Well, let's start with the basics. Oil and gas has been an industry facing some significant changes and challenges over the past few years. What is the current outlook? What's keeping your customers up at night?

Mark Carrier: Probably one of the biggest problems that they face is efficiency, better ways of integrating and essentially reducing cost, reducing the number of people on site to increase profits. The price of oil in 2008 hit rock bottom; in 2015 it bottomed out again. And these big dives in oil price really kind of reframe how the industry thinks. When the price of oil is very high, there's not a lot of attention paid to more optimal performance, more optimal solutions, better integration. When the price of oil declines, it happens very rapidly, literally almost over night and it causes a huge impact on the industry. I think because 2008 happened, 2015 came a few years after that, that was a very big shift in the way the industry has their mindset right now.

There's been a big focus on automation in the past. And automation was really to drive more efficient operations, it was really around safety, around reducing the number of people on site. But now I think people, since the frequency of these drops are happening and there's a prediction in 2019 we'll have another collapse in oil price, and it'll probably never hit highs that we've seen in the past, so it's probably going stabilize somewhere between $40, $60 a barrel. So I think because of that, competition will be very big. So people are really looking for ways to position themselves right now, and they're looking at technology. Because you're looking at an industry that, if you look at the Industry 4.0 stack, this is an industry where part of the industry is still in 2.0 and barely in 3.0, so they're really looking to leapfrog themselves into the 4.0, which means adopting technology.

It's an industry that's built on mechanics, hydraulics. Information is passed around by Post-it notes, emails, phone calls, so adoption of the digital age is only something we've seen in the last few years. I think the last major advancement on a mechanical rig as far as equipment was really back in the 80s, and the introduction of control systems in the early 2000s, and that was kind of stepping into industry 3.0 and that was about 30, 40 years after most other market segments have gotten into. Which is interesting, because now I think that the oilfield itself will probably get to Industry 4.0 before manufacturing and other segments do.

Steven Onzo: Right, which is huge for an industry that hasn't changed in years.

Mark Carrier: Yeah. So you can see how much the price of oil really affects their decision making. There are so many players out there, and I think that people realize that, once oil kind of bottoms out again. Right now we're just seeing land is huge. Offshore is slowly coming back, and it's just because the technological advancements that we've made, land can be done more efficiently, it's much cheaper. Offshore reservoirs still produce a lot of oil, but they're extremely expensive to exploit those resources.

[4:54] How is RTI helping oil and gas customers?

Steven Onzo: How can RTI help address these sort of issues?

Mark Carrier: I look at the technology that we make at RTI as more than just a technology, it's really an idea and a philosophy because it allows you to look at how you design a system and how you integrate systems in a much different way than we've traditionally done in the past. Typically we engineer a solution, which results in a system that's not highly scalable, they're expensive to maintain. As future growth, future direction comes within a system, it's very hard to adapt these systems to new ideas, new functionality, new features. So because of the technology that we make at RTI, we can start to look at the system in a completely different way, which is data. So I’m going to look at all the data that a system exchanges, and that's everywhere from the control systems, looking at the encoders on a motor, all the way up to how a business runs its supply chain, because all of this information is related.

So if you kind of look at the industry as a data model, you can start to build applications around that data model, and it's very interesting. I recently gave a talk about types of applications that fit into these market segments, and I classified them in two ways. One is analytics, and one is automation. If you look around, everybody's doing analytics. I've gone to so many conferences over the last few months, and I would say 95% of the talks are about analytics, IoT platforms, blockchains. And the interesting thing is, these are automation conferences and you don't really hear much about automation, and it's because to actually do real automation and use the analytics - which is the goal of why they're doing that to optimize the processes - you need to have bi-directional flow of your data. And most of the technologies out there aren't suitable for closing the loop.

Analytics are interesting because they're so far removed from the loop, you don't really need good quality data. You can spend as much time normalizing that data as it takes. You're pulling data from different sources, and kind of normalizing it into something that's understandable, then you optimize it. And then you want to use that to drive your processes. We are already so far removed, you can't easily use that data. But with our technology, when you define data models, you can add context to the data at every level, so the normalization is done as the system itself is producing data, so the context is already there. And because we provide multi-directional data flow, actually data anywhere you need data, we are actually enabling these market segments to kind of achieve a goal they want, which is automation and autonomous behavior.

Steven Onzo: Great. So you gave us a high level example of how RTI is helping customers. Can you do a deep dive in explaining how a company in the oil and gas industry is using Connext DDS specifically?

Mark Carrier: Yeah. So if you look at the upstream oil and gas segment, there are four natural market segments that fall in there. You have the OEMs who manufacture the equipment. You have the operators who are the stakeholders and managers of the reservoirs, and basically trying to exploit that. And then they hire contractors and service companies to actually go put holes in the ground and produce the reservoir so they can turn the hydrocarbons into oil and other retail products, energy products. Traditionally, there hasn't been a well defined system integrator in the upstream oil and gas, which is actually something that's changing very quickly. But the contractors in upstream oil and gas are essentially the de facto system integrator, because at the well site, that's where everything comes together, the service companies, OEMs. The contractor's responsible for bringing all these tools and services together to perform operations, and the data that's produced from that operations shift off to the operator.

So once we're able to identify kind of where this natural point of integration is - and this is all performed by humans -then all the operations, and most of the automation advancements that have taken place in the last few years have just been around kind of the repetitive motion on tools. So it'll move a tool up and down and number of times, or left and right and number of times. But in these stochastic environments, the distance you need to move or go up and down is something that's constantly changing, so just memorizing a point and moving to that point isn't really good enough, so that's why humans have been running the equipment for a long time because the equipment really isn't that automated.

So you have all these analytics that you're producing, you want to optimize the process, but does analytics actually have to come back to a human? So there's really no way to close the loop in an efficient manner because humans operate at different times than machines and processes do. By building an autonomous system, and you can actually include the human in the loop into this autonomous system, you can actually start to orchestrate the movement of these tools based on high-level objectives. And this provides a natural integration point, which then allows you to go back to those two applications I talked about, which were analytics and automation. So now I have a natural integration point, I have semantic interoperability on my data, and I have the ability for full loop closure because of RTI Connext. We have this wonderful thing called Quality of Service, which when I'm looking at my data, I can look at it in a very deterministic way and make decisions based on that determinism.

[11:19] What makes Connext DDS different from other connectivity software?

Steven Onzo: Okay, great. So, we've talked about the climate of the market and how RTI can help. I want to take this opportunity to get a little technical and talk about the technology itself, how Connext DDS works in terms in interoperability and data centricity. What makes this software different than other connectivity softwares out there?

Mark Carrier: Okay. Wow, you just actually hit the nail on the head. Data centricity. So every technology that's out there - at least that I'm familiar with - is message based. So what it means is we're connecting applications to applications. But really what these applications care about within a system is the data. So what happens is we over complicate our applications, we put a lot of logic duplicated all through different applications. We worry about a lot of things that we don't need to worry about, and we have some really good system design principles called coupling and cohesion. So what happens is we end up with highly coupled systems, which are not very good at scaling. They're hard to maintain, not scalable, especially when you want to distribute things. And then we end up with weak cohesion because we have information spread all over the place where we don't need to do that.

When you design a system to be data centric, you're actually designing the data within a system, and then you're designing the relationships between that data within a system, and then you're defining the qualities of that data, because observers and producers of data within a system have very different needs of that data. So you allow an entity within a system to only worry about the things that I need to worry about.

So it allows applications to take on very different roles. It allows them to have a domain of responsibility, I can focus on just the thing that I need to focus on because I know that the data that I'm looking at, I can trust. And if I can't trust it, RTI DDS Connext will let me know that the quality that I am looking for in the data isn't being met, so now I can make decisions about what to do because I have all of the information available to me. It has a domain of authority. I can make decisions in kind of a natural system hierarchy, so as new objectives come into the system I'm scalable for future features and future objectives.

Think about like cells. Think about it like your sweat glands. You sweat for many, many different reasons. In traditional systems, we would program all the reasons why you would sweat into the cells, and then if a new objective came along, then you would have to go back and recode that to the system, add that new feature. But the fact that they produce sweat because of a chemical response, so as new things happen within our bodies that may cause us to sweat is just because of the chemical response. So, it's not programmed into the glands themselves, they're just responding the way that they always do. So it allows you to really look at a system in a very, very different way. That's why I said earlier, it's kind of an ideology and philosophy. It's just a completely different way of viewing systems.

Steven Onzo: Excellent. Well, thanks for that explanation. So now I'd like to run through an oil and gas scenario with you, and just get your feedback on how this relates to edge-to-cloud capabilities, QoS, etc. Okay, here it is. If I'm an upstream operator and I have lots of data coming in from an oil rig that's 10 miles offshore, or from gas produced during a blizzard in North Dakota, how does Connext DDS handle that data, particularly when remote communications go down?

Mark Carrier: Okay, so that's a good question. So we can talk about it in two ways. So because I'm just looking at the data that I care about in the system, and I said a little bit ago there's always a natural hierarchy, so in these systems, you can simplify it by saying, there's control data which is the asset itself, and the data there, then there's the process data. It's a higher level abstraction about the process that's actually being performed. And then there's business data that I'm looking at storing in the cloud, and doing my analytics and seeing how I can optimize my processes much better.

So because of that naturally hierarchy, there's a natural different set of data models that can be developed. So quality of service is really important because in traditional systems, I would have to know that I'm speaking to certain field bus and I'm talking a certain network protocol. The transport is wireless, or cellular, or satellite, and I have no knowledge of what those latencies are. So as I am writing my application, which is like here, monitoring back at site of remote assets, my application would have to have an understanding of all these different transport mechanisms, the latencies, so that as I'm monitoring data coming in, if I'm not getting data within certain periods of times, my application is going to be programmed in a way that's trying to understand all of these different ways that data can be shipped around.

But with quality of service, I can just set expectations. I know that as a human observing data, my natural response time is between one and 300 milliseconds. Anything coming in faster than that, I can't really consume. And anything coming in slower than that is something that gets my attention. So if I'm monitoring let's say an offshore asset like you just described, and I'm watching the trend line and I'm seeing some graphs and they're kind of moving around, but then suddenly the data stops coming in. These traditional systems, it would be very hard for me as a developer to understand why that data was not coming in, and I would try to do all kinds of things on the UI, maybe set some alarms.

Here, I don't need to do that. Because of quality of service, I can set a deadline that says, hey, I expect to see data. Let's just say at 300 milliseconds. And in 300 milliseconds, if I haven't received any new data, the application will be alerted through RTI Connext because I've said my deadline is 300 milliseconds. So I can continue plotting or showing the data, but now I can start to visualize it in a different way, because maybe there's some jitter or latency on the line, and hopefully it'll come back. So maybe I've got a green bar, and because of this missed samples I start to turn it yellow, so then it can get my attention that way, and then maybe the data starts flowing again and it goes back to green, and maybe log that somewhere so that somebody can go look at the system... Maybe there's an issue in connectivity or something. But it just changes the way that I can observe my data. So with Connext, because I'm not looking at the transport layer on the data, I'm really just focused on those quality of service. My applications can do so much more because the complexity in the application isn't about managing the data, it's about just displaying it. Or if I'm controlling something remotely and I lose that signal that I need, or the quality that I need to actually be able to do control, the HMI or the screen that I'm observing can just gray that out. We still have the problem that we'd have with the traditional system that we need to understand what happened. Did we lose connectivity? What happened to my connection? But fortunately with Connext, there's enough semantics actually built into our technology, that I can kind of distinguish if something goes away because it's supposed to go away, or it goes away because something happened. So then I can start to display this type of information on the screen to the user to give a much better diagnostic. It's just very difficult to do that with traditional messaged based systems, because you don't have the right quality of service to be able to do that.

Steven Onzo: Right. So this is actually a good segway here. You've said that Connext DDS is easy to operate from a user's standpoint in these somewhat complicated environments. And on the surface, the technology sounds complicated. How does Connext DDS make the user experience easier?

Mark Carrier: In fact, I think the hardest problem that people have when they started using the technology is because it's a paradigm shift, you really have to start thinking about how you design a system differently. I myself was guilty of that when I first started using the technology. And then after a while you start to use it, you realize you're still doing lots of stuff in your application that the databus does for you. So as you gain more understanding of the databus and really the paradigm on how to do it, it just completely reduces the complexity of your application, and it really actually makes developing a distributed application much, much easier, 'cause you're really just dealing with data, and you're dealing with events on that data. So I don't need to be looking at data constantly to see if it's changed, I can just tell the databus, hey, only tell me when data has changed.

Or, if I'm looking at a temperature sensor and I want to see if it's succeeded a certain threshold, I don't need to sit there and say like, 32 degrees, 32 degrees, 32 degrees. Oh, it's 34 degrees. I can just put a query on the databus that says, tell me when it's 34 degrees, and then I don't have to do anything. My application just sits there idle until the event has happened, and then my application gets notified and it does what it needs to do, and then it goes back. So it allows you to really simplify. I can't even stress that enough. It's almost cultish, the way I say it, but it's amazing how simple it becomes. And then you can really focus on the complexities of the application that you need to, not on the connectivity and passing of information around.

[22:36] RTI and the university program

Steven Onzo: Great. So I want to take a turn here now that we're winding down the conversation, and talk about research organizations that support this industry. Does RTI have any program to support development efforts?

Mark Carrier: We have a university program, which is really good. We're actually putting together kind of a new marketing strategy for our university program to get the word out. For me, I'm very excited because there are several universities that I'm interested in targeting, like University of Texas in Austin, there's the University of Houston. These schools have big research programs with a lot of the major oil and gas companies, especially now with data science becoming very big, and that all goes back to the analytics. And the whole reason they want to use analytics is for automation. So yeah, that program is ... We're in the process of redefining it, and as soon as we're done I actually plan on hitting several universities to get the word out because I think starting with the young minds with the fresh ideas, with the guys that are doing the new stuff, and it's all about data, everything they're doing is all about data, so I want to give them the tools to actually be able to use that data in the right way.

Steven Onzo: Great. So where can oil and gas companies find more information about Connext DDS?

Mark Carrier: So, our website. We're in the process of ... We've actually got a brand new website and there's a section for oil and gas. In the process of working on some white papers, which will be available out there hopefully very soon. Yeah, I guess over the next six months I'm going to be working very hard on promoting Connext in lots of conferences through papers. We'll have some customer announcements coming out hopefully in the next few months, so just look forward to that.

Steven Onzo: Lot of things on the horizon.

Mark Carrier: Yes.

Steven Onzo: Well Mark, I want to thank you for taking the time to share your insights on how the industrial internet of things will certain disrupt this market, and eventually revolutionize the way this industry operates. But one last question before you go. As we live in this amazing moment in history where innovation is rapidly growing, and new applications arise every day, personally being able to work in this space and help developers sort of carve out the future, what gets you most excited about RTI and Connext DDS?

Mark Carrier: I think for me it's ... 'Cause I started in my career doing peer computer science stuff in the real time operating systems and compilers. And then when I moved to Houston, it was just natural to get into oil and gas. And one thing that really excited me about the industry itself is it's not a typical nine to five job in an office. I mean, it's really a lot of field work, to understand lots of different sciences and different things. But I realized early on, it is a very antiquated industry. And I really don't mean that in the pejorative, it's just slow to adopt new technology. And as a technologist, it's one thing that really excited me was, here is essentially a block of clay with a lot of opportunity to start making a difference, and really trying to revolutionize a new industry. And having gone through many, many years of distributed systems and actually trying to develop my own solutions for a middleware, kind of that very important infrastructure to a system, you spend so much of your time working on that, you don't actually get to work on the problems that you want to, and it's not an easy thing to build.

So years ago I was working on a project. It was all based around DDS, and I had actually never used DDS. And then once we actually got to implementing the project, we got our first Connext license, and we set down that path. And from that point on, I was personally addicted to the way that I could design and view and build a system because it was really truly all about the data, and that's what systems are all about. So yeah, for me it's exciting because it's just a chance to kind of revolutionize an entire industry, and it's an industry that is going to be impacted by technology in a very dramatic way. So being able to be part of RTI, it gives me the opportunity to go out and evangelize much more, and to work with a lot more people in a capacity I wasn't able to before.

Steven Onzo: Well once again, I want to thank you for joining us.

Mark Carrier: Yeah Steven, thanks.

Steven Onzo: And thanks everybody for listening, and we'll see you next time. Thank you. Mark, thank you very much for stopping by and talking with us. Join us next time when we speak to talent partner Nicole Ho about the top 10 reasons to work for RTI. If you have suggestions or feedback on this or other episodes, please contact us at podcast@rti.com. Thanks, and have a great day.