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0:10 building a thunder lizard starts here learn more at energy Tech Nexus Dot com welcome back to the show we're here today with Ian Uriarte the CEO and founder of Spindle top AI also runs a business

0:24 called Timber Timber grow for growth and and if you're here in Houston you know why that's named but we'll get into that in a little bit but no glad to have you on the show your I know you're a recent

0:35 member of the energy techniques as you're participating in our liftoff program excited to learn more about what you're working on and ensure that with the the audience here and and I want to start

0:46 with how you name your businesses cause until top is a very name to tell Us about this kind of theme you have that will get into what you actually do Yeah absolutely thank you thank you for having me

0:55 here Jason I'm excited to be here i am happy to be part of the energy that Texas Technics is I'm really excited to be part of it I I get so much value out of them membership in the the community that

1:10 you guys have form in there so for thank you for starting that I'm quite honest so do I Yeah naming so the first name was honestly a bit of being Lacey me showing up at the Harris County office to do

1:25 a debate in two thousand and three and realizing that haven't taught by the name of a company and I lived a timber Grove Manor which is a neighborhood houston but in your ASs as I thought through it

1:37 you heard of a cypress semiconductors in on different you know companies like that I thought you know why not name it you know it's a pretty name and and I gave you some meaning afterwards I realized

1:46 that you know a a wood timber a grove of timbers basically you know something that you have a you could have it with a bamboo ambush really strong I thought bump was flexible it's on built together is

2:00 very strong so I said you know we're flexible there were also strong US enterprise -grade because we were doing software initially so that's why sometimes the branch flows out of the name we got to

2:09 constrain yourself right Yeah and spindle TOPS really loaded as a name swap that one we put a little thought well you know everybody in oil and gas years that name and knows exactly what it is that

2:19 was that was the reason to do it right you know his pillow top to create it said that location you know near Beaumont where a succulent boma where the first gushers to start coming in Texas five and

2:33 nineteen a while on January twenty something like twenty eight I believe as an electing a one is when the new era of basically dreaming begins you know because of that drillbit there was using that

2:43 well and and everybody knows that those are those are the Gaucher site as the beginning of high production in Texas and put Texas in the map so we think that machine learning and AI Edge Computing

2:57 will do the same for oil and gas again I mean it has already right away but we're trying to go after a particular market within the oil and gas industry which is mid mid level producer in many ways

3:09 like the the energy and oil industry has used AI for a long time I was looking at like who is that when they do that the imaging of like downhole all that is a I post -process area right in and I was

3:21 listening to a history like Texas instruments write such a huge business one of those chips were for early AI systems Yeah right Yeah and you know when you think about lead neural networks you know

3:31 back in the nineties it all that was used in multiple things in geology as well you know a lot of a lot of computational you know high high speed computation systems and so oil and gas is not new to

3:45 technology I think for for for us when we started spindle to AI the reason why we thought that AI in in Machine learning and particularly its edge computing was relevant is because you know the majors

4:00 have solve a lot of the problems right and made solve it by putting you know manpower and money into right and thus how they solve although this province you know you have enough money and of people

4:11 you can do it enough talent but that usually doesn't become a product that can go to the mid size or the smaller producers right I mean when the assets are are pass you know from you know the measures

4:24 to them midsize producers because they're producing less red as that happens and he goes into the you know individual producers and dependent producers that his technology is not coming with it I saw

4:35 you don't have a skater system in those Wells J ripped the skate out or I guess it's proprietary rights or they don't want to give it away yeah so that some of the skaters are expensive right in it's

4:44 not just the hardware it is the the ability to manage him in and utilize it in in gas for example gas wells is more common that it stays with it because they're smaller they're more Aspirations are

4:57 less

4:59 troublesome you know there's less to do you know with gas but when you have oil production you have so many things that can go wrong with a well either you need daily interfaces me with gas you can

5:10 monitor remotely and make changes to the controller Napoleon but not with oil in skillet oil you're producing oil water and gas and gas and and pair of fins and sands and solid and suddenly you have

5:24 you know sour gas and press in as well and becomes a hazardous environment for people as well so there's so much happening Russia you have to inject chemicals or water gases well sometimes and so is

5:37 not something that you can leave alone for very long time periods of time to tell us a little bit about the life cycle of a well actually and not from like a drilling and production but this is

5:45 interesting as I was talking to someone and and they're asking me about like OK if the price of oil is depressed and like who's that going to affect and I'm like I really the oil majors it's really

5:56 the guys running these younger well older wells because the oil majors don't hold onto oil assets just one certain you know once they're no longer like a mentor like to tell US like so the E M P they

6:07 do the drilling and that is like day one but kind of what happens to the well before it's retired Yeah so you know once once you the real the initial well writing is completed you know you have the

6:18 first recovery that's called by their first record as the first one or two years that is basically just the formation pushing the oil out by the way you thrill the whale ride you go on top a specific

6:30 type of formation so that naturally that will will flow right so that's how it's done right so is is a lot of studies on the on the on the terrain you know the all the geophysics is looking at these

6:42 you know data and analyzing and and then interpreting where's the best place so that this is going to flow and and that'll pay back in like what nine months fifteen months he pays very quick very

6:52 cause we were talking about are five thousand you know Barrels of oil per day I mean just as a lot right so the initial investment gets paid and the next and I would think in the first year for sure

7:03 you'll get that investment payoh but then you have secondary recovery right that's sick on the records when you come and say okay is flowing but it's a slowed down right is no longer give me the three

7:13 thousand barrels of oil per day let's listen to some intervention so you either you know inject water right or inject gas right because oil will be lighter on it is start start pumping into it and

7:27 just gets out and so that's your second our recovery once the secondary recovery ends probably another couple of years now you got up there cherie currie ride that's actually when you do you put a

7:40 some sort of artificial lift system those artificially systems were talking about you know rod pumps you see those in the Permian all the time you know the little you know Donkey heads moving up and

7:49 down you may have a live one years you know you may have E s pieces or a steel for steel you're producing in the thousands or or the upper range of the hundreds of barrels per day ride these bees are

8:02 more more for high producing wells you know but can you talk to US about how that works cause I mean i understand when you put in gas or liquid and it pushes the oil gas out but the artificial lift

8:14 what are they actually doing to get that oil that's like a pump right I got my favorite analogy Yeah sure so you know in reality this so you have the oil in the well right so that the wellborn is

8:26 basically a tapping into a posse the oil or gas right or you know it's actually all oil gas and water I in and so that you know that the marching a pipe or like a straw right and he goes all the way

8:41 to the top of this destroy is that the surface right on on the ground and the bottom of the straw it's in you know and the formation and so let's say the permission is this cup of coffee and I you

8:52 know that I'm on top of you know I'm here so what is doing that the the physics of of the formation is pushing the oil out right now if you inject water right yeah he pushed as pressure pressure I

9:06 when you have a artificially system is you drop into what is called a a a pump suction like a syringe syringe the same mechanism right so like pulling it out like a section correct that you're doing

9:20 that and so it has a couple of openings that allow so when he pushes up you know some oil comes up and when he pushes down that oil that you you know that length of all gas goes up and gets the

9:31 artificial part of the last here's my Terrible analogy I Dunno if You'll get this but when you were in elementary school she has like little milk bags that you get with your lunch food a little one

9:41 day the the pouches the US Yeah so like for me are like it's like okay when you first get it like You put Your Sucker and Yes and and

9:51 exactly right and then eventually like you're You're producing and and You've Gotta Gotta suck on the milk bag when the bag goes and you can't get any more milk out and that's that's the tertiary

10:01 recovery right there you Gotta suck really hard to get that little bit and and it's it's low production set different screen three thousand a day vs I'm going to steal about an hour I this suction

10:12 portion is that efficient Yeah Yeah Yeah and so in in a rock pump the rod itself is going down you know several like to several hundred sometimes meters and he goes down and you pull it in so when

10:26 you're pulling that out you're you're creating that vacuum right and it's extracting the oil and when you push down there are holes on the side thus where it comes you know that and so is pushing out

10:37 and so the there's a ball usually at the bottom that it gets up to open you know the the basically the mall that allows the oil to flow and then when you push that you know once you finish pulling

10:50 that drop but it basically clogs you know the evolve and then you can extract that one thing that I think is like the craziest thing that I learned about this industry is like you know you're drilling

11:01 whatever it is thirteen thousand feet down and some larger wealth is literally two and a half miles right if you think about five thousand feet and so a the rod miles and then you think about like

11:11 duck tile metals they might stretch like whatever it is a quarter percent though Raj stretches like feet oh yeah literally between the top and the bottom and so there's a whole science around like how

11:21 you read the stress strain of like what we see at the top of the top moving even before the bottom has move tracks it's literally stretching up and down it's it's crazy it is amazing what what people

11:31 know about how that work early in my career I spend time as an MW the engineer would baker use and so I wasn't the field so spending time offshore mostly drilling rigs in and in offshore you're

11:41 talking thirty thousand feet of drilling none third As

11:46 and you're usually because you're usually ten thousand or that is water I cause you're floating on a semi -submersible and you're gone you know directional drilling rights which means you're turning

11:56 and twisting the pipe right and you've seen the the the the pipes are there are huge and to think that those things will stretch the way they do to be able to do you know angles some sort of angles A

12:07 and M for that amount of time so this is wife is something happens on the well and that completely comes on Donna's imagined the energy that house right so it completely destroys you know that area

12:19 you know so we've established the lifecycles very complicated so let's

12:25 talk about it cause you mental mentioned timber grove and you mentioned spindle top like what are the two come different companies what other products that you guys are offering Yeah so timber growers

12:33 as a studio arises as an engineering studio that the software and hardware solutions for multiple industries we work in the oil and gas space for a very long time my background is oil and gas as well

12:45 so that's kind of why we went after that market as well but in reality a timber was the creator of some of the technologies that we're utilizing for companies like spindle upright and so on but in the

12:59 end we partner we brought one of my co -founders have done a thesis on on improving operational you know efficiency you know and more and getting more of oil basically with less effort you know ah

13:12 using machine learning and so we started applying the hardware the machine learning all the data pipeline you know the infrastructure of those required to do this you know and so you know that the

13:25 difference between the two as Timber grove as as a studio write custom software solutions custom hardware solutions and spindle tub as a solution specifically for a large problem of oil and gas right

13:37 and so do we what we're trying to do with spindle tub is focused basically on meat level Raiders and it's not just operator sick any operator that has meat yield production well so we're talking about

13:50 fifty to two hundred barrels of oil then is that instill in the tertiary recovery phase or sherry coker Yeah doesn't that still does fairy I mean and then you have you know you know you have more if

14:03 he goes down right to like fifteen barrels if that's what what's called marginal wells try to over the years I mean if you think about the life of a wealth seventy eighty year sometimes right and so

14:12 you know you and you recovering maybe thirty forty percent of that either eventually it gets very difficult to get that out of the well because all the metals are becoming more expensive than actually

14:23 what you're getting out of the ground rise so when you're getting just fifteen barrels of oil timber some some whales are doing five barrels of oil a day or quill and you know and so and so we thought

14:32 looking at the market we you know there's over a million active wilson the United States right for and gas a million out of those about forty percent of those are weather cold Marginal or you know or

14:44 a stripper wells or wells that are producing fifteen barrels of oil or less those operators are usually single owner operators for either very small companies there are large companies that have that

14:55 right we met with a company in a conference zed there in Canada and have like forty thousand wells of that type so the problem is that the economics is not there yet to apply any technology if you

15:07 think about an average stupor wells you know owners can spend about two thousand dollars a year in technology and so it makes it very you will have to have a dozen her well desperate sorry PR Well

15:19 Yeah and so so but then you have the measures right there producing thousands of barrels of oil a day and they have you know realms of data scientists and a ten percent improvement there is actually

15:30 produces more improvement at this production while those I mean that is what seventy C and twenty nineteen with seventy seven percent of the production came from those big wheels right I think it's

15:40 gone down a little bit because In general things are producing more but but you have do you know about fifty sixty percent that has been produced by a third maybe of the of the wells which are the

15:53 height producing wells so you have a market of twenty to thirty percent wells that produce and that produce about twenty to thirty percent of the oil in the United States so we can incur increase

16:05 productivity for those for those operators tried meaning manage the resources more effectively belt be less reactive to things that happen on the well run if we are all to predict when these are going

16:19 to happen not just for not just for reliability and maintenance but also for production right I mean when when I'm an operator I I care about those two things but the production manager cares about I

16:29 need to produce added to get producing I need for this more run and have a very limited amount of people to do it and also limit to them on skills I mean these guys are you know are Masters of You

16:40 know very very few things very well right but but if you start throwing technology on top of that writes software you know you know skater systems that are complex and appeals assistant having to do

16:51 what should that you need some background that a lot of these guys you know at the pumpers ride on don't have right and so and is becoming increasingly harder to get these people as well as you

17:01 realize why people don't want to go and though this is a hard job you know her job been in the field and you know driving the strokes around high temperatures you know there's danger you have a they

17:12 have wells that are you know have a sour gas so a stewart and unison so you're going to be able to in a tube ever be able to to survive those areas and in overcome what comes with the job and so we're

17:24 trying to figure a figure out with the technology that we're developing how do we enable these operators to do more with less you know basically

17:33 Yeah sorry so when when you think about us tell Us about what you're building as I know you you work on hardware on the timber grove side by assume you're bringing the hardware over to spindle top and

17:43 and have a product do you have like an iota II module that you're deploying or what are the pieces that your your create opponents so Yeah so we we've figured out that one of the biggest problems with

17:54 existent technology was associated with well two pieces right one is the resolution of the data that you want to pass and also how far the data has to go so one of the premises that we have would

18:10 spend a lot of is that wells are autonomous entities and he should be making decisions on it's own how does he do I mean there's so much data at the happens at the Wellhead right when you're producing

18:22 there's data from the well right temperature pressures you know on the rod Palm you will see strength you know

18:32 on the rod itself fry you you need to have some visual inspection of the the stuffing box which is the little you know box that has all these agrees you know that allows the rod pump to keep moving or

18:43 you have a you know currents of the models that are moving the rod pump ride you can also have noises right I mean yeah a lot of a lot of today predictive maintenance is done by hearing the how the

18:55 machinery's working in in in he didn't define changes on the pit on the Friday yeah the rotating equipment so Yeah especially for rotating equipment so there's so much they'd on the that is not being

19:05 captured as either analogue right you have pressure gauges that are there you know showing the little gauges or Ah if they're digital they're stand right now when you have different themes coming in

19:17 for example you have an oil testing team right they come with a well testing equipment they're going to figure out what's going on with a well how much producing per day Ah they have all this you know

19:29 sensors that are doing this measurement they just print a and give you You know a you know a snapshot of what happened on the last twenty four hours and they you know they'll probably take this and

19:39 said this is my this is my daily production going forward

19:44 but what we discover is that if we put sensors that are you know cost effective right in the Wellhead we couldn't measure temperatures pressures all the things that I'm referring to in a in a way that

19:60 estates with a well we put an edge device computing device on the well in each well can interact with each other the problem that we you find is you know it's it's it's fine and fun when you do these

20:12 you know on an officer you know and the city but when you don't have connectivity wireless connectivity is very difficult and increases the cost by adding connectivity you know if you add a SIM card

20:24 to each device imagine if you have to have thirty devices you know and and in each of the locations that you're working it becomes and so each location might need thirty sims and then if you're

20:34 running whatever one hundred wells and suddenly you have imagined data as you have two are a lot of devices you have to manage right Yeah and so we thought how do we do this a scaled in in a way that

20:44 is cost effective but also that it uses very low power consumption because you can have each of these devices consuming power right Ah and so what we decided this we decided to create a network of

20:58 three data resolution and rings we call them right so the first one is for you know high speed high resolution data that could be wifi most of the time or could be BLe right Ah but think about the the

21:15 the the constraints of that WIFI cannot go more than you know a few hundred meters right and so you have a problem with that and so what happens if I need to send large amounts of data you know or

21:30 order this as you can So you have to forget our ways to that the other part is and you know you want to send data a very long distance whether a short amount of data you could use something like Laura

21:41 which is Lorawan long range low power ah that could work with battery may be have a solar panel for that as well ah but for example a seller you know it's really bad with batteries it eats seller eats

21:54 the battery very quickly so we have to make some decisions and we decided why don't we create this node and that node in that network that allows us to make decisions when data needs to be sent

22:05 through through the mesh in ble when he needs to be sent via Wifi or when it needs to be sent to Laura right another thing that we did is we realized we want images by some of the prayers when images

22:16 so they can see remotely what's going on there but sometimes you have the gay way you know over a mile away and you know Wifi won't be able to send you that right saw and you want to put in every

22:28 single camera seemed that becomes expensive so we actually figured out how to do send images via Laura which is something that not a lot of people are doing and we even file a patent for that is this

22:40 like a peer to peer network AH it it is it could be it could be peer to peer or it could be autonomous yet they can look at and I guess I don't know the difference i'm I'm literally thinking of old

22:50 school lime wire of like how do I get images or music from like pointed up Yeah Yeah like how do you jump across the node not using a server right yeah it's thinking like I do I'm trying to fit it

23:05 correctly Yeah I remember but with bit torrent you're sent this you know that you have Wifi or I or you have Ethernet which means you can put you know you know I in those days you know one hundred

23:17 megabits per second right dude I had a floppy two point five not a lot of data remember that Yeah Uh well I'm I'm so old that my first University program was written In and punch cards no man Yeah

23:36 anyway so but you know so with Laura you have twenty bits that's all you can send on a message oh wow so how do you send an image that you know and so we ended up having to write a pattern about that

23:47 when we've figured out how to make it happen and wrote the pattern you know and so that's the type of problems you find in the field right in that you know big companies are solid slumber just of the

23:56 world you know the you know Halliburton or solving that but there's something that for the high paying clients who can afford the power and you could put in the big system and so you're a lot of the

24:07 IP is how do we be limit only piece together how do we control stuff that we need to control but then not send everything and then we have a a system that says here's the high -grade stuff that we do

24:18 need to send back so that we can spend the expensive energy and data resource for those things that are essential but let's filter out ninety nine percent of things that are not mission or not are

24:29 urgent today thus right then you do the processing like dusty edge computing part right like you do a right to know what to call for help but otherwise it tries to make all the decisions itself we

24:40 were talking about autonomy of decision right so not autonomy in the sense that that is the well as a robert writing those on it but it's autonomy an increase in making others fishing and providing

24:53 that to the operator operator it'll still have to come daily if not every other day to those wells right and so you know so many problems to salt right connectivity we're talking about one of those

25:03 for example we're talking with you know one of the Super supermajors and you we would talk told them where we were building and they said you know this is a great idea but we solve it in the Permian

25:12 already right they throw millions and you know then maybe hundreds of millions on creating their own networks right up to do it and they you know people realms of data scientists but you know you can

25:24 do that if you have one hundred so two hundred wells you know and so and thus where we're going after trying to help those those operators know I remember they they basically have their own private

25:33 cellular network out there just like me to think about it that's exactly right Yeah Yeah between Laura and in and regular silver towers that's what they did interesting yes where are you now on your

25:45 journey you already have a product are you testing it do you have customers so we're we're early stage we did a ten month do we call it pilot initially but it's really a proof of concept right with a

25:59 North American operator of fifteen wealth for ten months and we were able to achieve an average of fifty seventeen percent optimization of production of oil and it's a good number especially if you

26:11 have already an artificial lift system in place right and we've found out is that we needed to do hardware right we thought it's just algorithms as that's the beauty of it now are we need to build

26:25 hardware so we talked to multiple vendors and out there is not and

26:32 some don't have the interests because they sell those those set the sensors on those you know systems in multiple industries and you know focusing on one is not always what they do and the ones they

26:43 do focus on that focus on the high producers right Yeah cause that you can charge five thousand dollars for a pressure transducer and so you can afford to pay that if you're you know you have to

26:54 hunter well since you know half of those are stripper wells and the other half are producing fifty barrels of oil per day you know so so what we have is we have the algorithms that we tested for ten

27:05 months we did a prototype of our network and we're finishing you know complete than they are and the one on all the hardware that is needed for this remember this hardware is not just like an arduino

27:18 that you can put in there I'd you need hazardous area locations certified device does a class one DIv class one they have to okay that's exactly right and so that takes also outs into the equation in

27:28 terms of cost In time right just the timeline we just finished certification of a product that we built for a company that I have that I'm a partner on and we build this and compliance tracking system

27:40 for assets from what I said this collective assets and the tax you know there look like you know a bigger apple talk right it doesn't track the assets in terms of location it can but it's not made for

27:53 that is for the certification rights because something is not certified to be where it is if the ID is serialized there you go to the cereal the you have the actual certificate of compliance on it and

28:05 other maintenance information has NFC NFC that's Awesome valuable at BLE site inspection and just tap it and say Here's it it's like I guess the analogy is like when you get into an elevator and you

28:17 see that sign that says this was last certified by the city like go find it here or there but this is each equipment is certified and you haven't You'll You you can pass audit right there and in the

28:26 search if the people who do certifications goes in there sometimes it does the certificate they need to have their own you know a key and a private key and so we made this basically electronic you

28:38 know that's Awesome Yeah basketball so we build that and we realize you know that it takes time we always knew this because you know working only gas you you find out that it takes time to do

28:47 certifications and I Yeah I mean we took Us about maybe three months to go through the design you know make some changes to their initial prototypes you know they suggest to change the battery make

28:59 some changes to the capacitors nose up with less energy and in the end once we submit them we ought to give them like twenty or thirty samples of the product and they take two or three months to test

29:09 it you know destroy them and then come to the the manufacturer and they revised the line and then they give you a certificate for the As you make changes you have to go through that are you ready to

29:20 lead the decarbonization charge energy techniques nexus is your platform for growth offering unique resources An expertise for energy and carbon tech founders join us at energy Tech Nexus dot com and

29:33 start building your Thunder lizard do they I'm curious when they're testing cause usually for explosive environment or they like blowing gas catches fire imagine they do something like that Yeah we're

29:45 dealing with a company called Eurofins because one of the you know one of them multiple industry authorize I guess certification just as you know like you'll Yup Yup Yup okay so interesting and so to

29:60 bring it back so you realized you needed to build hardware and and what was the customer challenge there was that they didn't have good hardware to even know use with your system the hardware was

30:10 great in terms of performance the problem is management so for example part of the challenge when you're doing what we're doing is that sometimes the hardware has to work

30:23 and real time meaning if his battery operated your Burning their body right and sometimes they'd only need to send data every fifteen minutes or every hour ride we build a system intelligent enough

30:35 that we tell that the the brain in the you know in the machine learning algorithm tells the sensors how often they need to send data right in so that change created a problem because not the vendors

30:50 don't do that I know they don't allow you to make changes you can go manually make the change and that's it but we're trying to avoid that try to automate that part of the process the other piece is

31:01 that you they may have Laura they may have NFC as well but they know how Laura NFC Ble and WIFI while at the same time right because our bill for specific purposes and is not this thus part of the

31:13 premise a lot of technology that is using oil and gas comes from the automation the manufacturing is literally like the the challenges that there's there's not a standard it's not integrated and so

31:24 you have a mixed mash of things that just don't work together and so you spent millions of dollars when in integration services right in systems right to make that work and he works right for the

31:34 mayor's but when that goes down you know and and the and the value chain there is this becomes a problem you know so Yeah it's kind of like a that's my terrible analogy it's like like I was at Siri or

31:47 not Siri and Google and Amazon Alexa for your home so you got the one thing and it'll like integrate with like your lights and your TV like it just needs to work on and it needs to be fifty bucks if

31:58 it's not those people won't adopt yes that's the kind of analogy I'm trying to get you if you're going to have like that central hub and it needs to all link together right and operators are a little

32:10 skeptic right I mean you can blame them they have been there fatty you know a lot of people making claims and so sometimes you know i remember talking with this operator that had this system from one

32:20 of the vendors that has some machine learning involved into it and you know it's kind of a skater but you could control it make some changes for the controller ah base on their outer mission from the

32:32 machine learning and what the operator says like I know better so I'm just thinking to myself Yeah I hear I know that you know that you have a good feel for how things work and you know this happen in

32:45 every industry but when technology comes around right as like technology proves that when you're especially you're using data and statistics and a CI learning uses all that right and so the results

32:58 are very impressive where you can get challenges like you know experts basically like I'm expert I've been doing this all my life and now you're telling Me I have to listen look at the data like the

33:10 thing is like you don't have infinite time like what it's like it's even if the AI isn't perfectly if it's ninety eight percent correct you spend your your your time on the two percent that are

33:19 terrible right like that's that's where your expertise needs you can read the regular efforts to something else that produce you more value right and thus part of the the concept Lady as like how do

33:29 we give technology to the people in the field you know the funny thing about this devices is that a two year old I mean the kids write is like watching videos they're doing they know what to do it's

33:41 intuitive it's not intuitive can we keep our operators technology that is that simple to use that doesn't require to go and take our you know three day class you know and how to configure it is like

33:52 Oh my God it's like you know let's do it I mean it's twenty twenty five right so that that was kind of like the driver you know to can do this you know Yeah so I Guess you mentioned one of the things

34:02 he learned was like you needed to beat the building hardware because if you have to kind of customize it and because there's no standardization vertically but what else did you learn from the pilot

34:11 that you've done is it still ongoing you know did you get any results yet so that other than the fact that we were able to tune the models right because these are physical models you know they are

34:22 taking you know real time sensor data as well

34:26 so we tuned the models we learned that the models work alright we saw results seventeen percent increase some fifteen wells five or ten months that's that's a big amount this is a big number for for

34:38 everybody everybody seemed to be happy about it and that's top line benefit really good as it's explained it to me cause I mean you did so the seventeen percent increase is that the edge competing

34:50 that kind of made decisions unlike you know when the lift was going to be done like what kind of decisions was a mess the suggest like you know change the length of the rod right on the rubber palm

35:00 increase the frequency stop pumping for this amount of time come back and do it again trusting you you're seeing data that tells you maybe you have you have a need to inject you know gas or water or

35:15 chemical into it sooner than you thought that you had to do it right a lot of this is reactive so the beauty machine learning is that you can make predictions right and we had so many I think means

35:26 that we can make and we were feeding that information to the operator so they were acting head said like they have a dashboard that tells them he actually the flow is really good right now maybe pump

35:36 again or you know so giving them guidance in which they could then make sense like active decisions that they can so we we we did have that sports we try not to share those passports with them because

35:47 they have also that's where fatigue I don't know i just want to know what to do like every vendor has their own dashboards like who tells them what to do so what what we were given them is like at

35:58 least the decisions right here here are the predictions right and here are the actions that are require they will have to you know they're the operator so it's up to them but we were giving them that

36:08 this list of just so you know make changes to the rough pump and the next day right to make changes to the inject a gas or or you know or water into the well and stop pumping for this amount of time

36:21 but things like that right You probably to them update the maintenance on this model because we're seeing a prominent writer with a modern so if the Mortar the other day I was talking with one of our

36:31 investors he was telling US like we were trying everything slope as the production was slowed down from like you know X number of barrels that you know like eighty barrels to like fifty and is like we

36:42 really don't know why and they tried everything to start thinking obviously we need to inject more and more chemicals into the well and realize is the motor and motor is giving up but it took them

36:51 awhile like two or three days and you're talking about trips to these wells right there looking at this way forest east south east of you know of of their site and in the Midland area is two hours to

37:03 get to the well that's like a thousand dollar trip right when you think about the time vehicle and people Yeah and the people he had to bring in Andorra Realize Oh I Gotta change the motor and so that

37:14 type of stuff is where we were you know telling the operator on it and so then today again it's no we're making the autonomous wells meaning robots like rather they can act on their own We're making

37:24 autonomous decisions for I so we don't need external data you will read the Internet week the well can make that decision on it's own and be able to communicate that to the operator so that they can

37:34 intervene know I think you know early on like in you know maybe like seven eight years ago when we first came out with these algorithms and machine learning and data then you would just be throwing

37:46 those data at the operators and they just didn't know what to do with but I think this next step of like being able to give them instructions and not confuse them with the data and just say you know

37:57 do their sector Yeah correct Yeah I think the simplicity is what makes simplicity so much better I you can steal it you know so we were working on app that allowed them to you know do things like NFC

38:09 so with within that we we did it for this for the talks that I was telling your efforts we've done it for other other customers as well and then we would spend time with adding that into their into

38:19 their hardware from the beginning because we think I weighed the the pumper can go in you know touch it and see what's going on exactly the right right or if they want to see the decision they see a

38:30 list of priorities they can drill down into it and realize oh this is why but most of them probably just like hopefully eventually inherently trust the system right but I imagine that the production

38:42 manager will be looking at the y looking at the dataset okay Yeah you know initially they're going to Validate all they need to value that I remember we were doing a pilot and we were doing something

38:51 out in like an on an Awd El Paso line and it was like two hours by car there was no there's no any solid nervous and we ended up printing out all our documentation like in Bihar Yeah because that was

39:02 the only reliable way to get get stuff if you have like really needed it cause a rut and I have power for out there too long and then be like we couldn't reliably polst off off of box if we needed to

39:14 dig it so it's literally we showed up with like four diviner zones of binder even just like how to use the control system is it being able to save time on when my pulling on my documentation Man Oh

39:24 it's incredible Yeah I mean is it Martin reminds Me My Days in in drilling rigs rise like you go there if there was any type of connectivity to the world he was very limited it was for fun you know

39:36 any of the used data very short amount of time because satellite that if they don't then ice was for expensive so you competent with the older variety of manuals and so that was the only way around it

39:46 now you can have it all in here yeah whether it's downloaded ahead of time correct that it's hard to remember running around we we on our premises that will because it's an autonomous entity all the

39:59 data should be in so when you arrive to the well all the data about the well that the manuals for everything should be in there and so that way you know you do Us like oh I didn't download it's oK to

40:11 use full force when we're talking about the other though the company that you know all of the information could be there you know so eventually right Yeah talk to US about your fundraising journey how

40:22 have you funded these initiatives we initially bootstrapped you know two for the initial couple of years we got a couple of investors that have put some some money into it but we really are racing

40:38 right now a fund four we still call it precedes because it's such a big problem to solve that we think that we need to raise you know a strong amount of money to complete what we're doing we need to

40:49 finish they are nd which has made you know creating their hardware with with done there the initial prototype of the of the you know of a three ring network you know we've we have the machine learning

41:03 algorithms we have some of the pipeline with the data but everything else needs to be done you know them the the mobile devices the dashboards that there will be the last verse of courses just try not

41:13 to get them pushed to their operators constantly and in all that is going to require you know aren't the It is the product and then getting certifications we have about six buttons that we have work

41:26 on but we haven't submitted only one costs as well Yeah Yeah So we're we want to finish all that and then not only build the product but also do the first few runs of manufacturing so that we can

41:39 invite companies into the pilots Ah you know you're going to need a lot of hardware I mean we're talking about maybe six seven sensors per wellhead plus the plus the Edge computing device per well you

41:51 know and you know so and you have a some Sergei Waifu in especially in A in a pilot we want to be able to monitor that remotely unless we want to leave there for months you know yes it seems like a

42:04 good timing for you for a piloted thought that Fucker I'm excited about Houston energy and climate we just said that for people who don't know September sixteenth were hosting a pilot a thon way you

42:16 can come and showcase your pilots in front of Corporations who would be interested in actually piloting that technology you know and I think we have tickets going on sale for that soon and I think

42:25 we'll have early bird pricing should probably get on that Yeah we should add a little of in the podcast for you Yeah absolutely I I I know so many startups they will welcome that as well go all the

42:38 way here yeah so at end you know what are your thoughts about like starting that fundraising journey do you have like a road map of like where to go who ask for money requests Yeah so well actually

42:54 I'm taking a class with Yeah and and I'm excited about it because just listening to the enthralled which will happen this monday is like OH boy this is I I Wish I knew of these you know fifteen years

43:10 ago you're a good place cause I think because everyone kind of comes to the fundraising journey with different experience and AM curious what are some I guess initial impressions you have about kind

43:21 of the fundraising process and kind of where you are today Yeah and look this is not my first enterprise this is probably my seventh company and I always bootstrapped he was never accept the very

43:35 first one I was never really it was mostly services initially consulting and service implementation saw I was trapped every single time in even products that I created within those companies that

43:47 became some sort of product the company would strapped and did it right thus why we started this way we knew from the beginning that spindle tub will require funding is a large problem even when we

43:58 sat down with one of the supermajors talking about their you know their studio their venture studio they're like this is a big vision right and said we like the vision but ah we need to see where the

44:10 products are and so we were we were a lot of the the time that we're spending now as you then define how do we go as a product like how many products are going to make the The components that you know

44:20 make the solution so in the end if the fundraising journey for Me has been first of all understanding the language of of you know of this right so I knew it the angels have spoken with angels before

44:34 but once you are racing a million two million five million you're talking with VCS now and these V ceased to speak a very different language so what's an example of something that was like a

44:44 surprising piece of language you know for example understanding the POS money premium that was a that was an interesting thing the terms you know of the of those of the funding rounds save notes for

44:58 me it's like Oh My God that is amazing that is somehow a standard arise Ye y combinator for creating that and so do I you know just understanding language in general but I think for me just a the year

45:14 that somebody who is in In investing in early stage companies will have the interest to come and talk to us and look or is this a lot of potential great potential I mean look at the numbers I mean the

45:27 the the the the market the total of this market for we're talking about is in the four four six billion dollar or you know market and so when you look at that I see why somebody would want to put

45:38 money on these things right but is interesting to see how they do it and how often they failing health and they're succeed and when they succeed it doesn't matter how many times they fail because it

45:48 succeeds so well yeah that's the power law Yeah and So I AM learning all that process right and then first of all you don't go to the big once you You know Starwood's you know asking feedback you know

45:58 so that's what I've been doing you know I had one of the first people that I talk about fundraising was with you Yeah you know back in January and in a bidding in general to me it's like you know

46:08 sitting across the table with somebody who's done the investments and they understand this world venture capital has been has been eye opening and it's been helpful to me to even work on injections

46:18 and and you know be more grounded to knowing that you know if somebody invest in me you know some of those investments won't pay off and rum I am aiming to be the one that pays friday so that puts a

46:30 lot of weight on on my shoulders but but I'm I'm enjoying the process I mean this is new rather than so and I like to learn I'm I'm a D D professionally so I liked so many things so this is one when

46:41 you think the senator's scheduler data and I'm curious how many investors have you had a chance to talk to so far maybe about a dozen looker yeah those in between angels and then maybe half and half

46:54 you know the the last half have been Micro of he sees or you know or overseas as well you know and Yeah so we're excited about it were and we joined the the software today at the Iron Ogre next week

47:07 and so you know the mercury is involved in that so we're we're hoping to see what comes out of all this you know Good good you have a cushion

47:17 Yeah my Question was I mean I was thinking about it as you were talking because this is a lot of work fundraising is hard and and you know you're definitely passionate about your do what you're doing

47:29 so talk to US about what drives you why are you doing this this como interesting question very interesting question you know I think I as I said I'm a DD right I'm a professionally so I love learning

47:44 when I my first job out of college was with baker hughes you know as a as a MWD engineer but what does that stand for measuring wild really sorry not weapons of mass destruction Yeah cool medical jobs

48:01 but it was miserable doing so which means is that you when you're drilling you have right behind the the drilling the the the drill bit right you have something called a bottle home hole assembly

48:11 which is a bunch of pipes right but have a bunch of technology behind it a telemetry You're actually you know how how do you direct you know that the drill bit through the Heavens Forbid Downhole has

48:27 to do with Azimuth it's right in in the type of the weight that you put on on the bit and all that is transmitted via pulses in the moth that you're sending so the water pressure keeps changing either

48:40 the mud that keeps changing in in on top of that that the telemetry of the machine the machine down hall is sending you information so you the code that and it looks like noise right when you look at

48:52 an actual scope but it is data you know and is telling you in ones and zeros you know how how you're doing down there you know three thousand feet though so I was doing that and so when I did mission

49:05 will em MWD I realized the amount of acknowledging it looks like going to the Moon you know drilling a well off shore and so I just got passionate about the industry right and I love technology I

49:17 program My first computer that was in with punch holes by the way it was like an Atari type of computer and it was a basic language I remember programming data sixteen realizing OH my God I love these

49:28 you know and saw and I love technology when I went to work at Innovia had this lab and I couldn't believe that people were paying me to do what I was doing don't don't tell anybody but I I thought I

49:39 was getting paid so much money to have fun you know with toys and so I like I'm an early adopter of technology I like software I like people I'm a weird engineer I love people so I love talking with

49:50 people and learning from them and and challenging people so I like building teams and this is a heck of a challenge in an amazing industry right in how do we make this industry better to write I mean

50:03 how do we prepare for the the energy transition how do we make it more responsible and I believe that all this technology is going to do that so I think that's what reisman and then that they write so

50:13 and I Guess I'm naive to a degree and I and you are right if you're a builder you've been building companies it's not the first time you're doing it and that excites you it excites me and the people

50:23 excited me so you know we like having great people around and our teams are great great people and so and you know it it cleans itself when somebody's not great right and so and I love how the people

50:35 that worked to we worked together for twenty five years on and off and so is because in one way or another we attract bring people together and you know we to solve problems together I like doing that

50:48 you know send the context of where we are today because a lot has changed from like two years ago and you know politically and just do thing now is actually a good time for what you're doing I think

51:00 is a I think it's the perfect time and I told you why there's no better time to do more with less than right now I mean the price of oil is what today five sixty seven was going Yeah so I I stop

51:12 sometimes and Stuff

51:15 It affects everybody right in multiple ways but in the end the operators who are producing you know that the SYS target that I'm looking fifty to two hundred three hundred barrels per dollar per day

51:28 to produce more with less because now they're they're any less right and so had a fifteen percent increase will be phenomenal for them right so I'm willing this is a great time to do it you know is

51:39 there something that the audience listening to the show could do for you ah Yeah I mean if we can connect so I can never speak enough with production managers honestly I mean and they're so busy is

51:53 really hard as a customer I to target buyers and it is Yeah so because they're the ones who are going to have to be responsible for whatever implementation if you implement this in a company they're

52:03 the ones who are going to be you know hall accountable in a way right to keep producing more as if if we come with a claim we can do fifty per cent more for you there are going to be holding US

52:12 accountable to that end they're going to be held accountable by their you know by the leadership team right so Ah you know if you are an operator and if you are as we want to hear this it's not about

52:23 selling them the system is about understanding what other problems they are facing are we going in the right direction you know we did this you know ten months a pilot but in the end we want to see

52:34 and hear from many ones one of our partners founders co -founders of spindle tub is he is an operator of one hundred wells right and so we have some but we want to see multiple angles to this and hear

52:45 different problems and we have been talking with operators but I can never talk to him and off you know and saw especially my co -founder was the the most technical guy in the team you know a Bruno I

52:56 he really wants to hear from every single operator he's been on the field for twenty five years working with operators but we want to hear more and I any of you know if you are in the leadership of a

53:06 company you know the other at the executive level and this resonates with what's going on we loved it You Wouldn't we're not selling anything we want to understand what's going on your company and how

53:18 a potential fifteen percent average improvement in production will will help you and can we do a pilot then at some point right we don't have good the technology completed but once we have it you know

53:29 I'm thinking and then the next nine months to a year we will have it and we'll be ready to start doing so awesome and how can people learn more about spindle top are the ot or website spindle Dot dot

53:40 C or not common

53:43 or spin the top AI Dot com have those to cover that's confusing so I spend a lot of Dot C or will be deceased Yeah Okay can I find you on Linkedin Yes absolutely if you know Ian already RT I think I'm

53:57 one of the very few Ie an audience in the world So Yeah Yeah well Thank you for coming on Awesome Thank you for having Me Guys the Pleasure rate