How ExxonMobil is Leveraging Aerial Robots for Inspection of Oil and Gas Infrastructure

In the dynamic and challenging landscape of the oil and gas industry, maintaining the integrity and functionality of expansive asset infrastructure is paramount to support strong reliability and performance throughput. This live talk, led by Shankar Nadarajah, Global Drone Inspection Lead at ExxonMobil, will delve into specific challenges faced in overseeing remote inspection of vast infrastructures and how ExxonMobil is addressing these challenges using aerial robotics. 

Including: -Standing up a drone inspection program and process for getting executive buy-in to scale inspection operations.  Illustrating the value of aerial robots for inspection of oil and gas infrastructure vs. traditional methods  -Enhancing inspection workflows with higher quality insights powered by AI-enabled aerial robots. -Expanded uses for innovative technology solutions outside of inspection, such as critical response and security -The future vision for persistent aerial inspections with dock technology and remote operations.

Join us to learn about the evolution and benefits of oil and gas workflows and critical response through the use of aerial robots.

Shankar: Yeah. Hi, everybody. This is Shankar Nadarajah. Appreciate the invitation. I'm the global drone inspection lead for ExxonMobil. Been with the company twenty-two years. So been in this particular role for a plus or minus about two years or so. My previous background, I started off in IT, technology, networking, servers, and data centers, but then quickly moved into a wide variety of assignments outside of my comfort zone. Everything from HR to chemicals, sales, and then to manufacturing and refining supporting our large maintenance turnaround and execution. These are maintenance turnarounds where we have anywhere from a few hundred to a few thousand people on-site, for a period of time, about thirty to sixty days, taking down a unit, putting it together, and getting it prepared for operations again. So yeah, appreciate the opportunity. Thank you for the invitation.

Sterling: Yeah, thank you for joining us today. Being part of the solutions engineering team allows me to go into the field, such as with Shankar and perform some really amazing autonomous aerial robotic tasks in complex environments. So we'll be covering some of those successes that we've had in the local Exxon refineries. Shankar here will first cover some of the high-level Exxon overviews, and then we'll get into some specific Skydio captures.

Shankar: Yeah. So I think, just to kick things off and set the scene for the meeting. Right? Just a little bit of background around ExxonMobil and our entry into the drone operation space and why that happened. We're going to talk a little bit about an acronym called GAVIS in the next slide, which stands for Global Aerial Visual Inspection Service. Essentially, the business problem that led to this is really the fact that we had an interesting technology back in early 2015-2016, but it was mostly used for hobby purposes, not a lot of commercial use. There was a lot of uncertainty around what you can and can't do with a drone on a commercial property, especially an oil and gas facility with various risks and hazards to manage. So we needed a program in place to help us work through that.

First and foremost, we wanted to understand where we could apply this technology and where we saw the need. Many of these applications are for areas where we have assets at heights, such as pipe racks, reactors, furnaces, flare stacks, and confined space entries. For example, inspecting the interior of spheres. This is where confined space scenarios play a significant role in personnel safety and risk mitigation. The GAVIS program helped us set the stage to standardize how we expanded this program globally. We now have this program in over one hundred ExxonMobil affiliate locations and sites around the world. We've achieved deep penetration of the technology, and it has been paying dividends.

I also want to acknowledge our partners who have been instrumental in our success. We took a strategy and approach to scale quickly by establishing strategic third-party drone operators that were vetted to ensure they met safety metrics, performance, had the latest equipment, and could produce quality results. Data is the prize for ExxonMobil, helping us quickly put together remediation plans. We wanted consistency across our operations, whether in Baytown, Texas, or our upstream unconventional space in Australia. We partnered with Hover Data based in Austin, Texas, which helps us manage, organize, store, analyze, and produce high-quality reports that our inspection teams can collaborate on globally.

Our aviation department and our community of practice, our drone COP, have also been pivotal in promoting awareness and identifying opportunities for improvement and new technologies.

Going back to GAVIS, which stands for Global Aerial Visual Inspection Service, it helped us organize how we would structure and scale a large-scale drone program by identifying opportunities. We had different levels of drone operations at various sites, some with people certified to operate drones and others just learning about drones. We closed that gap by putting a standardized program in place, leveraging third-party support to scale quickly, and ensuring regulatory compliance globally. We also identified cost-saving opportunities in scaffold reduction, motorized equipment, and rope access, and we significantly improved data quality from binoculars and digital cameras to high-resolution video.

Looking ahead, our focus for 2024 and beyond is automation. We aim to digitize the end-to-end inspection workflow, making it more automated and efficient. Skydio technology is crucial in achieving this, providing us with a three-dimensional view of assets and enabling AI and machine learning to process data and identify defects quickly.

Sterling: Thank you, Shankar. Going out into the field with Skydio's autonomous drones has been a transformative experience. The autonomy and obstacle avoidance capabilities of Skydio drones, such as the Skydio 2+ and Skydio X2, have allowed us to capture complex datasets in challenging environments. For instance, using Skydio's AI, we can conduct thorough inspections without needing extensive piloting skills, enabling us to perform high-quality inspections quickly and safely.

In one day, we captured data from five different large assets, showcasing how Skydio's technology can efficiently handle complex structures. The data we collect integrates seamlessly into ExxonMobil's inspection workflows, providing valuable insights for decision-making and enhancing safety and efficiency.

The Skydio X2, with its high-resolution imaging and 3D scanning capabilities, has allowed us to create detailed models of assets, improving our ability to monitor and maintain them. The use of Skydio Dock technology for remote operations further streamlines inspections, reducing the need for on-site personnel and enabling frequent, automated inspections.

Our collaboration with ExxonMobil highlights the potential of Skydio's technology to revolutionize industrial inspections, providing safer, more efficient, and higher-quality data collection.

Sterling: Just looking at the angles that we're able to achieve here. And just to take a quick pause and throw a question to you, Shankar, in terms of the data collection that we're able to do with Skydio, how is that fitting within your normal day-to-day inspection workflows, whether that's terrestrial, aerial, internal on some of these assets, or LIDAR-based? Have you seen an impact with Skydio data in helping not only blend, but also bring some of that data together?

Shankar: Yeah. No. Absolutely. I think, you know, one of the greatest things again, and this is, again, going back to what I said around having a foundation to start with at your respective corporation on how do you ingest data from different sources and being able to have kind of a unified platform, again, regardless of where you are in the world we're operating in, to have a standardized platform to bring in that data, whether it's coming in from a Skydio feed or another source to help with, like, what Sterling was saying is blending that through. And so we've been very fortunate to have a great team here within our ExxonMobil digital organization called the Digital Reality Ecosystem. And the we call it Dre, D-R-E. The Dre team has been instrumental in helping us on that journey and making it easier for folks like Sterling at Skydio and the rest of the team to bring in this data, and be able to blend it in with CAD and other models so we can start to superimpose and start to see as fit. And if you look at the accuracy of some of the models that Skydio is able to scan, I think we're very, very happy with that with the accuracy of those results.

Sterling: Thank you. So going on to some other assets that were captured, this is a fairly large one, in terms of some of the instances that we're able to discover post-flight, post-process here. You can imagine we've actually had some pretty large storms roll through South Texas in the last weeks and even damage, significant damage to downtown Houston. Right? So we'll just use that as a mock here.

So, being able to step out into the field, with the Skydio aircraft and quickly set up an autonomous mission, and capture the entire asset full coverage. And, again, because the aircraft is intelligent of its environment and is actively interacting with those assets to maintain those settings that we, as a user, can define, for quality or coverage, and then being able to then quickly assess those through, GAVIS and those structures that Shankar has highlighted today in the post-process environment. We can look at in finding, you know, damage to insulation, potential, insulation that was, you know, removed from post storm.

But, again, as Shankar said, we have now the ability to look at this asset in three hundred and sixty degree unrestricted space.

And this is just the reality model. There's, you know, tons of raw data that can be used in various capacities. So all of our metadata, exit data, telemetry, it's all open, for us to stay agnostic.

So this one data set can be processed in many different ways.

We do have streamlined Skydio cloud integrations and also direct partnership integrations, and I've recently launched Skydio Extend for professional services on that back end integration side of things.

So, again, being able to step out into the field and easily capture, a complex structure like this is possible with Skydio.

Shankar: Yeah. I think, you know, Sterling, it might be interesting to add, like, just to give, like, just to order of magnitude on a model like this. Like, how many actual images this is when you stitch it all together. I think on this particular furnace, I remember Skydio X2, I think, shot around, like, two thousand to three thousand images. And then then it was those images that were then carefully, you know, processed properly and stitched together, to build this model. So, you know, for any given area, we wanna hone in and look at the actual photo, the high-res photo, we can do that now with, you know, our other platforms that we have working with Skydio.

Sterling: Yeah. And then that's that's a great call out because, you know, some may think, well, it's a lot of images. Well, imagine trying to do that manually.

You could capture two thousand images on just the stack or the front side of the facade of this structure. Right? So that's two thousand images roughly of full coverage end-to-end as Shankar mentioned. Does any surface that is recognized by the aircraft during exploration and in flight will be captured?

And we actually have tons of augmented reality for you in AR observers and overlays to actually see and view insight into the autonomy, for overlap coverage areas that, you know, may or may not be, fully overlapped and also manual capture workflows within that as well if you see any significant damage. I will say, you know, there is a high level of autonomy here, but there is also a tremendous amount of flexibility for the user, during setup, overlap, distance to surface, the ability to pause the mission at any time.

You can move to maintain visual line of sight. You can pause to, let's say, conduct a safe operation to allow a nonparticipating personnel to move through. You know, this is an active refinery. Right? So full control of being able to pause an autonomous mission, take action, and resume, back in is completely possible.

And and that those number of photos are then the highest coverage while being, fully efficient on time-wise to provide, datasets like this that we're seeing on the screen.

There's another angle here.

Sterling: Excellent.

Sterling: So then even moving into smaller yet still complex, you you know, environments, we're able to to look at, you know, our smaller aircraft even still today is is quite relevant in in the pipe rack inspection or more confined space. Our obstacle avoidance is three hundred and sixty degrees, roughly one meter from propeller tips. And so the S2+ is a little bit smaller, so that footprint, for for standard obstacle avoidance will allow us to to operate in a a pipe rack like this a little bit more freely than an X2 or an X10.

So during this day, we really put the S2+ to to the challenge and and found some really interesting data on on live and decommissioned lines here.

Captured, it might be a little challenging to see, but, in terms of all of the, photo positions and freshman points here, green highlighted and raw imagery to even a shot from from one of the models here on one of the decommissioned lines, I believe. So jumping into, what a 3D model, can look like from a pipe rack inspection. I think this is actually, one of my more favorite inspections on-site, because there was an active, inspection happening not not too far off from from where we were flying, of a of an individual actively going through this complex and challenging area to work in to to inspect it. And I'm sitting there thinking, wow. If only he had, you know, the thousand images, two thousand images, or even a hundred, depending on what we're scanning in Shankar's end-to-end workflow to where he could have just reviewed, maybe the, you know, top ten key highlighted points for focus and targeted those versus actually having to go out and find what's wrong first.

And so that that was, really resonating with me in the field as the S2+ was flying through this entire complex pipe rack capturing, a couple thousand images within a short amount of time.

So in terms of, you know, not necessarily quicker, but better quality, better coverage, the autonomy and scale across your pilots, that you're able to, grow your network within data collection.

I would like to just ask, you know, like, what type of impact does this data here have on decision-making within your different business units within Exxon, a refinery like this?

Shankar: Yeah. I know. I think, you know, Sterling, good question. Right? I mean, if you look at first of all, just take a step back and just take a look at that, that asset right there.

That is a very detailed pipe rack, limited, you know, limited distance between each and every other one of those pipe racks. So getting in and out of that area is already risk in itself. A lot of it's done, you know, typically by rope axis teams.

And, and and a lot of them, we have to use, like, a pull on the stick kind of set up and have to manually go through there like Sterling was mentioning. So, you know, speed to market, right, for us is being able to get a very good perspective of that asset using, you know, the Skydio S2 drone technology that has a collision detect in a void like no other, to be able to properly and safely scan that, entire pipe rack for us, to a point where we can perform the basics of an API 571 inspection and and kinda go through this and look at some of the key anomalies and pain points that we're we're focused on, you know, especially corrosion under piping.

We call it CUP inspections as well as other other other parts of the, checklist that we have for pipe, pipe rack inspections. And so, you know, for me for us, this is this is a game changer, essentially, to be able to have a a robust technology like this to quickly scan the asset, get the the level of quality we need to do that analysis, and then porting this, you know, high quality data through, AI machine learning algorithms to speed up the identification of those anomalies and defects, and then localize them so I know where on this pipe rack these defects even are.

That is, you know, as if, you know, we're in there in the field doing this ourself, and that that's that's, to me, the the big game changer right now.

We're remotely being able to inspect a lot of this stuff.

Sterling: Excellent. Yeah. So we, you know, highlighted there from capture you know, in in field inspectors to to focus on those areas. As you know, in in field inspectors to to focus on those areas. I did wanna highlight, you know, I don't have the the camera positions, on on the screen here, but, you know, the aircraft was actively flying through that support structure in the entire entirety of that pipe rack.

And we do have an unrestricted gimbal across all of our aircraft at Skydio, so that does allow for, you know, straight down and straight up, unrestricted limitations during capture.

So in in terms of overhangs under under portions of the piper piperacts to straight overhead shots, we're able to to capture and coverage, cover those areas. So in terms of, you know, proactive of of of data capture being proactive in data capture, where do we stand, you know, moving forward if, let's say, someone was to go out and inspect this pipe rack tomorrow? Are we looking at capturing drone data prior to looking at historical data that was captured if it exists, or moving forward with that day to day inspection?

How do we view that happening today and and in the future, Shankar?

Shankar: Yeah. I mean, I think this is the beauty of what we're doing right now in terms of digitizing, you know, our our inspection workflow. So the historical stuff that now that we're capturing, we can use it, to determine, for example, change detection. Right?

If we identify, you know, an anomaly or, you know, from their from the data that was captured and analyzed, especially from our our AI algorithms. We'd wanna be able to measure whether that be, you know, the severity of a crack or severity of, specific corrosion that's taking place, understanding the rate of that change. And and so now we're just being, you know, more laser, you know, precise on exactly some of the key areas we're looking at. And so we don't forget and have to, like, lose sight of what we have checked, you know, a prior inspection because our inspection intervals are all different depending on equipment type and and age and whatnot.

Sterling: So, this is just giving us a a level of transparency now across, a wider, duration of time so we can now piece the store together and and then really start to build a predictive maintenance strategy.

I think that's, you know, you you think about the the the size of these plants, the amount of equipment we're we're having to maintain, having a way to drive a predictive maintenance strategy and, repair strategy using these kinds of technologies is gonna be, you know, really a game changer to help us pave the way on how we're gonna, run our operations in our sites on on on a future basis. So it's, definitely a lot more intelligence going into this now than ever before.

Sterling: Thank you.

Sterling: Alright. Moving on. So in terms of forward thinking, as as everyone knows, we have, recently, released our our next generation aircraft, our Skydio X10, which really resonates, you know, more powerful autonomy paired with higher grade, sensors and modularity.

So we have, a tremendous amount of runway for use within X10, from RTK.

We have NightSense.

We have, parachutes coming out, right, for operations over participating or non participating personnel, and also the ability to upgrade into different sensor packages as they're released.

So in terms of forward thinking and scale and adoption, autonomy is definitely going to be key in those conversations as we continue to look for more flights, more data, and more, accountability within inspections, and progress monitoring, etcetera, based on that data.

So with that being said, definitely, proud and excited to, talk about some of the remote operations that we are starting with Exxon, in terms of Skydio Dock operations within their facility, which allows for, some pretty groundbreaking regulatory work within Skydio's professional services offering and partnership with Exxon in order to achieve the proper waivers and meet the right regulation in order to achieve the end result and desired data.

And that, is possible through Skydio hardware, our autonomy, our obstacle avoidance, our safety, and our deep and and intimate understanding of of how the FAA operates.

We're able to take Shankar's, full, you know, program next step into the desired next step into the desired fully autonomous workflow here.

Sterling: So just take a moment to to ask you, Shankar, of really how you see, you know, some of those inspections that we did in the field across five assets, you know, in one day to now in a remote operations environment, being able to have scheduled missions, predetermined missions, and then also the ability to have a multiuse asset right where you're inspecting assets during the day. You have incident response when needed and also security as well across many different use cases as these are online connected, you know, IoT devices, flying sensors. So there's a lot a lot of different, values that we can add when we, go and scale up into full autonomous remote operations.

Shankar: Yeah. No. You said it well, Sterling. Absolutely. I mean, if you can see what we've gone through the slides and we went from a specific asset or assets to now we're looking at a site wide approach on how we do inspection.

I think the fact of having this Skydio Dock technology or just drone in the box technologies in general. Just give us an ability to do a lot more in terms of, periodic, inspection And it really touches on this entire predictive maintenance strategy, right, of being able to be more in a proactive mode than a reactive mode.

You know, maybe we don't have an interval per se that we have to inspect certain assets, but maybe there's a, you know, a heavy rainstorm hits, and we wanna go and send our, you know, drone in the box solution here, into our tank farms and being able to look at the tank roofs and just check and see that everything's looking safe and sound from an integrity perspective after that rainstorm. That's just one of many examples where we're looking at this from a, you know, kinda site wide perspective in terms of identifying use cases that will return value for us and maintaining, you know, strong performance and reliability of our entire operations.

And I think this example here is kinda showing you a footprint of a a typical refined degraded refinery chemical plant set up. But we also have operations, as you guys know, in the Permian Basin, which is our unconventional business that is got a lot of, different, equipment classes and types, but also it's spread apart. It's very much spread apart for those who've been to the Permian Basin and then and witnessed, all our well pads and, other other well pads spread apart like that. You just got a lot of coverage to to to maintain and to inspect. And having a technology like this to help us automate some of that inspections, is gonna is gonna help us greatly.

Today, we're you know, we we have to have people driving in pickup trucks and high you know, heavy duty vehicles inside, these locations and have to travel a far distance to get to the next asset to do do that inspection. And so we're trying to, you know, really mitigate the the need for some of that extended travel and the risks associated with that with using technology like this. And so we're really excited about just where the future is about automation and being able to use kind of dock technology, but their own in the box technology to support that, across our, asset fleet and sites, as we as we move across the world.

Sterling: Excellent. Really appreciate that. And, yeah, I've, had several trips out to the the Midland Odessa area, and, you know, it is few and far between, you know, driving out to each of those sites.

And you can imagine, you know, with our our professional services offering both in the regulatory space and also in API and integrations, being able to have a, a Skydio aircraft in a docked environment that is fully integrated to where you actually have a triggered, alert through your SCADA system instead of triggering a a truck to roll out. You've just, had an automatic API call that initiated a scheduled mission or a predetermined mission that flies to view that gauge or that sensor that could be in question. So I've I've had several very fun successful POCs in that capacity as well.

So when it comes to, you know, remote operations here, again, I truly do believe in in the in the, in the safety and scale that Skydio can offer in beyond visual line of sight, BVLOS, non BVLOS, skills based, or performance based, beyond visual line of sight remote operations. So, it's it's been really fantastic to see the growth. Very excited, for expansion, within different use cases and the improvements in these environments and data collection with X10 as we've offered now, much, more robust sensor packages, 640 radiometric thermals, telephoto, lenses, narrow and wide, and also the modularity of it.

So so quite excited to explore, new opportunities and data collection types, within your, facility, Shankar. So really it's been a fantastic journey that we've been on again starting in in the drone space in 2015 and and teaching myself every day how to be the best drone pilot to now teaching others about autonomous drones. It's it's been really a fantastic journey, and I would not be able to go into any environment, any complex environment, and feel so confident if it wasn't for Skydio. So let's, hit the next slide here.

Host: And I think we're pretty good on questions time.

Host: Just wanna make sure.

Host: Yes.

Host: We save early or late.

Host: No.

Host: I think we've saved plenty of time for questions.

Host: Just as a reminder to everyone, if you have not already done so, to ask your questions, please use the Q&A box and hit send to submit them.

Host: And let's see. Our first question here, is Skydio's AI ready to fly in dark indoor spaces? For example, inspections of furnaces from the inside.

Sterling: It's a great question. So first, you know, before Skydio X10 was released, I'd be thinking about how much space do we have, how much lighting do we have. Right? Well, the Skydio X10 in in our, groundbreaking product that goes with it, payload accessory, NightSense, we actually can physically illuminate our our flight area both in the infrared spectrum or the visible light spectrum with a module on top and bottom of the aircraft. So now that question really is how much space do we have to operate within those environments?

And Skydio's standard obstacle avoidance, again, is one meter, three hundred and sixty degrees from propeller tips, and that's driven by those six onboard navigation cameras that feed our neural network and process those world iterations and allow us to be intelligently aware of our environment.

So to to directly answer your question again, through Skydio NightSense, both in the infrared or the visible light spectrum, we are able to actually have obstacle avoidance at night. It is very groundbreaking, and one of the most advanced features in my opinion.

Host: Awesome. Thank you. And are the deliverables for reporting from a Skydio software or from a third party?

Sterling: Yeah. Great question. So that is going to be in that partner ecosystem. Right? So Skydio is is an amazing tool that provides the solutions and the software and the hardware to capture the data.

Sterling: And then there, we have, again, more software and integrations and Skydio MediaSync, Skydio Cloud, Skydio Extend to port into existing or new workflows, for individuals such as Shankar or businesses like Exxon to seamlessly integrate. So, if you wanna quickly, Shankar, hit on again, just just hover or some of the, softwares that you use to integrate and and how you do that with Skydio data, I think that would be great.

Shankar: Yeah. No. I mean, I think in general, you know, we've we've got a wide variety of different platforms, you know, to help support different business problems we're trying to solve. Right?

Shankar: So not every inspection necessarily requires per se, certain certain features and capabilities. So we we are very, you know, careful on how we wanna manage that. But that's the the beauty of having that level of flexibility with a foundational platform that gives us that restaurant menu to choose when we wanna use something that requires 3D model versus what needs, some particular AI machine learning algorithms to scan that first. Right?

Shankar: So I think that the the unique thing here is here is having the ability to have the data, you know, easily to be shifted and managed without having, too many, you know, chefs in the kitchen, as I call it, and having that data smoothly come in and and then be able to kinda go in into the different platforms we choose depending on the business problem we're trying to solve. So yeah.

Sterling: That's one of my favorite things really about, the back end of of the API and and and Skydio Cloud ecosystem, and I hit it earlier on on the, call, is one dataset can can be used for an inspection team through an AI machine learning and processing workflow, for reporting. And that same dataset could also be used for modeling and integrations with terrestrial or aerial grade lidar, for design teams, you know, registering and and recognizing as built to design.

Sterling: So we have that ability to seamlessly port one capture through many different processing engines so that your, end to end clients or your users are working in that data ingest area and not the drone capture data workflow processing workflow.

Sterling: So we have, again, some pretty streamlined workflows to where you're living in that end to end goal versus having to worry about the drone and the capture and the processing.

Host: Great. And someone else is wondering, how long did it take to capture the two thousand images on the furnace and how many battery swaps?

Sterling: Yeah. Great question. So, we do have the ability to break up missions, really. You just set them up and then also think about maintaining overlaps, same settings, etcetera.

Sterling: So I broke up the mission for a couple of reasons. One, maintaining visual line of sight, radio connectivity, right, and then also coverage and efficiency, and also being able to resume the mission back into this complex about three, three and a half batteries, so about thirty minutes of flight. So we were able to break that up pretty quickly and and capture a large structure like that, quickly. Keep in mind, I was out there, doing a POC for both inspection, showing the technology, but also being able to walk away with a high quality model, and also be able to capture five assets within that day.

Sterling: So, with that being said, there's a a tremendous amount of flexibility kind of heavy kind of heavy in photogrammetry and you understand a lot of those settings, then you'll you'll be quite excited to see that flexibility in setting up only a z axis higher, a higher, end user, I guess, more historical based in photogrammetry would find quite useful to change in terms of inspection versus a pure end to end photogrammetry data set use for reality models or design work. Right? That that different initiative would change a little bit if Shankar just said I needed, you know, the chimney stack or I need, you know, the latest photo collection versus a full end to end inspection workflow or reality capture, that flexibility is totally designed within the system for the user to define number of images, number of footprint of overlap, etcetera, with insight prior to starting the mission.

Host: Great. Thank you. And do you operate the drones in the rain? And what gust or wind speed can you expect at the oil platforms, and how do the drones cope with that?

Sterling: Yeah. Great question. You know, all all of this information is is always paired within our Skydio support articles and, overview and manuals just for y'all to have as reference. But we'll find, about twenty five to twenty eight miles an hour with the X2, S2+ in terms of wind tolerance, I would suggest.

Sterling: And and really that's in a comfortable range. We have to think about flying in new environments with closer proximities and autonomous actions. We have to be cautious of how the aircraft is behaving in winds that are higher than that. Right?

Sterling: Much higher than that. I actually did spend, several days, offshore, and we we had a a safe metric of about twenty six knots, to maintain. And we experienced a little bit more, but we were able to, mitigate and perform safely within those environments. So both onshore and offshore, everyone knows the Midland Odessa area can get quite windy, etcetera.

Sterling: So for current dock landings, right, we're about that thirty thirty mile an hour threshold miles an hour with a forty minute flight time.

Sterling: So it can handle, miles an hour with a forty minute flight time, so it can handle, more wind and is more robust with an IP55 rating, which does allow us to fly in that inclement weather, dirt, dust, debris, rain. We do have to keep in mind that, you know, we do have computer vision. So if we do, impede our computer vision, we do have those workflows defined in terms of disabling obstacle avoidance and listening to GPS or vice versa, for those environments where, again, it's inclement weather and and our vision navigation sensor may not have a reference. Right?

Sterling: So, hopefully, that answers your question. I did do a a nice, ortho mosaic the other day, in in some in some lights to moderate moisture, and it it was, quite an enjoyable flight as some other aircraft who were left in their case.

Host: Thank you.

Host: And someone else is asking, Shankar, referencing your one hundred locations that are using drones, how does that translate said, our model said, our model from the start is, you know, to scale quickly.

Shankar: So we partnered with, you know, third party strategic drone operators that we had vetted through our Exxon Mobil aviation departments, globally.

Shankar: And so for that matter, you know, we we don't, you know, we we actually are, quite lucky in a sense that we have a a interesting model that allows us to scale up or scale down.

Shankar: And so these these strategic drone operators are essentially the ones that'll help us, with the latest equipment and even more pilots as needed depending on the demand. So, yeah, we don't track that that information to tell you the size. Now our internal teams are different, but, like, those those are far far than few. Right? Because they're more focused around certain areas of the world that maybe are very, remote and, you know, depending and having a lot of dependents on a third party would be challenging.

Shankar: But for the most part, we we are heavily scaled out with a third party, support model for these hundred plus locations around the world. And we rely on on those those those great partnerships to to help us manage our program.

Host: Excellent. Thank you. And how has drone technology improved safety standards during inspections at ExxonMobil? Can you provide specific examples where drones have mitigated risks?

Shankar: Yeah. I mean, I think, you know, like I said before, some of the biggest areas where we're deploying drone technologies into confined space locations where you typically have, you know, whole whole watch monitors and you you're gonna have all kinds of, you know, you know, PPE requirements to be able to enter some of these these these, these assets internally to do those confined space inspections. And so a lot of that, you know, carries a lot of safety risks. Right?

Shankar: And so when you have personnel inside the vessels. And so now having robots be and you know, derisk the situation in many ways and also reduces the nest all those associated costs of having all those additional services requirements, motorized equipment, and scaffolding, especially when you start looking at, assets at heights. Your scaffolding costs will quickly, amount to quite a bit depending on how high we have to get up there and inspect some of these assets. So a lot of that is, mitigated.

Shankar: And on top of that, some of these inspections are done online. You know? In the past, when we have to send personnel, we'd have to take the unit down, especially on some of these flares and stuff. And now a lot of our flare stack inspections are done online while the unit is up and running, and we can safely, be be able to capture all the the high quality data we need to build, a proper, model, and look for those anomalies while the, you know, the units, the flares are on.

Shankar: So, you know, these are some of the big things that support, overall value capture because, you know, every, you know, every minute our equipment is down. You know? We're we're not we're not producing product, and we're not then therefore producing any earnings.

Shankar: So this is a way for us to continue our operations safely as well as be able to understand the mechanical integrity of, of our asset structure.

Host: And has let's see here. Sorry. My screen just adjusted. And is Skydio inspecting offshore installations as well?

Sterling: Yeah. I'll take that one. So, specifically, with Exxon, we we haven't done anything offshore that I'm aware of. Correct me if I'm wrong, Shankar, in terms of of something I may not be aware of. But, we have had other instances.

Sterling: Again, I had mentioned that I I had spent several days offshore, and other clients that are utilizing the technology offshore.

Sterling: You'll you'll find that there are a lot of similar assets offshore just more in a condensed space.

Shankar: Yep.

Host: Excellent. Thank you. And someone else is wondering, are FAA permissions or waivers ongoing and permanent, or do you need to apply regularly?

Sterling: That's a great question. So definitely, you know, a conversation for the Sky Skydio regulatory team, but we definitely look, both from a, operations perspective, a historical record of your organization, and what you plan to do, what your intent is, and determine in which pathway is best for you to achieve that goal, whether it's skills based, performance based, operations, BVLOS, C mode, etcetera. There's a lot of different pathways, again, depending on the environment that you're in, the operations that you're trying to conduct, and if you have any historical records of operations that are deemed, you know, safe and valid within the eyes of the FAA, Skydio, again, professional services offering, architects that entire workflow, and defines those waivers, which usually are good for, a much longer set of time. You know, it could be two, four years where you you'd have to then do a resubmit, for that specific waiver or any type of exemption.

Sterling: Again, we'd we'd love to, you know, get your contact information and and discuss regulatory services at Skydio further.