Part Two: Digitalisation trends in natural resources

Dal: Yes, you're getting efficiencies and you're getting ROI on your bottom line, but you're also doing well for the environment, and GIS is core to that. 

Disclaimer: This podcast is brought to you by the team at Boustead Geospatial Productions in conjunction with our affiliates – Esri Australia, Esri Singapore, Esri Malaysia, and Esri Indonesia. To get your hands on more short, sharp and immediately usable resources, head to the GIS Directions Podcast website and check out the show notes. 

Wayne: Welcome to GIS Directions. I'm Wayne Lee-Archer.  

Mary: And I'm Mary Murphy.  

Wayne: And we welcome back Dal Hunter to the conversation today. We had so much to talk about that we needed to bring him back for a second go. Welcome to the show again, Dal. 

Dal: Thank you. 

Mary: So Dal, it's very obvious from what we've been chatting about, that we are in what I would call a period of very rapid digital transformation. And that geospatial thinking is a vital part of working with natural resources, be it mining, forestry, energy, agri, you name it. 

So, I wanna pick your brains a little bit about what we're seeing, what the trends are, where we're going; and I know a lot of the listeners will be very keen to hear this from you, and you did mention that you've identified four emerging patterns. So I think it was sustainable business operations, instrumenting the planet, which we touched on a little bit, but we'll go back to. Advanced analytics, around enriching decision-making and then geospatial excellence. So, you know, that mission and business-critical enterprise systems side of things.  

So, let's talk through each of these in turn. Maybe help us understand what they are and what's happening in that space when it comes to geospatial tech. And maybe we'll start with sustainable business operations.  

Dal: Absolutely, and that sustainable business operations is one of my favorites, only because we've been doing this for years. Really we’re thinking about it now more from the sustainable lens. And Wayne, just as we were talking about the guitar maker. 

Look, sustainable business operations, you think about it, it's operations and management and maintenance and security of that physical asset. 

And while we've done this for years to improve efficiencies, improve productivity, reduce risk, it's time that we evolve that story a little bit more to think about things that are relevant in today's times. And one of those areas is ESG, right? Environmental, social, governance and being able to really talk about how ArcGIS supports that. 

Cuz it's not only about increasing the bottom line, but it's doing better for the environment. And the efficiencies gained you know, if we look at, from an operating asset, I'm gonna give you an example from oil and gas. Okay, if I have to go and visit 10 well pad sites, what is the most efficient manner that I can get there? 

Can I reduce the windshield time from a safety perspective? Can I reduce the drive time from a fuel consumption perspective? And if I do those things, you know, and I reduce the amount of time that we're in a vehicle driving, well that's good for the bottom line, but it's also good for the environment. 

And so that's where it's sustainable, again through both lenses yes, you're getting efficiencies and you're getting ROI on your bottom line, but you're also doing well for the environment, and GIS is core to that, and that's where I really think sustainable business operations, it's almost just the way that we talk about it. And that's evenly internally in an organisation or sharing out with the public.  

Mary: Yeah. And that brings it back to, again, if you're looking to have that sustainable business operations or improve upon it and look for those one per cent tweaks to make it more efficient and more effective. You know, if you're a junior mining company, for example, how does that, you know, work for them? 

If they're jumping into now leveraging the geospatial tech and they, they have this aim of sustainable business operations, what part of the tech can they use to help them? How can they get their feet wet?  

Dal: Yeah. I think at the core of this, when you look at the pattern, it's back to that system of record and developing that so that you can truly understand your operation. You understand your assets, and understand the impact that they have today, and look for ways that you can improve upon that. 

To me it's very simple. Get you an ArcGIS Pro, start developing that system of record, get an ArcGIS Online subscription. I think about customers that have just one Pro. I think about this in the US when I talk to some of the small operators, they are mapping that asset and now once they start to leverage ArcGIS Online, that opens the door for so many more to see and understand the patterns and the way that they operate that they couldn't do before. 

It's being able to see and understand those patterns and you don't have to have this massive infrastructure to do it to start out.  

Mary: And I suppose building out from that, you're starting small, and you might do things like, um, you know, start with the data. Let's see what we've got. Let's get that system of record, let's manage that data and then we can start to build it out. Where we're getting that data from is also changing. And we were talking about that next emerging pattern, and that's in the world of instrumenting the planet. Do you wanna dig in a little bit more on that? What are we actually seeing specifically in the natural resources side of things?  

Dal: We have seen for a while new instrumentation coming on the market and whether that's from sensors that capture raster content such as satellites or aerial or drones, that's one aspect of it from the instrumentation.  

I think the other is devices that are attached to an asset to capture emissions and let you better understand those emissions. You know, I think in agriculture being able to use sensors to understand soil moisture and content and all the new information that, some of this information you could get before but it was really difficult to capture. 

Today, and this is where GIS I think is crucial, it's really good about integrating into a variety of systems and bringing that information together. And with all these different instrumentations, especially in natural resources, it's really critical. 

And then you can go from simple to advanced, you know, I think about shipping and AIS. Every large vessel out there has a beacon on it that sends a signal and we're able to see that in real-time. Understanding routes and patterns as we develop offshore wind. It's really critical because there's work going on out there. 

How do existing shipping routes get affected if we're gonna install a wind farm offshore? How do you make sure that you're looking at collision avoidance while work is going on? It's being able to bring this information in, into real-time and visualise it, and a map is the perfect medium for that. 

Wayne: I would love to know a little bit about the tech that we are seeing leverage behind this. All of these new sensor information coming through, how are we funneling this down into our GIS? If we're seeing such a burgeoning industry in, you know, this kind of sensor data, how is this being handled from a technical perspective, how are we ingesting this into our GIS so that we can get those insights? 

Dal: Well, I think the great thing about ArcGIS is the flexibility and the openness, to be honest, right? So, depending on your needs, you know, it can be from very simple that you need data once a day possibly, right? You can have an ETL process with just a Python script running the background that pulls this information in. 

But if you want more timely information based on your needs, maybe you are gonna use things like Velocity to stream in that real-time information. And Velocity is, again, we talk about, well how do you get started with some of these things? Velocity’s a SaaS, so you subscribe to it, now you can bring in real-time information. We tie into multiple types of sensors and feeds. We tie into event hubs from the major cloud providers like AWS and their IoT portion of their stack. Same thing with Azure.  

Being able to bring that information in, perform analytics on the fly, those solutions are readily available today. And we're seeing an uptake in that because again, we've had some of the technology, GeoEvent, we've had it on premise we've been able to do these things in the past. But as more and more come on, you know Velocity’s really starting to take off. You don't have to have that infrastructure onsite, it's ready to go. You turn it on, you start connecting your feeds, and you're collecting information and visualising it in real-time.  

Mary: I love velocity because it breaks those gates down though as well, because if you are relatively new to this, and this'll bring us onto our next little topic quite nicely as well, is around the analytics, the advanced analytics. Well, what does advanced mean to you? Advanced to you could be you getting started and doing some very basic analysis using the union tool in ArcGIS Pro, right. 

But if you do want to dabble in those big data feeds those more traditional advanced analytics that can seem scary. So, something like Velocity, if you are going to jump into that instrumentation and then leverage something of the tech stack to actually do something with that data, Velocity is a lot easier to jump in and start playing around with. It's very beginner friendly.  

But I'll use that as my segue into the advanced analytics which is one of the points you brought up, Dal. So, again, advanced analytics is an emerging pattern, isn't it always?  

Dal: It is, and it's a perfect segue because you start thinking about advanced analytics and if we use Velocity as a springboard, well Velocity, one thing about it which is great, you think about in the mining industry or in any industry where you're going out and you have operations in the field and you're collecting real-time information. One of the things about Velocity is it can perform analytics as that information is coming in. 

One of my favorite examples and the one that stands out to me in oil and gas is, they always want to know when their staff or contractor has entered a site. So, when have they entered the lease? And if they have a device on the truck or on their person that's capturing their location, as that information streams in we can say, is this point within this boundary? It's a simple analytic.  

Wayne: Geofencing 1 0 1. 

Dal: But it's performed on the fly. Now, the beauty of Velocity in capturing all that information is you end up with a lot of data, which is great – what can you do with that data? You wanna start looking for patterns and trends. And this is to me, where advanced analytics comes in. Things that you couldn't really see because, did you have the data? Well, maybe you weren't capturing, but now you're bringing in real-time information you're getting massive amounts of data.  

How do you make sense of all that? And that's where advanced analytics really comes into play because you start to look for those patterns and ask questions of that massive amounts of data. And that's an area again that, as we progress and there's more instrumentation, there's more data, which requires more analytical capabilities. That's probably the one that's inspiring to me because we're getting asked questions that we couldn't ask 10 years ago. 

Mary: Or we were asking, but we knew in a month of Sundays we'd never get the time or the budget to go out there and capture enough data.  

Dal: Yeah, I would ask the question and I'd have to wait a few days to get the answer cuz it would process for so long. Now I can get those answers in less than a minute. 

Mary: Yeah, and with the analytics side of things, it's a case of, I suppose from the data science side of things, be careful what you wish for. Because you're gonna get all this data, like you no longer have to have these very specific, let's go out in the field, put these sensors out for a period of time, we have to bring them back in and then digest that data afterwards.  

When in, you know, reality we've been leveraging satellite imagery, for example, good old Landsat for X amount of years to do a lot of our monitoring. Now we can actually put our sensors out in the field, leave them there long term, have them come in, set up our workflows, have it working on the fly, right up to, you know, things that don't need to be as real-time. But we can do that.  

You know, I think it's gonna make our workflows and our field research, for example, in if you're trying to do things like exploration or re-vegetation etc. having sensors that you can leave out there and feed in, in real-time is definitely going to increase efficiency because you're not the only people asking that question of where? So, we then need to leverage more advanced analytical techniques to handle that data. 

So there might be a little bit of a learning curve there for people to go, okay, well, we know what the questions we want to ask. We know the data we need. How are we now getting that big chunk of data in, and how can we get the most out of it? How can we ring that data dry?  

Dal: Absolutely. And, and you know, Mary, it's one of those things where, as you get massive amounts of data, you don't wanna be moving a copy of that data around. And this is where I think I mentioned a product earlier called GeoAnalytics Engine, we've developed a technology that we put the capabilities where the data is, you leave it in place, you analyse that, you derive results, and you work from there. That's an exciting area as well because of the way that we can perform that analytics. I'm sure throughout your career you've had to copy data. And it's like, oh… 

Mary: Yes. 

Dal: The time. And, you know, just to get the data in an area, then you're duplicating data, you end up with multiple copies, then you have questions about authoritative content. Where's the authoritative data set? You know I see in all these companies now, right, you wanna leave the data in one location and perform the analytics where the data is. There's multiple benefits for that.  

Mary: Yeah, the last little step of that analytics now is the prediction, because if you have this high resolution, temporal, spatial resolution data and lots of it, that's a good amount of sampling for you to go, hey, let's do some predictions. 

From the data analytics and the data science side of things, if you're instrumenting more, we can learn more about those phenomena that we're interested in and then we could actually start to do things like, well, let's predict or endeavor to predict and understand.  

So, there's lots of opportunity there as well within the stack to work with those AI Machine Learning techniques. If you wanna leverage Pro or for ArcGIS Bridge, you have Notebooks. I mean, we could go on with those as well.  

Wayne: One of the things I've learned with Machine Learning is that data is king, you know, in a lot of ways data is the new oil. It's another new natural resource. Once you get this massive amount of data that's coming in, it really leads itself towards that next question, doesn't it? Machine Learning. One thing that we've learned with Machine Learning, is more data you can throw in a model, the better it is at being able to make predictions and being able to analyse the data that you're using these Machine Learning tools to analyse.  

What we've heard today is the data's coming in thick and fast, we're collecting it in the field, we're collecting it with sensors, we're pushing it through things like Velocity and Field Maps and Survey123. We're getting this vast amount of data coming in. Agribusiness is burgeoning with all of the robots out there in the field driving tractors around. Sounds dangerous I know, but what possibly go wrong!?  

We've got the data streaming in, and now we're using, you know, these kind of really deep learning models to analyse that data. We're seeing some great things like, you know, crop health analysis from drone and other imagery in the field in real-time because of this big burgeoning, evolving field of data that's coming into the systems. 

Mary: So that leads us on, I think to our last point, geospatial excellence. So, what are we seeing in the emerging trends geospatial excellence wise for the natural resources crew? 

Dal: You can do all this great work, you can do all the analysis and analytics, but you've gotta be able to make the information and those capabilities accessible to the business. The business is the ones that hold the SMEs, the ones who truly understand some of that data that's coming in. 

As GIS people, we can do a lot of analytics, and we may have some subject matter expertise, but people in the business really know and understand that data. And that's where, to me, when I think about geospatial excellence, how do you get that information out to them? 

How do you incorporate them into the specialist, into the workflows to help you make that decision? And I think Portal is key to this. It's really delivering that wealth of capabilities that GIS allows across all lines of business. GIS again is good at integrating into multiple systems cuz we're not gonna be the only system you use, right. 

You're gonna use AutoCAD or Autodesk, IBM, Microsoft, SAP. A number of them. And again, I think regardless of the industry, bringing this information together through a portal, establishing that, whether you want to call it a platform or a system that people can have access to, that is key to demonstrating and creating geospatial excellence within your organisation. 

Across my career as I've seen organisations deploy these portals, it's really one of my favorite things to go in and see the things that are being done because you can't even imagine, cuz you're getting these capabilities in the hands of people who are not GIS analysts and GIS specialists. 

But they understand that data now they have access to it through a map, and it's always interesting the questions that they want to ask. And I think that's the key thing because they know questions they want to ask, they just don't know how to get there. And as GIS analysts, we're the ones that can help them get there. 

Mary: So that's ArcGIS Enterprise as a business-critical set of infrastructure. 

Dal: Absolutely.  

Mary: And again, you don't have to start out with the perfect monster of the infrastructure side of things. Chat to the local teams, talk about what you need and start with the aim to build as you recognise your needs and so on. 

Dal: It's a journey. It's a never-ending journey, which is great right, because there's always gonna be business challenges that you need to address. You're never gonna be finished. That's one of the things that I've always loved about being in GIS, there's always something else, a business challenge or a business need that comes up and there's a spatial component to it, and we're like, huh, haven't thought of that one before.  

How can we address that? Do we have the technology to address it? And there's just so much going on in natural resources, it impacts all of us in our daily lives, natural resources do. And so, there's always areas for us to leverage spatial to improve those workflows and processes.  

Mary: It's amazing to see all types of organisations, but particularly some of the larger ones that are leading the way. So for example, you did talk about ConocoPhillips, and Brian Tran discussing that journey, that digital transformation journey that they went through, and if you have an opportunity, go back and watch that recording from the ERGIS23, he did a great job of discussing all the different stakeholders and the different thought processes and planning, etc. that they had to do to get this thing off the ground.  

And it didn't happen with a hard cut-over in two weeks and that was it and we're done. No, there was a lot of planning, thought around the adoption side of this communication is key, bringing everyone on board for the journey and making sure that they actually had the infrastructure that they could work with and wanted to work with at the end of it.  

So, I think that's an excellent example of showing how people are in different parts or stages of their journey, and people have different kind of ideas of the life cycle of the GIS as well. 

Dal: Absolutely, Brian tells a great story because it is a journey and you need to involve different members across the organisation, different lines of business, get them to understand and the value that it's gonna bring them. And again, we see it from small organisations to large ones. It's the same, it's just the scale and the technology's accessible to both.  

Mary: Excellent. In a nutshell, Dal, why is GIS a critical business system for any enterprise working in the natural resources sector? 

Dal: Well, I think, as GIS has become more an integral part of the everyday workflows in these organisations, going through the digital transformation, the way that they work, the way that they leverage that information. We've talked about instrumentation, all this information, GIS is a great tool or great system to surface that information.  

And so it's really becoming a mission critical system inside of these businesses. If that system is not working, they cannot operate the way that they need to. And so, you can think about that with other systems as well that might be out there like SAP and work orders, you know, if they can't get work orders out that's critical to their business.  

Well, GIS and ArcGIS has become that as well. It's used in so many workflows because everything we do is inherently spatial. I know we think spatially, I think spatially all the time. So, the way that all these natural resources companies work, right? It's assets, it's physical assets, they're inherently spatial. And so GIS has really been recognised as one of those systems that can improve business, improve operations, it's just become mission critical. 

And we're seeing it across all the industries, which is great as a GIS professional to see the recognition that spatial is getting within these organisations today.  

Mary: So as a GIS nerd, it is great to see it. It is fantastic.  

Wayne: And what we've heard today is that the natural resources sector really seems to be one of the big driving sectors for what we are seeing, the success of GIS at the moment. You know, this is where the data comes from, you know, all of those layers that we have on our digital twins and on our maps, the forestry layers, all of these things that we throw on there by default because they're the things that we see outside through our own eyes. 

They're all coming in from the natural resources sector. And I'm a little bit surprised cause I didn't expect that's where things were coming from. So, where to from here, I suppose is the, is the question Dal, what's the next big thing?  

Dal: Well, look, I think GIS and spatial in the natural resources space, it's been there for decades. So, it's been leveraged for a long time, but I really believe we're just tapping into the potential across the complete enterprise. So, for me personally like, I'm really looking forward to the next few years to see where it goes as people in the organisation truly understand the power that spatial brings.  

There still is this education that has to go on with an organisation about the value of spatial, so while we might think, oh, what's the next big thing? Is this advanced analytics? Yeah, in some ways it is, you know as technology advances we are able to do more and perform more analytics, but I truly believe that the, the exciting part for me at least, is the belief that people are becoming more educated and more spatially aware. 

And so we're gonna see just more and more spatial solutions as I would call 'em, that you're gonna see that are bringing value to organisations. So, years back we used to say, we've gotta get all this data, you had to collect data. I mean, today we have data. So now that's where it gets exciting because of the analytics and the decisions and the predictive modelling. 

I guess if I had to pick one area, Wayne, I’d think about the predictions, the predictability. Being able to analyse this, look for patterns and predict, I think we're gonna see more and more of that. And that's where the digital twin itself has become really important, cuz being able to understand that in the real world, in context and being able to model out and predict what's gonna happen. So exciting times ahead.  

Wayne: So digital twins are the answer, I'm expecting we're gonna see better fidelity and more realistic digital twins coming out of the natural resources sector moving forwards! 

Dal: Absolutely. You, you're gonna see more and more through gaming engines, you know, fast access display, real-world immersive environments. I think that's the thing we're gonna see more and more of as we move forward.  

Wayne: Well, there you go people, you heard it here first. Real-world immersive environments. It’s the next big thing!  

Did you have any final words that you'd like to leave us with Dal?  

Dal: Just, want to thank you both. I think, again, natural resources is something that's key to everybody out there, to our whole world, it's a resource. All those industries, whether it's how we generate more food to feed our populations as they grow, but also more importantly, you know I think about natural resources in GIS and the applicability of ensuring that we have a planet that's gonna be here for a long time, and that we protect that planet. I think natural resources is key to that, and GIS plays a role in making sure that we do that appropriately.  

Wayne: Absolutely, a hundred percent agree with you. 

Mary: And Dal. That's it. Thank you very much. You've made it through again, thanks for coming back and rejoining us. 

Dal: All right, thanks guys. 

Wayne: You’ve survived a second episode with us. 

Mary: And we will add any and all of the resources we've mentioned to the website, gisdirectionspodcast.com.au, including any information you'll need to get started with any of the tech that we've mentioned. 

Wayne: And we're really looking forward to hearing from everybody on the socials, so hit us up there and stay spatial. Until next time.  

Mary: Stay curious. 

Disclaimer: The views and opinions expressed in this podcast are solely those of the hosts and guests and do not necessarily represent the views or opinions of the Boustead Geospatial Group of companies.