Transcript for "What's new in Spotfire 14.5": Once again, I'll add my thanks to everyone, for joining us here. My name is Brad Hopper. I'm the VC of Industry Applications. So what does that mean? I help to try to figure out which kinds of problems we solve in the various industries that we serve here at Spotfire and do a little bit of prioritization for what should come next in the the Spotfire, application in in collaboration with the awesome people in the, product strategy, product management organization at Spotfire. I'm gonna talk to you, myself, and my colleague Athir Alatar, who's sitting down here, will join me as well-to-do some demonstrations at the end. We're gonna talk about what's new, just say what's coming in Spotfire 14 dot five. Spotfire 14 dot five is not yet released, but it's coming out in just a couple of weeks, so we're within the time window. Of course, it's okay for us to talk to you about that. And let's, actually, this presentation was put together lovingly by the organization and the product strategy organization. There were a 130 slides in this presentation. So I put a lot of effort into reducing that down to a a manageable subset, but I wanted to say that if you wanna get into more details about what's going on for the developer, what's going on for Spotfire administrator with the features and functions or the the technical content with respect to data functions and whatnot, do reach out to your account executive and you can get some more details about that, within your own organization. But for now, let me dive in here a little bit. A little bit of a disclaimer. We won't be talking about too much about futures because this is, what's, you know, on deck right now. The Spotfire Visual Data Science platform, as we've talked about before, combines interactive, agile data exploration and advanced energy analytics. And so our goal here is not just to provide you a set of tools, but to provide you the kind of environment that allows you to express your own expertise and creativity for solving these different kinds of problems. The presentation from Diamondback was amazing. I loved how they got into the details of super technical, like, lifetime mortality statistics for pumps. And then at the other end of the spectrum, they're talking about kind of operational managing operational and business concerns in the field. We want that. We want our our our, customers to be able to take Spotfire wherever you need it to go for you. And so part of our goal here is to make it possible to unleash that expertise and creativity, but also allow you to build applications that you can share those best practices across the organization. So we'll talk about how we support doing that in the fourteen dot five release. So the pillars of 14 dot five, what is what is visual data science mean? So first of all, this kind of idea of exploratory interactive analysis of data has been there from the very beginning, all the way back to, I think, 1996, with respect to, getting, asking, and answering questions, figuring out what the next question might be before you can then go ahead and ask and answer it. And then, the industry focus is now, I think, undeniable. We're here now for the second year after the kind of respite in COVID, talking to you about what's coming specifically to to support the oil and gas and upstream energy and midstream downstream energy use cases. We've been spending a lot of cycles on that. As Stephen mentioned in the kickoff, one of our primary objectives here is to tell you about what we're doing, but more importantly, to get feedback from you about if we're headed in the right direction or what else should we do next in order to kind of complete the picture there. And then finally, enterprise scale. Charlie had some great remarks about how they're managing an infrastructure to support a large organization and a large deployment. So Spotfire, unlike some other tools, is actually designed for large scale deployments of this kind of analytical, kind of creative environment for problem solving. Okay. So you may or may not remember this, but in about February, we released spot Spotfire 14 .four. And as a part of that release, we actually repackaged, the offerings from Spotfire. We had something like 200 products, which is kinda crazy. So we consolidated that down into just these key five products. And I'm just gonna talk about the top three today. Spotfire analytics, Spotfire data science, which is was a new SKU as of 14.four, and this is where we're putting a lot of our, energy specific content that that I'll talk to you about for Spotfire fourteen dot five, enterprise, and then, of course, the real time capabilities for enterprise data streams and advanced data services, which we spoke about a little bit earlier as well. So we always like to think about not just features and functions, but what are the themes? What are we trying to help our audience and our customer base accomplish? So we like to keep in mind here optimizing system performance. So we've got a number of investments in the enterprise SKU itself that help administrators manage the system to try to understand its utilization. Is it being used effectively? What can we turn on? What can we turn off? You know, running a tight ship as as kind of as Charlie put it. Optimizing core business processes. So this is at the core of how you ask and answer questions and solve technical domain specific problems with Spotfire. And then this last bullet is super important, increasing value with continuous innovation. So I will tell you in the in the last kind of Q and A session with Diamondback, somebody asked a question about security with data functions in Python. We, that keeps our engineers awake at night. This is something that we care a lot about and we spend a lot of time focusing on how can we make it possible to continuously release new capabilities in the product, but at the same time, make sure that we're managing the safety and the compliance posture that we we know that you all need to maintain in your organizations. So we probably spent the the lion's share of the data science team or the data functions team focused on how do we package up and and and manage the kind of, lineage of Python functions that we wanna deploy as part of the product. Sneak peek, we're deploying Python functions as part of the product. So this idea of allowing you to continuously solve new kinds of problems, not just by writing your own functions, that that we always want you to be able to do, but by, in consultation with you all, identify specific functions that you think will be core to your business processes and delivering them directly inside of the product. Okay. So I'm gonna start with I don't know. Depending on who you are, this might be the boring stuff, right, Spotfire Enterprise, and then we'll kind of get into the vertical domain specific stuff right towards the end, and then myself and Athir will give you a couple of demonstrations. So with Spotfire Enterprise, I wanted to just highlight this was released in Spotfire 14 dot four. We put a bunch of effort into, building more automation into the system, making it possible for you to, for example, loop through a series of unique values in a in a dataset for an automation output to perhaps, you know, send for each property that you're managing, send a different set of PDFs for those users, to be able to embed custom iron Python jobs in automation services directly, to personalize that content so that you could make sure that everyone is getting the content that they need out of those automation jobs. So this is not something that's new, but in 14 dot five, we're continuing to kind of double down on expanding the capabilities for automation and scheduling. So now we have a much more granular possibility of scheduling on a hourly, daily, weekly, monthly basis, and you can specify rules that reoccur so that you have a much more fine grained control over which kinds of jobs are being, launched at what time. And then if you are now, one of those organizations who's using automation services and you're using information links and you're using the infrastructure capability of the server, we have much more detailed proactive monitoring in place so that you could see, for example, how long is this information link taking to return. So you might discover there's some optimization that could be done in the database in order to to improve that. How often are these different, jobs being requested. Information services processing. So it's everything in the stack. We're starting to add more and more observability functions so that our administrative users can try to understand how to deliver the best possible operational efficiency to their organizations. Now this was, I think, one of the most highly requested features, in our, ideas portal and that's notifications, not only with email, which we've supported for some time, but we're adding adding the, different ways in which you can configure emails, but also HTTP based notification systems. So again, Diamondback talked a lot about their Teams infrastructure. Other organizations might use WhatsApp or they might use Slack. So many of them were starting to see standards emerge around how to publish messages into these queues and these channels. And it's now possible to take a number of notifications that come from the Spotfire infrastructure and feed them via these kind of chat communication vehicles that you all will be widely using. Everyone's using something different, so often it becomes a a little bit of a numbers game here, but luckily there's some standards starting to emerge that we could take advantage of for, populating those systems with notifications from the system. Now a deployment report is something new for Spotfire. We we have had kind of utilization reports built into the system before, But we've had, oftentimes when it comes time to do a renewal, sometimes the customers are obviously they wanna be compliant with the system, but it's been a little bit of extra work to try to figure out what, in fact, are you actually using. And so this allows us to or allows our administrators to, just with a single button, get access to a lot of detailed information that can be useful for that discussion around, the renewals, but also about utilization. Who's using which assets in the library? Which ones are used the most frequently, the most consistently, parameters like if you have a larger deployment, how many processes, processors are being used. So again, this idea of observability is a significant enhancement on the enterprise side to sustain these much larger deployments that we see across the oil and gas business. Okay. So that's it for now. There's actually a lot more content on the enterprise side that I omitted from this particular presentation. But But if you want to learn more about that, as I say, get in touch with your with your account rep and they can hook you up with a more detailed personalized conversation about that. So let's talk a little bit now about Spotfire Analytics. So this is the basic blocking and tackling around asking and answering questions that you're all familiar with. We are advancing the authoring experience in Spotfire. So you might have seen this properties panel. I mean, everybody knows when you when you right click and get look at the properties for visualization, there's just this huge list of things that you can customize in Spotfire. And if you're like me and have been using Spotfire for twenty years, you have a little bit of muscle memory around built up around that. But, what we've found in in talking with customers is that so often you only touch a few of those properties and not all of the ones in the detail, and you have to kind of scroll past a bunch of them in order to get to the one that you want. And also, there's a difference between how you configure visualizations on the web versus how you configure visualizations in the desktop environment. So we're bringing those to parity and in doing so we're improving the overall kind of properties configuration experience in general by putting them into this visualization properties panel on the sidebar. So this has been in kind of preview mode for quite some time. It's now generally available in the product. You can set the properties on your visualizations in the same way that you always did. Just look over to the right instead of right in the center. But there's some significant advantages of this. Number one being it's a single interface that works exactly the same way on the web and works on the desktop, so that you don't have to remember where to click to do the same thing depending on which environment you're in. Then also there's a whole series of enhancements, such as, we'll only show you the properties that have been modified for that particular visualization, not like a long a long list that goes down seven pages. And you could search the properties. You know, last time I gave a, a road map presentation talking about this, I actually got applause on that because sometimes you know it's in there, you just can't really quite remember where it is. So you can search for the property, make a change, and then that will appear in the list the next time you go back to make a modification. It'll be there waiting for you. Another key advancement here is that it's possible to say set the colors or other properties on multiple visualizations at once. So you might choose three different visualizations and you wanna say, I wanna use the same coloring scheme for formations across all of these charts. And it's possible to do that now with this properties, team. Thank you. Yeah. I mean, it's so convenient. You know, when you when you have to go and tweak them one at a time, you're like, darn it. This is just the same thing I just did in the last visualization. It saves a lot of precious time and and frees up those, synapses for doing more creative work. So we put a lot of effort into this new visualization offering experience. And as you might imagine, bringing the web experience together with the desktop experience has been a goal of ours for probably six years now. I'm doing it a little by little. This is a pretty significant moving of the ball forward in that in that respect. I went back. Let me click the green button instead of the red button. Okay. New web based visualization authoring capabilities. So you might know that some of the older visualizations in Spotfire, you could not configure them on the web. You could only configure them on the desktop. You could consume them on the web, but not author them. And so that's changed with Spotfire 14 dot five, specifically the box plot, the heat map, and the summary table, it's now possible to create a new one in the web and configure it completely as you would do with any visualization. So we're kind of going back through history, mopping up some of these things, and bringing them all, to first class citizens in the web based environment. Let's see if there's anything here. Oh, the box plots in particular. How many of you all use box plots? Excellent. I come from the manufacturing space. It's all about box plots. I wasn't sure to what what extent you all would use them. Them. But that's fantastic news because we're making a lot of investments in this box plot visualization. It's now possible to support multiple scales, to support a separate scale by trellis, as some of the other visualization, capabilities do. And we even have some significant plans in the future that I think my colleague Daniel might say something about, with respect to reference information that relates specifically to the box plot and other visualizations. Okay. Custom marker shapes. I think Michael showed you a little screenshot about this. We kind of scoured all the energy sources that we could think of. I think there's one called the shell red, if I if my recollection serves. There's a a whole series of different collections of images that are often used and associated with different types of what the well is producing, whether it's an injector well, whether it's shut in, and so on. There's also a lot of industrial kinds of shapes. We're not shipping collections of shapes out of the box, but we have some available for download via the community so that you can go and get access to them, bring them into the product, and take advantage of those. And you can also create your own shapes. So if you have custom, you know, icons that you would like to use to display on a map, for example, or really in any visualization, you can take advantage of that. You can create custom groups so that you might deploy a particular group to a particular type of user who is all the time going to use those shapes, but maybe not the other shapes. So again, thinking thinking through the whole use case and making them as usable as possible. You can store these in the library, automatically update them as you automatically update applications that use those collections. If you update the collection in the library, it'll get propagated to the to the applications that use them. You also have control over color and a few other, attributes here. So a significant amount of effort went into the custom marker shapes. I think this was another one that, in particular, for oil and gas had lots of votes on our on our, ideas portal. Okay. I keep pushing the red button instead of the green button. Alright. Viewing and managing data table relations. So as you know, a Spotfire file can contain more than one table and often contains more than you want. By the time you have analyzed to your heart's content, you've ended up dragging in pieces of information and creating relationships on the fly that now you can't remember what you did. So the Spotfire Data Canvas makes it possible now to see at a glance all of the relationships that are among all of the different data tables that you might have in your application, and maybe sometimes more importantly, data tables that don't have relationships. What am I missing here? Why am I not getting my mark records in the way that I want? A quick look at the table, relationships, panel here will answer that question for you. You can also define relationships from the data canvas here. There's maybe two different places from which you can activate that functionality, but I find it quite convenient to be able to do all of my kind of data management tasks on the data canvas itself. Okay. Data access improvements. So this is a little bit, you know, for the administrators, but also for those hungry end users who want to get data from all these different systems. So we've had many different requests to kind of, complete the picture with respect to single sign on for all of the different data sources that exist out there in the world. This is a labor of love. There are many, many different kinds of data in the world, but we're kind of knocking them down one at a time. So in this upcoming release, we are supporting OAuth two, OIDC, for multiple data sources including Oracle, Snowflake, which I recall the Diamondback folks were calling out, and also WMS Layer services. We have also now added new connector web user interfaces. Again, with this kind of alignment of the desktop versus the web, changing the data connector configurations was something that previously had to do in the client, but now it's possible to make those changes for data connectors in the web UI. Some more kind of assorted capabilities here, private endpoints for Google BigQuery, and also, I I think importantly, for the future, reading and writing data from Apache Parquet files. Just curious also, quick show of hands, who knows what an Apache Parquet file is? Not that many. A few. How many of you are using them in production these days? Okay. So the parquet files is a a column or data store projected into a file into the file system along with some metadata. So it makes it possible for you to query parts of files much much more rapidly if you're if they're not in a database. So oftentimes, these parquet files are at the base of all of those data link technologies that you've been hearing about. Parquet is kind of plays a central role in that. So now we have native direct access and support for connecting to parquet files directly. Connector prompting. So many of you have used information services for many years, and we built that out over a long period of time. So there are a lot of features and functions in information services that have not had parity in the Spotfire connectors framework. And so we're basically finishing that process out now so that it's possible to, use a connector to to connect to any one of those data sources. And when you launch an application that depends on that data, you can prompt the user to say filter down to just the region that they care about in that particular data set. Or filter for just a subset. We we support enums, so somebody who's building out one of these applications can themselves construct a list of choices that's not necessarily in the data, but that has some meaning for the application and provide that to the end user to map to data that you might go ahead and query. Optional prompts, this is also quite important. Sometimes you want to give the person the possibility to filter something down, but if they just want all the data, you don't want to force them to select everything in the, in the selection criteria. Custom analytics with action mods. Okay. So we're getting into the kind of interesting part here, I say. So action mods is something that we introduced a couple of releases ago, but we didn't actually release any action mods. So this is a framework for automation. I think Michael alluded to this a little bit before. We have visualizations, native ones and plug in visualizations. We have data functions that calculate on data and create new data. And then, I think, somebody mentioned this, that the data function itself cannot create visualizations unless you use IronPython. And IronPython is a little bit on on the outs with respect to Microsoft. So we wanted to make it possible to not only make calculations, but also customize visualizations using pure Python, which we also support directly in the application. But we didn't wanna make it possible to direct we wanted to improve the security posture of Python, as I said earlier. So what we did instead is build another piece of the infrastructure layer that's specifically designed for automation. And if you'll bear with me for giving you a little bit of a sidebar on this, you all use maps quite frequently, obviously. My home industry, the semiconductor business, also uses maps. But those are so called wafer maps, and they display where the chips are on the silicon wafers. They don't use CRS coordinate systems. They don't use latitude and longitude, but they are quite happy with how you can use the Spotfire map to display semiconductor maps. But in order to do so, you open up the map, you turn off geocoding seven places, you take out aggregation in nine places, and eventually you get to what you're looking for. So it's quite important to be able to have an infrastructure that can configure specific settings within a visualization. So that way, if somebody who's in drilling wants to visualize the time series in a certain way, but somebody who's in production wants to visualize it in a different way, you can use the same chart and configure it differently to support different use cases. In ActionModes, that would be, I think, one of the most common uses for an ActionModes. But it also can automate, for example, and now we're getting into what the bullets say here, you can launch data functions from ActionModes, and the action mods can configure visualizations. So maybe you start to see how the pieces fit together. Right? A data function can calculate inputs calculate outputs from inputs. A visualization can show you those results in an intuitive way, and an action mod can orchestrate all of that behavior so so that you can build applications that are suited for a particular business case using all of the same building blocks. So it might take a couple of extra steps to put those pieces together, but it gives you a dramatically more, wide palette for painting applications that your end users might might wanna take advantage of. Okay. So ActionModes is a JavaScript based configuration, so that uses directly the Spotfire API. Some of you might use the s the deep SDKs for doing c plus plus extensions in Spotfire. The ActionModes has access to most of those same APIs, just limiting a few for for for safety considerations. So action mods is amazing, and we'll show you a couple of examples of action mods. But next year, I wanna see the action mods that you all built and bring back to show us what you did. Oh, run data functions from action mods. I think I just said this on the earlier slide. This is a key capability. Oh, and also more flexible input and controls for action mods. So this is primarily a tool for automation that allows the end user to set configurations that they want and occasionally to avoid setting configurations that they just always need. Right? So you can just simplify the user interface. The end user picks what they want, and you just directly do that that action. So in in doing so, we need to make it easier and easier for the end user to select multiple columns, for example, to select a data table, to select an output variable. So we've added a whole series of new UIs to the action mod, framework so that when you build your action mod, you get you get a lot more flexibility as to how the end user can interact with it. You can configure visualization mods from action mods, as I said earlier. So it's not just visualization mods, but visual the native visualizations in Spotfire and also the add on visualizations that come with Spotfire data science in this and today, we'll be talking about the energy specific ones. Okay. Also improved visibility for individual actions. So an an action mod is really a collection of actions that pertain to a particular task area. So, in this I can actually I should look down here because I could maybe read it a little better. Well, I'll show you in my example in the demonstration, but you have a high level action, and then within that you have perhaps multiple steps that the end user can take, either one or all of them, to kind of have a little bit of a lightweight workflow, for configuring the application in the way that they want. So we now make it possible to show that nesting in a hierarchical way and give an individual name and an individual icon to all of the subset actions inside of a group of actions in an action model. And finally, I think if you all have been using the mods, you will be thankful for the undo button. If you make a change for a configuration for our plugin visualizations, it's now possible to undo that that behavior, which was not possible before. And actually, there are many, many other features here that I'm not gonna talk about with respect to the plugin visualization framework because as the Spotfire infrastructure itself advances, we want these plugin visualizations to be able to take advantage of all of the inherent capabilities. For example, the properties panel. That's another one that you can configure the plugin visualizations using the new properties panel. So a lot of work went into what I'm going to talk about immediately after this slide. So the add ons browser here is the last slide for the regular Spotfire capabilities. And this now is, it may seem small, but actually this is a window on the world for energy and oil and gas specific functionality. You'll see this little add ons button down there on on the in the middle of that panel. And when you click on the add ons button, you see all of the various capabilities that are available to you of two different types. Actually, multiple different types, but two different categories. One is the specific energy functionality that's available with the new data science SKU, and those are marked with a colorful data science banner as you can see on each of those, but also access to the community content. So I think Michael talked about this. We have this kind of arc and evolution. We work with our customers to understand which new functions you might be interested in. We might put an example or a prototype on the community. Others can download it, give us more feedback, and then we might harden that, increase the security, increase the performance, and then bring it into the Spotfire, application directly. That life cycle is now kind of explicit, and you can get access to the, community content directly from inside of Spotfire. And this is also the mechanism by which you will go and pick and choose the advanced visualizations, that you want to include in your particular application. Okay. So Spotfire data science. I'm actually gonna start moving a little faster because I wanna make sure we get our demos all the way in. And besides that, Michael gave you quite a nice rundown of some of these capabilities. So first of all, there's at least these four new plugin visualizations which are now officially part of Spotfire. They've been hardened, the the security has been increased, they're using more capabilities of the platform, they have higher performance, but the same kind of functionality there, that you might have seen before, but in addition to that, more features and functions that we'll probably go into on an as needed basis with you on individual conversations. So a whole series of different, new visualizations, a set of data functions that Michael also kind of alluded to, and as well just a few action mods that we're starting to kind of start the trickle of those coming out, and then future releases will probably accelerate the number of those that come out. Alright. Data functions and actions. I think Michael already ran through, the list here again. This is a somewhat of a small list with this first release of production data functions and action mods. But with subsequent releases, we've put a lot of effort into that platform to make it easier for us to deliver new functionality to you off cycle. So what does that mean? If you if you're sticking with the LTS release, you might get a new version every year, every year and a half, even sometimes out to two years, we've we've done in the past occasionally. And what this will allow you to do is to get new functionality without an upgrade of your Spotfire system. So all of these are highly secured, embedded, and are available directly from inside the application. So as new things come out, you can just go and start using them. So this is a fantastic new possibility for us to bring new functionality to you whenever you decide that you wanna take advantage of that. Okay. The well bore diagram, the three d surface and line chart, the well spacing diagram, and the well log chart. So those are the four, key visualization mods, and now we're gonna get into the demo section where we'll show off some of that stuff for you. So I'm gonna give you a little demonstration here, if we can get the video queued up, for the Williston Basin. And I'd like to first give out a shout out to, Gunther Harms, who's a petroleum engineer who works at the North Dakota Mineral Bureau, who helped me gain access to, you won't believe this, 20,000 wells and all of their well logs and all of their, survey information. Now I know what a day in the life at your organization might feel like, and just a massive amount of information to put together this little video here. There we go. Alright. So, this this dataset here is, production data, and we'll I'll talk about that as we go. So I've got fairly significant dataset here with a lot of different information in it. In the upper left hand corner, I have total production in the Williston Basin by operator. In the bottom right here, I have a simple map listing out each well color coded by, the county in which that well is located. Alright. Here we go. So we're gonna mark the top 10 producers in the Williston Basin, and we can see a kind of a boring chart, but an incredible chart. 600,000,000 barrels of oil since the early nineteen nineties with Continental again up at the top. But I wanted to take a look at maybe a little bit of a more interesting chart. So this is a metric that I just kinda put together here, which is the total number of barrels of oil divided by the unique well identifier. So this is essentially a well productivity measure. And, of course, as you get more wells, it gets harder and harder to move this metric around. But when you're first starting out, you can see WPX out here in the early nineteen nineties drilling a couple of exploration wells out there almost by themselves, and you can see this characteristic really nice high initial production, but pretty steep decline. That I think was probably the reason why it was another fifteen years before you start to see more activity out in the space. And who can explain, what was going on right in the 2004 time frame when we started to get an uptick there in the Williston Basin? Horizontal drilling became a thing, which was a way to take advantage of that of of those reservoirs, and not experience those fast decline curves. So we have here Continental, we have Marathon, we have Hess, all early innovators in that space. And then, our buddies at EOG Resources discovered the partial field and really kind of the bomb went off over here. So now you can see an incredible amount of activity, that's out on the slope there, an incredible amount of activity here in the mid two thousands to the late two thousands. And what's interesting about this is not only do you see, a ton of activity there, and as I said, as the more wells come into place, it gets even harder to kind of bump above that average threshold. But notice the low threshold is actually continuously improving as well. So the average production per well is going up significantly from all of this new technology. I don't think it's a coincidence that Spotfire Energy Forum also started focusing on the oil and gas business right around 02/2004. Coincidence, I'm not sure. And then in 02/2017, the oil prices were just starting to come back up again, and we had a new pipeline in North Dakota making it even more economic to produce oil from there. And so that brings us to the current day. Now if you are a new operator or maybe you are considering your an investment company and you're considering investing in someone's development program, things are getting a little bit crowded out there now. And so it might be a good idea for you to understand, to ask and answer a few different questions. Which formations are kind of overproduced now? Which formations have additional resources to to exploit? If I wanna pursue a particular formation, where in the field do I need to go to access that easily or how deeply do I need to drill to gain access to that? What are my peers doing? What are my neighbors doing in terms of lateral lengths, in terms of perforation intervals? Maybe even drill spacing, well spacing. I wanna answer some of those questions. So if you were here last year, you might have seen Manny do a very similar demonstration here with a couple of caveats that are different that I'll that I'll talk about as we go. So let's just go pick a couple of 100 square miles here, and we'll drill down into two different visualizations. Alright? The first visualization is a simple, drill down map, and I've layered on top of that shape files for the horizontals for all of the wells that are in this Right? So for drill down from here to here. And then over on the right, you could see this three-dimensional subsurface and line chart. And what's amazing about this is that I think when Manny gave his presentation, he was visualizing an export. I'm not sure, maybe Hector, you know if it was from Petrel or from Kingdome, but one of these advanced, petrophysics systems. You have to create and export a gridded infrastructure that you can then visualize in Spotfire. The problem is if you want to change the resolution of that, you need to export another one. And if you need to change the area in which you want to visualize that data, you need to export another one. It's not really possible to export one massive file of all different resolutions and just sort of navigate that. So what we've done here, and I I tell you I was absolutely amazed by this myself, I went into Spotfire Copilot, and I said I would like you to make a data function for me that can take the top information, can project it to a linear, to feet, basically, from lat latitude and longitude. Then I want you to create a grid, and then I want you to interpolate using creeping, and then I want you to put that data back into Spotfire Energy Forum. And I kid you not, it was a one shot operation to build this data function. So now, dynamically, anytime you wanna mark some wells, it will automatically create the gridded formation information and populate the visual so that you can go and explore that. Now obviously, this is not gonna be as accurate as Petrel, but oftentimes, it's just a quick look that you're looking for. So this makes it super easy to go and get access to this data pretty much whenever you want, even if you're not the kind of person who has easy access to those petrophysics tools. So let me continue on here. So we can, of course, spin around this analysis. We can take a look from different perspectives. We can turn on and off. So if you notice up here, I have a set of filters. So I can turn on a particular top and dynamically, on the fly, calculate and then render that, and then I can actually turn it off just as quickly because we use a kind of caching based structure here. So it's easy to turn things on and off rapidly and interact with this three d subsurface. Now the second part of the equation here is the well sticks. So I'm zooming in, I'm selecting a couple of, parallel wells, and let me just pause it right there. So I'm selecting a couple of different wells here, and after I've done so, a second data function will find the common normal to those and create a well known binary layer that then gets automatically added to the map. That's the light blue color. So we're effectively establishing number of wells, a shared cross section. And then it also places that cross section, the the three d version of it or two d version of it, into the three d subsurface. And maybe one more thing happens at the same time, and that is that we query the survey data and take just the laterals and put them directly inside the, the three d visual. Now the visual itself is Spotfire, so we can slice and dice and maybe filter down some of the y coordinate, turn it around and take a glance at this and say, I think probably these wells are penetrating the 3 Vorx Reservoir. But maybe to get a more fine grained view of that, we'll use a third data function, which will calculate the cross section between that, line that was designated down in the lower left hand corner and all of the formations so that we get horizon lines down below, and we also get the individual well spacing points and calculate the nearest neighbor distances of those well spacings. So here we have indeed the 3 Forks, horizon line, all of these formations down here, all of these wells down here and their and their various spacings. And I just like to say that the first time I got this working, I had to sit back and be in awe of people in this room who are able to somehow drill down two miles into the earth, make a left turn, and then somehow, you know, stay within a thousand feet of one another and and fully exploit these reservoirs. It's amazing. We're so honored to be able to provide tools that might help you, do that even faster. Okay. So now, getting towards the end of the presentation here and getting ready to call up here, but I want to is it playing or not playing? There we go. Okay. So you might be wondering, well, this looks a little bit complicated. How would you set something like this up? So I'm just gonna show you the underside, the canvas a little bit. There's the tops, the wells, and the well stick information. That's the primary inputs for this analysis. Here's that relationships page, where you can see that we were able to do all the various drill downs because there's a relationship between production, the wells, the tops, and the well sticks. But then we have all of these other five calculated data tables down below that are used by the visualizations that are not directly related to the underlying, input tables. So now, if we look at where all of the action is here, it's in the grid information. So we talked about that interpolation function that provides the basic, gridding infrastructure. We added rows to that from the slice plane, and then finally we added rows from an on demand query of the subsurface. And so with that, I think I'll probably, end my portion of the demonstration here, and I'll ask my colleague and friend of the year to come up and do his. Hello, everyone. My name is Adir Alta. I'm a data scientist and a petroleum engineer. You've probably seen my face in more of Doctor Spotfire episodes or one of the YouTube videos. So, Michael and Brad talked about the new features about in, fourteen point five. I'm gonna go into details, in some of these, new features. And then let's start with the, with the well lock mod that, Michael was showing this this morning. And then I will go through the, the configuration and the features of this all new, visualization. So to start with to get the, to get this new, add ons, yeah, we can see that we have this add on item now, and, you can see the, the world log model, like, the visualization mods, and the the action mods and then the demos. And in order to get any of these items, you just need to sign into the community to download any of them and you can add them to your library or to your visualization. In order to use them or like into any of the team members to, to use them. And so you can see that you need to sign in to the community, in order to be able to, download any of them. Now looking at the, well log mod, we have two types of configuration. We have, let's say, curve level configuration, and then we have also visual visualization level configuration. In this new version, you can interactively, let's say, swap the curves between the, the tracks. You can, do a lot of configuration on the curve level. You can see here we're swapping the, the spy key from, track to track. There is a couple of, let's say, rules on how to fill in the the curve. If you wanna fill, let's say, say, the curves, between the curve and the track or, like, the curve and another curve, you can configure that on the curve level. And then you can also, control how the curve would look like. So for example, if you have, pressure points, you can, represent them as points or you can, let's say, keep the default as, as line. With the with this new, visualization mode, you can, also, yeah. This is like the the general, or like the overall appearance. So you can set all your logs or all your curves to be, markers or lines or lines and markers. The background of the track can also be configured individually. And, what is nice about this is it can be also, parameterized to, like, an existing, barrier. So So for example, if you have, I mean we will see in the dynamic and warping example that, the the the similar wells are highlighted separately. Okay, the new visualization properties made it very easy to quickly configure parameters or features of the world log mark. You can see here that we're configuring the background of all the tracks or, from the, from this from this panel. Yeah. And then, selecting a specific interval. So in here, we can, simply select specific interval, and then we can save that to a new tag, the marking to a new tag, or let's say, any other team member can use that, tag and then bring that selection, back if they wanna, work on it. So here we are. Yeah. Selected and terrible with the high resistivity and then save it. And then there we can just bring that selection back, if we want it. And then in terms of, in terms of performance, so the new log mode is is is really fast. So, in here, we're, we're bringing 70 ks rows per per well, and we can see that we can interactively add, multiple tracks for the, I think, yeah, that's a guy here. So we can add multiple tracks as we, as we select select them from the, the tree map, visualization. And it's all connected. And then with with the with the with the new log mod, you you won't be losing any of the, let's say, default Spotfire visualization features. So everything is is there in addition to the, to the new configuration, features that you can, select from here. Okay. So this is the world of mod. The next demo is, on the new, analytics data functions that we've added, to 14.5. So to start, these these newly added functions, they can be accessed here. I will demo the dynamic, time warping, and also the geographical, the geographical distance matrix. So now the dynamic time warping, if you're familiar with the function before, you need to, like, write a data function in Python, but now it's, kind of, like, ready to consume in the Spotfire. You just need to, configure your sequence data, your sequence ID, your let's say, the the reference that you wanna compare with. And then it also comes with couple of, nice optional features. So you can, fill in your missing data. You can do any smoothing before you, like, calculate the dynamic time warping. And then just to summarize, dynamic time warping is, a way to calculate the similarity between two two sequences. These these two sequences, they can be depth different sequences. They can be, time based sequences. And then, this is also the geographical, distance matrix. So you have, let's say, two sets of points, and then you wanna calculate, the distance between them in a form of a of a matrix or in the form of, let's say, nearest neighbors. So you identify, the number of neighbors and then, you can calculate the distance between, let's say, a source point and the nearby neighbors. So putting all of this together, what we are doing here, we're, once we select any of the wells, on the, on the map chart, a couple of couple of things will happen. So first, we can, first, we set the number of neighbors. And And so once we select one of the wells, a couple of things happen. The geographical nearest neighbor data function will, will calculate and then identify or highlight the nearby neighbors according to how many neighbors that we, let's say we set in our data function. And then interactively, the dynamic time warping function will be triggered, and then we'll calculate the similarity between all of these wells that we selected. And also there's another data function that will, highlight, this is like the screen scoop right here. But basically, we have these two, tracks that are highlighted. The green one is the, the source well that we selected, and then the, the red one is basically the, let's say the most similar well to this well that we are interested in. And you can you can see that once you scroll through, let's say, through the the these two wells, you can you can see the the signature of the gamma ray is similar, although that you have kind of at some places, it kind of, like, compresses or, stretches. And that's what the dynamic warp that time warping is doing. It basically helps you to find the similarity between two sequences, although they're, like, not not in the same, length or like the same signature. You can interactively add or, like, update your neighbors. So you can see that here where, we updated the the neighbors to four, and then we have, like, four twelve highlighted, and then they everything will be recalculated again. And then to give you an idea about the, let's say, the size of the data, so each one of these wells is, basically $1,717,000 gross. So the dental camorbing basically is calculating the inclusion distance between each of these, these pairs. So and this is all, real time. So you can have an idea about the, let's say how fast is the function of how fast is the execution. And then, yeah, again, we we use the, we use the the background, configuration of the well log to identify or like to, have the function identify these two similar wells. Now the going to the data, let's say the data canvas. Once you, once you insert that function, data canvas will be automatically created and then you can also access the function from here. To reconfigure it. You have a lot of options to, expose or like to go to to reconfigure the function inputs. You can do it like the back end property value custom suppression. And then that's the same for the, the same for the geographical nearest neighbors. You can expose any any of the parameters that you need just like we did with the neighbors, so you can expose any of the parameters, so the user can, let's say, configure these, interactively. Okay. And then the last demo is the, another data function. And also, I'm, gonna touch on the action ones. So, I'm gonna talk about the, the smoothing data function that we have, here, which can be also accessed from, the new data functions, that we have added. It's the the the computation of the of the function is is fairly, simple. I mean, you can also, check-in to show only the required, columns. And then so these are all optional. You can configure them. You can read them. After you configure that, you can, run the, the function or you can expose the function parameters, to configure it on, let's say, interactively or, like, on the fly. Now the the action mods here, we have couple of, action mods. And then, just like Michael mentioned, this had a series of tasks or, like, steps, using the, the JavaScript, API that you can sum them up sum them up all in, let's say, one action. So what we used here, we used two action mods. We used, visualizing the missing data. We're using a data, production data here that has, some missing data in it. And then we also use filling, missing, filling the missing data with, let's say, the nearby, good values, like, the nearby averages, four or five values. So you need to first sign in to the community in order to be able to use the, the action mod, or to download it. And then once you sign in, you go ahead and then just configure the, the action mod. So in here, we're visualizing the missing data for the production data that we're dealing with. You just need to identify your your table and, the the column that you are interested in. And then we're also configuring handling the missing data. How do you wanna fill in the missing data? So we I mean, our example, we choose we wanna fill it with the, average of the nearby five five points. And you can also, we have selected table, select the column. And all of these selections and parameters, they all can be parametrized. So these are all can be, let's say, a user input or that can be, like, a definite property as you will. You'll see. So here we we chose the average nearby five points. And then now we configured the action mods. How do we use them? So there are a couple of ways you can bring the action mods to your visualization. You can have them as, let's say, floating points here. And then, by the way, all of this can be configured with the newly, added visualization properties panel. So you can have them as, let's say, floating buttons just like this. You can have them as, let's say, right menu click, or you can have them as, an icon added to the, the visualization tag. So you can you can see that here. And to, to run the action model, you can simply just click the action model. So we will see in this example that, we're gonna summarize the missing data for some of the visualization some of the production data. So we choose the product. We're looking at the water production for one of the selected wells here, and we wanna see, whether or not this, this well has missing data. So you can simply just click on your missing data summary action mod, and then that will run a couple of, let's say, steps, and it will generate a new tab that has, a couple of visuals and then, some KPI charts that shows that you have 10% missing data in this variable. Now we want to fill this with the nearby averages, the nearby, let's say, five averages, in order to get rid of the missing data before we smooth that. So you can simply just click your, missing data, action mark, and then that will perform all the, let's say, the calculation and then filling out the missing data. And then to confirm that you don't have any missing data, you can run the the, the, missing data summary again, and you can see that now we have, zero missing, missing data. So this is an example of the action mods within the visualization. And then this is, how we use the, this smoothing, data function. So we expose the, we expose the, let's say, the smoothing method and then the smoothing parameter, the function here. And then we can interactively, let's say, change the product. For example, if we're looking at the oil, we're looking at the, the water. And we can change also the smoothing method, and we can also change the smoothing parameters, parameter here. And you can see interactively that the the smooth curve is that the pink one is recalculated, as we change. So these are some of the, some of the newly added features and functions to, the, Spotfire 14.5.