 So my name is Arthi. I'm from Shell India. I'm a digital commercial lead taking care of commercialization of digital products created in Shell in collaboration with several partners. So we have an external ecosystem and I'm also the open-source lead at Shell and I closely work with Dan Brown who's sitting in the first row you know many others in Linux Foundation energy and we deeply appreciate what Linux Foundation energy has been helping Shell with in the context of open-source and energy transition. So this is my topic. I'm going to talk about how open-source is helping us in our journey of energy transition and specifically I'm going to take an example of data platforms, data standards and take that as an example and help you understand how open-source is really a must and needed for energy transition for the globe and not just for one company like Shell. So that's about my talk. This is a disclaimer slide. So everything has been wetted. So if you hear something about some of the publicly available information, you have all rights to quote it. So yeah, so cool. I want to acknowledge my leader here Dan Jeevans who is our VP for digital and computational science. He's also the decision executive specifically for the open-source program. Bryce Bartman who is our chief digital technology advisor and also the business opportunity manager for open-source program. Hari Ramani, my line manager. He's the GM general manager for digital innovation. Ian Betts who is the business opportunity manager specifically for data platforms. So I have four sections in my talk. First, I'll take you through the why, why energy transition and digitalization are intertwined. In the second chapter I'll talk about how open-source plays a role. In the third chapter I'll specifically talk about the core capabilities in the tool called real-time data ingestion platform that we have open-sourced via Linux foundation energy. And the last one is about how this has really wide networks of application even beyond energy sector, right? It's it's beyond energy sector, right? So that's that's what this talk is about. Since we last about five minutes I think I'll try and say that's why I have enough time to hear your questions and engage in discussions. So let's go into why so this this is a report titled digital technology the backbone of net zero emissions future It's a it's a report driven by MIT technology review insights There were about 350 c suit executives who were interviewed who who were Requested to give inputs to develop this report. It's editorially independent. Shell did not influence this in any way Shell has participated though. So you can see our VP Dan Givens has participated in this report. So What's what's what's behind this, right? So why am I bringing this? It's a very recent report just few months ago It came out It it it has addressed inputs from nine industry leaders As I said 350 c suit executives digital technology chief advisers chief for data officers chief information officers, you know All the very senior level executives of many industry sectors and there are about eight sectors that have participated So energy mining metals transportation petrochemical manufacturing industrial manufacturing Construction retail All these sectors have participated in providing inputs and geographically it's spread across North America Asia Pacific and Europe. It's not restricted to one location in the global context and to give a bit more views on what what is the demographics of this about 30% of respondents are from North America About 50% of the respondents are coming from the industry whose revenue is in the range of one to ten billion and about 30% of respondents correspond to the industry whose revenue cross or it's beyond, you know, 10 million 10 billion Yeah, so so it's a very, you know unbiased and highly covered You know Report I must say so given that background. What is the outcome of this report, right? So let's look at it So the report clearly found out that these eight different industry sectors Have their own different ways and scales of how they and how they work on Sorry decarbonization and how they are, you know evolving in this journey of decarbonization Definitely, you know, they have their own Players and they have their own favorites when it comes to levers for decarbonization digital is one of the most fastest and arguably one of the cheapest lever for decarbonization while I'm not standing here advocating for digitalization alone, but it it was found in this report that digitalization is one of the You know best leverage that we should take into account for decarbonization. So that's that's what it found and This is where it becomes even more pertinent for You know the climate goals of this planet. So what are we doing as an energy company, right? So Needless to say we we need unusual partnerships. We need You know boundary less ways of working and partnering with external people when I say external external to shell This this is where Linux Foundation energy has helped shell enormously to partner with many other companies and You know, this this isn't a clear example of open innovation and open ecosystem needs Which is connected to how digital can help in decarbonization and that's where open source comes in So with that I'll move on to the next slide Let's let's address why energy transition and Digitalization are intertwined, right? So as you can see on the blue side, you have mostly technology-driven aspects on the red side, which is energy transition It's all all related to non-technological related aspects including political commercial operational aspects, right so Needless to say You know these these two are intertwined in their own manner If if you want to decarbonize the entire value chain of a particular energy system Digitalization has shown a enormous, you know benefits whether it's about the operational efficiency or CO2 emissions or how they are in deep how they are dependent on each other digitalization has played a big role and We can think through digitalization in context of data and AI, right? I mean digitalization is a very broad word. So we can go a little bit more specific and AI and data They provide the mechanisms and tools to what we call as you know reduction of overall CO2 emissions and how they do is by overall optimizing the energy system and AI and data has also provided this powerful way of you know coming up with entirely new low-carbon energy footprint systems for example in a coordinated power systems Decentralized energy systems beat any any of these two examples I mean it has made it a lot more Coordinated lot more flexible when it comes to consumption of energy it has also made overall better in terms of efficiency and Not just in the power sector in you know whether it's a highly decentralized, but network You know sectors, you know for example aviation fuels carbon sequestration and storage and hydrogen Digitalization has become very very relevant for us and in shell initially, so I joined shell 16 years ago Initially we used to sell digitalization to people now we see everybody working on digitalization be it business be technology be it Finance functional organizations. We see everybody having digital expertise sitting in the organization So it's not anymore a centralized team, but even the skills and the culture has been decentralized, right? So I hope this explains how these two are intertwined The next expert is the integrated aspect, right? So energy system is not of one kind We have multiple energy systems. We have Traditional refineries now even for traditional refineries example in Germany We are using renewable energy as a person means to produce energy to run the refinery So we have installed a very high mega watt Proton electrolytes system to generate clean hydrogen which is further used in the Germany refinery called Raindland I mean if you look at this they are integrated in one way or other be it hydrogen solar electric vehicle charging road transport Conventional oil and gas assets the CCS. They they are not independent anymore They have a lot of interdependency So this is one of the other layer that we can go so we so far talked about energy transition and digitalization this is an another layer of you know Importance where digitalization clearly adds tangible values and if you want to do an optimization and integration at the system level You can't do it without digitalization And if you see data is the equalizer in all of this, you know If you just take an example time series data whether it's a solar form Which is all about how the weather input data is going to affect the overall prediction and intermittent of solar You know, you know asset performance or is it? hydrogen asset where it's a typical process industry you have to You know process the real-time data of the process values like you know temperature velocity and all of this It's it's the time series data that equalizes among all of this, right? It's just one example It's not the only example. It's just one of the examples So this is where shell is doing some fantastic work So we we don't look out Look outside the world to help us in this if we see yes This is the strategic way we can go ahead Otherwise we will not have interoperability between the technologies of these different energy systems That's where digitalization team comes into play and says we will govern how the data acts as an equalizer It's not just about data as in Management of data. It's it's also about data ownership data. Master ship data accuracy It's it's everything that's related to data and hence this is Senior group of leaders in shell who govern how this data acts as an equalizer and interoperability Enabler across this integration of energy systems. So So I started with the why energy transition and why digitalization and how they are intertweaked talked about MIT technology review insights outcome Which is a global study and I talked about next layer how as by taking an example of Integrated energy system how digitalization brings that in interoperability Let me address next how we are going to transform the energy system with all that we have talked so far right so Here it's not anymore about technology alone. It's it's it's about culture It's about unusual ways of partnering. It's about going out of traditional barriers You know having open-ended Collaborations where we help each other and I I think that's that's the change that we have seen in the last ten years At least in shill that that has really led to the transformation of energy industry So while technological innovation is core of it. It's not just that alone It's about how we have moved away from traditional, you know Biggest energy company who has their own secrets and patents to how we have started talking about openly sharing our codes openly sharing our data standards because It's not a individual player energy transition is a team sport We need to actually collaborate with our customers suppliers system integrators technology partners in an unusual way, which is Really needed for rapidly accelerating this because we don't have a lot of time for reaching our climate goals So I hope I have addressed the why of it so far Let's go into how aspects right so Open source. I mean this this is not just how it's it's it's it's one of the key enabler We see in shell as as a means to you know enable these Transformation of our assets into highly optimized and You know autonomous assets as self-optimizing and autonomous assets that actually talk seamlessly to each other And even if they are completely from different energy mix different end of the value chain How they integrate and talk to each other? This is where we really rely on open source as one of the key enabler now I talked a lot about how data is important how data enables AI a bit more on on that context so if if you look at You know how we do business. It's it's not about You know having a set of confidential data working on it within the teams even within our Internal ecosystem we have enough transparency to work seamlessly without any vertical silos in the organization because We can't do proper digital transformation of assets if we can't have a standardization of our data and we can't do it if we don't manage it if we can't do it if we don't Efficiency efficiently process those data in cloud. We can't do it if if we don't have Reliable reliable data standards across our assets So that's one of the key area where open source becomes very very important whether it's it's related to math behind how we calculate methane emissions or CO2 emissions or it's related to how we report it in terms of Structure of the data these standards have to be open source And that's where she'll is going on we we just started with one tool called real-time data insertion platform Last year in October and November last year, but we are already working on 10 different open source projects now So this this is where a data enabling AI is further enhanced by open source The second is culture and learning so she'll has got its You know a cultural program called she'll dot AI which has got 15,000 internal You know community members and it has also reached out to external members. We have done 40 hackathons this the same shield at AI program has a Residence program called she'll dot AI residency program where we bring in talents from MIT rise and Indian universities European universities globally in Netherlands London Houston and Bangalore specifically these four locations we have this two-year program where we take a young talent and nurture the talent Learn from the young talent and also, you know Make sure that they are also up skilled in a unique manner via our collaborations with Udacity as an example to you know meet these Really challenging problems to join the vision of energy transition, right and last but not the least the access to talent That's another place where open source plays a huge role while We know the problems that we face and we understand it better But there's nothing that stops us from taking help from others Outside she'll and it's it's not in a right to say anymore that we know we will solve it Ourself and we don't want to collaborate that's not going to work and open sourcing has helped us to collaborate with extensively with our partners We have left and right many partners coming to us in the context of both open source and commercialization Commercialization which not only makes our products talk to their products seamlessly, but as I said in the previous slides It's it's the global decarbonization Strategy and agenda that's that's behind that right? It's not about how these individual companies can make more money because they cross sell and upsell their tools together now It's not about that. It's about the global agenda of climate goals So in in this context, I also want to Give another example, we we have something called open AI energy initiative The founding partners are C3 dot a Baker Hux shell and Microsoft So we started this in 2021 and previously before this initiative Specifically for oil and gas customers operators Technology partners in that space there wasn't any market place where they can bring their products. They can Collaborate seamlessly by integrating their products for example C3 dot a platform is now integrated with the digital twin platform from Kongsburg via this Well, we are four partners. We have enormous number of other partners like Kongsburg infosys axelos Senesco are all part of this initiative. So What are we doing there? It's it's not as open as open source, but We have both binding and non-binding contracts within this framework wherein we Integrate our tools in a meaningful manner and also we also collaborate on open sourcing some of our tools Especially the foundational technologies that needs to be open source because the collective success matters So this this is just one example and here The novelty is there wasn't any such a platform before so now we have several partners who are joining us We have three work streams one on upskilling one on product work stream and other on sales work stream It's it's about working on customer backward strategy and understand feeling the pulse of what they need Not focusing on PR press release, but actually, you know Understanding customer problems. They're really really pain points and solve their problems, right? So this this is one place where we didn't have a marketplace still till we created this and This year we have made a major refresh on how we are driving this how we are upskilling each of us For example something that Microsoft has already done in a very very good fashion in in the context of cloud Infrastructure we don't reinvent that wheel in shell We don't let our partners like C3 dot AI or Baker Hughes reinvent that wheel. It's a kind of a mutual trust You know oriented Platform where we come and share each of our strengths and we take help from each other. This is just an example of How you know we work in open with other partners So some of the benefits of this now because of this we have got Enterprise scalability of our tools one of the example is predictive maintenance, which is about how reliable The assets are and how predictable their performance is how safe their performance is we have scaled from few hundred equipments to now several thousands of equipments without doing it in a manual fashion and we are further scaling up and Imagine we have assets and also the world has assets which are not digitally ready There are assets that are being digital. There are assets that are doing real digital There are assets that are not yet even ready for digital It spans across all of them and how you scale up your tools digital tools is based on The platform help that we got from C3 dot AI some of the infrastructure that we got from help from that that we got from Microsoft and Needless to say it has led to full interoperability So our technology works seamlessly the digital twin to tool of Kongsburg The platform from C3 dot AI and the core heart of it is our you know Algorithms which which comes from the domain expertise of shell engineers They all talk to each other in a seamless fashion and it's not just a shell We have also sold this to our external customers Galp adnog Chevron Petronas as an example So, you know, this is this is all about how you can have an end-to-end Integrated tools. So that's the last bit one point and also, you know Integrated domain specific solutions We don't rely on just AI we we bring the synergies between AI and physics based models So that's one of the things that we have been very successful in scaling up via C3 dot AI platform And other solutions from Microsoft and Baker Hughes So let's go to chapter two So far I talked about why and gave some examples of how she'll has been working in open Both via open sourcing and via open AI energy initiatives So this is as I said last year we open sourced our tool. It's called real-time dataization platform It's a tool that we are very proud of it. It has gone several years of development From America to Australia and every shell I said this is the tool that's working a day and night To you know produce some of the fantastic valuable results for us Not just on efficiency, but also on carbon footprints, right? So what is this? What is this tool about right? It's about how we you know do an efficient way of dataization and how we do that in cloud and also how we provide a user-friendly You know algorithms and Additional tool kits along with this heart heart of this tool called RT deep to enable any users from world Just because now that this is open source. Well in X foundation energy Anybody can now download it and you will also see how user-friendly it is because of some of the Python wrappers that we have already built in and this is an another example where you can scale Across different sectors. I talked about eight sectors from that MIT technology report transportation constructions for so many sectors Each of these sectors can be benefited via this because it's at the end of the daytime series dataization platform It's all about how we efficiently do it how we structurally do it consistently and how we Actually also share the results of the data crunching or the data processing to other systems So this these are the strategic values we we have already started to work with Company partner types called technology partners for example C3.a Kong's books and as co come into that category We also work with operator customers For example, we are now working with the cement industries in India and some of the other global locations Which come under hard to obeyed sectors and they're struggling a lot when it comes to decarbonization but using RT deep we are helping them to connect the you know quintessential Electrical related technology products digital products to process engineering products, right so Strategically, you can work Seamlessly with other sectors support integration via this platform We we definitely have used it in the context of interoperability So I mentioned about Kong's book digital twin. How is how is this and that connected, right? So because this is now ported on C3 platform and it works on C3 platform and because C3 platform and digital twin are Integrated this is also integrated with digital twin So while digital twin can help on both the static and the dynamic data Without the connection with RT deep you you really can't for example If you do a machine vision end-to-end a tool integration for understanding where the problems are in the set You can't map the 2d image data to a 3d location of the asset Especially assets are of Olympia at field sizes that kind of integration is also enabled via You know how how we make those tools talk seamlessly to this RT deep data platform There are few other examples one of the thing is We do not distinguish small operators small customers small technology partners big technology partners We don't want to do any of those business here. It's a fair share mechanism irrespective of How small a company or how big a company each of them have their own visions. So many smaller companies have reached out to us You know after Experiencing for a few months with the RT deep they have come and reached out to us on some collaborations We have they've also reached out on some help from our side So this this is how we can enable You know decarbonization in my humble view. We can't distinguish companies a small big here This is not about status gate. It's rather about how we can really work towards Decarbonization and in that context some of the cement industries that I mentioned They don't make a big revenue, but they make a lot of CO2 and they're polluting our environments and You know I come from India India is second largest when it comes to see products steel production and also second largest when it comes to cement production and We are still a developing country. That means we have enormous needs for cement production in the next few decades If not centuries, and if you don't tackle these problems, we're not going to decarbonize the world So that's that's the agenda behind this. It's not about You know being first being large here It's rather about being together and working together in this space to help each other and it leads to You know seamless partnerships. That's that's something that I'll talk about in the last chapter So some of the tangible value from this real-time data ingestion platform, right? So How we do data utilization today? It's it's not something very uniform whether it's weather data, which is a time series data or process data there's a lot of For the want of a better word divergence and inconsistency in how we do it This is one of the areas where this RTD has been extremely useful We are now working with many power companies who wants to Collaborate with us, but the base layer will start at the infrastructure layer starts with RTD And some of the services from Microsoft and C3 dot AI on top of that that company wants to bring their tool and we shall Wants to bring our tool with all these foundational layers such as RTD we are able to make Contributions to each other and help each other in our decarbonization journey It's it's not something where we we have not taught through Scale up today. We are at four trillion in terms of rows of data within shell It's it's a public information available and it's You know crunching data from three million sensors from shell assets in total globally And it's beyond energy be it power beat other sectors food Supply chain industrial manufacturing any kinds of defense It is not, you know Specific to one sectors. So these these are the tangible Values I must say I'm not repeating some of the things that I already mentioned Going to chapter three, which is about core capabilities. So what you have here is Where a very efficient way of how you process time series data in the in the in the cloud and You start from the streaming points It could be event hub or Kafka and then you file it into a Delta lake house, right? And I talked about how users can actually work with this without Having much of a knowledge on how it works, right? So that's where Python SDK and rusty APIs come There's not a big difference between Python SDK and rest API. These are meant for different types of users So the Python SDK enables how the users can interact with the data. So it has got a security layer it has got an You know deployment and execution user enablement Similarly rest API also does the same thing. It's it's also about interaction with the data But it's for two different kinds of users now going into You know RTD bestiki SDK as I said, it's it's it's all about building executing and deploying has got a fantastic way of how it You know queries can be executed RTD PPA is very similar. I suggest you read the documentation links are provided here And my talk has been uploaded in the internet Open source semi page as well now going into How we have applied it for energy transition in shell, right? So I talked about three million cells working on this are providing data into this RTD platform and How the you know Scalability is also managed with the four trillion rows of data all that but where is it going? What is it doing right? That could be one of your question and this is where I want to say it's it's it's the Right time to think because I request you to go through it go through Linux foundation energy website and search for RTD It's it's not about whether we we can collaborate in this space It's about how we collaborate and how we move ahead, right? So I really suggest you guys to join as partners with us and it's it's not about You know one particular sector as I have repeated multiple times It's all about how we can have a world that has Seamless foundational technologies if you want to have a good control of scope one to three emissions and really want to Contribute to the climate goals. We can't have Thousand tools with the different Standards which don't talk to each other and each of them competing in the race of climate goals No, that's not going to help and of course if something else works better than RTD We are happy to move on to it as well. So long long story short It's it's really a request from my side It's it's the right time to think bigger in terms of climate goals in the context of sustainability Why technology innovation and why interoperability is the key for energy transition? This is just an example as I say data management is just an example and we consider data as an equalizer because that Connects all other sectors So I already talked about integrated systems a quick reinstating of what I said We have multiple energy systems from traditional oil and gas to renewable energy and They they are not any more working as individual energy systems We're doing very big system level optimizations and digitalization plays a very big role here just reinstating what I said before These are some of the specific examples electrified chemical reactor. So just as this example, right? So steam crackers, we know that they're very energy intensive You you can't have a steam cracker without having that very high gigawatts of power generation And that eventually means you you are generating a lot of CO2 and polluting the world conventionally it runs chemical reactors are running based on you know Supply of fuel burn the fuel generate heat and then use that heat furnaces Or what's being behind the scenes right now? Imagine if you replace that traditional technology with the electrification If we electrify one steam cracker, it's equivalent to removal of 350,000 cars in Europe our road So can you help hello? So I'll continue till then so that's just an example right so So the other example is systems level modeling, right? So I talked about cement and steel industries Traditionally they they don't have Renewable power in their mix for example, I quoted Rainland Germany example where we have gigawatt level of proton electron You know electrolyzer which generates renewable hydrogen and use that as the power to run some of the operations in that Rainland refinery Imagine the same thing if the power mix can become renewable in the cement sector You you can actually go towards net zero carbon in these hard to obeyed sectors But how to do that? How do you install a? Electrolyzer with all these challenges that we have with intermittency of solar power intermittency of wind power That's that's that's not something you can solve by working on one system Which is a small it requires a very different lens scales at at the electrolyzer level You have to do multi-scale modeling computational models physics-based models that come into picture But at the scale of larger integrated systems and even integrated between different plans and different assets you will have to do a plant-wide optimization and a plant-wide modeling and Imagine the level of interoperability that you need to make cement plant talk to a solar plant from which it's extracting the power or Wind power wind plant from where it's extracting the power. It's it's unimaginable. How much is the complexity? So this is a one place where we have been extremely Benefited by leveraging tools like RT-Dip because we make sure that's that's at the foundational technology level and that's how the data is structured managed Processed crunched and shared across these different plans. So, you know, we just make sure that it's not just for process industry It's for electrical. It's for every other sectors, right? So when we collaborate with internal or external assets, we make sure that we we bring in the same open-sourced RT-Dip as our foundational technology so that you know tomorrow We don't have one big problem which doesn't talk to this technology and we don't know how to solve it Or we have completely different standards and we are again diverging Convergence is the only way and hence open source helps a lot. The third example is better cooling of our EV batteries Based on our simulations again a lot of time series data crunching and physics based model data crunching What we have found is our product called shell e-fluids is 30% better than the market fluids in cooling Batteries which if they get overheated can cannot work can be in danger and cannot do what they are supposed to do Now this has led to a partnership with crazy and they are also now hence using RT-Dip and you know These these are some examples sustainable aviation field in 2021. We have managed to produce Synthetic kerosene from carbon dioxide water without any a non-renewable feed into the mixture and We have powered the real passenger flight from Amsterdam to Madrid and it became a huge news again a lot of technology interoperability there Sorry, so CO2 water In in presence of electrolyzer. We created a few Yes, but your primary fuel does not have a non-renewable footprint. Yeah, so your net zero Carbon is managed there Yes, yes and Safe storage and transport of hydrogen. This is the last example with that. I'll close my talk This is a fantastic example. We have intensive thermodynamic expertise in shell and Combining that thermodynamics knowledge with our digital tools such as RT-Dip We we have strike a very big deal under DOE of US Our project has been selected in creating a large scale but manufacturing and transportation of hydrogen liquid hydrogen for both green and blue hydrogen and Yeah, needless to say it would have it would not have been possible without the digital interoperability and You know all the benefits that we have derived from our partners in this space Yeah, so with that I'll open for questions Okay a couple questions. Thank you for your talk really appreciate it Okay You talked a lot about data management Is there and you also talked a lot about improving Interoperability, can you explain a little bit more about why there's such complexity between say a steel plant and a solar Generation I didn't quite understand where the compact complexity lies is it in the prediction or is it in Changing the transmission of power and then like adapting. I'm not I'm not really sure. I'm not a power expert. Sure. No problem. So Like you said that cement industry example, it has to talk to the power plant in a digital way And also to a wind plant in a digital way And if the data are not die or not convergent if they have different diverging structures different diverging Formers and also how how they are processed if they have completely different technologies behind it Solving that itself is a big mess Okay, if they use different standards of communication, you mean it's not just communication It's it's about how you maintain the structure of the data how you report it and how you maintain that as a seamless uniform format across all assets and Efficiency also right, you know, if you don't know how to crunch the data You know, if if you have a hardware sensor that's monitoring the data because it's just yet another sensor present in the set It's put in the DCS. It comes to you via a Process information system. There are various ways Aviva has got this OSI pie soft as a tool for example At the end of the day, if you don't know how to get that very quickly into the cloud If you don't know how to do number crunching for that big data in a very efficient way And if you don't know how to report that in a structured way Uniform structured way. It's not going to be easy. You will lose a lot of time just in processing and doing it and RT Dip solves that problem. Yes. Okay, cool. Okay You focused a lot on data. Was there specifically data for communication of sensors? Was there anything about? Storage of electricity or operating grids like there was slight mention of distributing power and stuff like that so anything about balancing grids or Maybe more specific to grid operations That shell is working on that. Yes improve efficiencies overall Maybe not so much like again processing and data efficiency, but more about grid operation efficiency and how technologies Yes, yes, so I can't quote the name of the partner We are working with because we haven't signed the contract and it's not it in public release But this is an area again for hard-to-abate sector customers We are partnering with one of the quintessential electric company where, you know, they are good in what they are doing They they have a fantastic distribution of power networks. They they are good at doing microgrid simulations But they do not know how to do the integrated system modeling And how to do that efficiently to provide the help that These hard-to-abate sector customers need so we have a partnership Which we are going to sign where shell will bring in our expertise and our tools which we call as background IP of shell They'll bring their background IP and together we are a lot more synergistic and also like I said in all these example cases we steadfast insist on interoperability and having a common foundational layer How you do data how you pass data how you work with the data how you communicate data We we are convinced if you don't have uniformity and diver convergence there We will not be efficient So this partnership is also leveraging RTD and top of that some of the proprietary tools that we have not open source yet plus system modeling computational efforts from shell site and from their side they bring in the Experience and the expertise and tools related to power Thank you. It weren't you speaking in the morning. Yeah, I was in the in this room in the morning to start off Thank you very much for the presentation So you spoke a lot about the role of the open source software that you guys are developing in LF energy for optimizing the The system of an organization, right? Which is really useful, you know, thank you a lot for showing that I know also within the LF energy group. They're also work on I believe it's called I Believe this is a very important for Shell as a traditional oil and gas company on the carbon data specification This see the CDS. Yeah, which deals. This is coming from their website Dealing with the raw data and standards for data requirements that enable energy access for measurement and tracking carbon emissions From production through to consumer. So in this case, you're not dealing with just optimizing data within a system But optimally is using the the flow of information across Cross-systems which for an oil and gas company like like she'll can be really important and I wanted to just know if you Have any exposure to this work in LF energy anything that Shell is doing on that on that front Which which has to do with the flow of information across this customer base and supply chain base It's something I'm personally interested in like to hear your thoughts a few Completely completely resonator CDS has been in our purview for a long time now We are considering open sourcing some of our tools related to methane emissions and it's not very easy methane emissions imagine wind velocity Various other parameters that can actually influence all the data Has to be processed right then your baseline correction becomes extremely difficult in these cases So definitely we are going to work with Dan Brown and his team on this. So Really good example where you know companies like Shell has to work with Linux Foundation energy on topics like data specifications It's a no-brainer. Yeah, okay Well, maybe we could talk a bit afterwards because specifically on the point of methane emissions scenario We've been focused heavily on our data certification and tracking for oil and gas industry emissions And we did some prototyping on that. So it'd be interesting to hear what you mean Maybe also explore joining LF energy as a member. I know there's a certain formality So I can maybe learn from you. So it'd be great to hear your thoughts on that. Yeah. Thank you everyone. Thanks