1 00:00:00,200 --> 00:00:03,280 Speaker 1: Chad Orfield as our guest. He's the CEO of rigzone 2 00:00:03,400 --> 00:00:05,680 Speaker 1: dot com and if you go to the website you'll 3 00:00:05,680 --> 00:00:09,520 Speaker 1: see that in addition to be a marketplace from the industry, 4 00:00:09,600 --> 00:00:12,880 Speaker 1: not the outside press that tends to hate energy, the 5 00:00:12,880 --> 00:00:15,600 Speaker 1: greeny weenies and the left wingers. It is from within 6 00:00:15,640 --> 00:00:20,920 Speaker 1: the industry. It is information about the energy industry. And 7 00:00:21,120 --> 00:00:26,200 Speaker 1: it's also the largest job placement within the industry for 8 00:00:26,360 --> 00:00:29,120 Speaker 1: all sorts of jobs, and they're hiring, and that was 9 00:00:29,120 --> 00:00:31,800 Speaker 1: the real reason we reached out to Chadnorville of rigzone 10 00:00:31,800 --> 00:00:35,400 Speaker 1: dot com as part of our business Leader Insight series 11 00:00:35,720 --> 00:00:39,639 Speaker 1: from NetSuite by Oracle, and you, as a CFO can 12 00:00:39,680 --> 00:00:43,879 Speaker 1: get their free guide to machine learning and AI and 13 00:00:43,920 --> 00:00:46,040 Speaker 1: how you can use it in your own company at 14 00:00:46,080 --> 00:00:49,440 Speaker 1: NetSuite dot com. Forward slash Berry my last name. I mean, 15 00:00:49,479 --> 00:00:51,440 Speaker 1: technically you'd not put my last name in there, but 16 00:00:51,479 --> 00:00:52,600 Speaker 1: you make me look good if you do, and I 17 00:00:52,680 --> 00:00:56,760 Speaker 1: appreciate it. NetSuite dot com Forward slash Berry. So you 18 00:00:56,800 --> 00:01:00,279 Speaker 1: were talking about AI and the role of AI, and 19 00:01:00,320 --> 00:01:03,240 Speaker 1: you don't see that replacing a lot of jobs in 20 00:01:03,280 --> 00:01:06,679 Speaker 1: the short run. You see it more as something that 21 00:01:06,880 --> 00:01:09,720 Speaker 1: employees will just have to use as a tool. Is 22 00:01:09,720 --> 00:01:10,720 Speaker 1: that what I'm hearing you say? 23 00:01:11,240 --> 00:01:12,800 Speaker 2: Absolutely? And I can give you an example. 24 00:01:13,880 --> 00:01:17,000 Speaker 3: Last month, I was at the Saudi Aramco Gala for 25 00:01:17,080 --> 00:01:19,880 Speaker 3: the fiftieth anniversary of Iranco America's in Houston. 26 00:01:19,920 --> 00:01:21,000 Speaker 2: It was a fantastic event. 27 00:01:21,640 --> 00:01:23,640 Speaker 3: I met a gentleman there who leads their data services, 28 00:01:23,760 --> 00:01:26,440 Speaker 3: brilliant guy double master's double PHC from MIT. 29 00:01:26,640 --> 00:01:27,880 Speaker 2: He leads data sciences there. 30 00:01:27,959 --> 00:01:31,240 Speaker 3: We're just fascinating fellow talking to him talking to some 31 00:01:31,280 --> 00:01:34,679 Speaker 3: other folks at a data science event actually last year, 32 00:01:35,200 --> 00:01:40,200 Speaker 3: and they're using AI for some really interesting purposes. One 33 00:01:40,200 --> 00:01:42,160 Speaker 3: of them I can tell you that I thought was 34 00:01:42,160 --> 00:01:46,600 Speaker 3: interesting is they're using it looking at machines to predict 35 00:01:46,600 --> 00:01:47,800 Speaker 3: when they were going to break down. 36 00:01:47,920 --> 00:01:49,880 Speaker 2: You know, it's cash is king. 37 00:01:49,960 --> 00:01:52,240 Speaker 3: You need your you need to be producing, and so 38 00:01:53,160 --> 00:01:56,200 Speaker 3: pump's big machinery that they leverage out in the old field. 39 00:01:56,880 --> 00:01:58,720 Speaker 3: Being able to tell when those things need you know, 40 00:01:58,760 --> 00:02:01,960 Speaker 3: the appropriate time to service them, what when the general 41 00:02:01,960 --> 00:02:04,200 Speaker 3: times that they break down under what conditions and what 42 00:02:04,400 --> 00:02:06,560 Speaker 3: oil fields and you know what environment. 43 00:02:07,000 --> 00:02:07,400 Speaker 2: Uh. 44 00:02:07,440 --> 00:02:10,120 Speaker 3: These AI models that they're developing can more accurately do 45 00:02:10,200 --> 00:02:12,280 Speaker 3: that and it creates more efficiency. So you hear everyone 46 00:02:12,320 --> 00:02:14,239 Speaker 3: say you know, we don't have as many rigs, but 47 00:02:14,280 --> 00:02:16,519 Speaker 3: they operate more efficiently. This is part of why they're 48 00:02:16,520 --> 00:02:17,560 Speaker 3: operating more efficiently. 49 00:02:17,639 --> 00:02:18,760 Speaker 2: You know. You hear that and you don't know what 50 00:02:18,800 --> 00:02:20,440 Speaker 2: it means. This is what it means. 51 00:02:20,440 --> 00:02:22,799 Speaker 3: They're bringing AI to bear and that doesn't mean it's 52 00:02:22,840 --> 00:02:24,720 Speaker 3: doing it on its own and a robot is bringing it. 53 00:02:24,760 --> 00:02:28,280 Speaker 3: Back to leadership, there are engineers and managers out in 54 00:02:28,320 --> 00:02:31,960 Speaker 3: the field that they're help using AI modeling to optimize wells, 55 00:02:32,360 --> 00:02:34,960 Speaker 3: and they're responsible for a group or a field of wells. 56 00:02:35,120 --> 00:02:37,760 Speaker 3: They're able to more efficiently and effectively look at all 57 00:02:37,800 --> 00:02:41,120 Speaker 3: of that data, make decisions, look at suggestions, look at 58 00:02:41,160 --> 00:02:43,680 Speaker 3: past experience, and those models can look at all of 59 00:02:43,680 --> 00:02:47,640 Speaker 3: this data significantly more effectively than a person could and 60 00:02:47,720 --> 00:02:52,200 Speaker 3: find patterns, find trends. This is what AI is bringing 61 00:02:52,200 --> 00:02:52,919 Speaker 3: to the industry. 62 00:02:53,000 --> 00:02:54,200 Speaker 2: Just just one example. 63 00:02:54,440 --> 00:02:58,240 Speaker 3: They're using AI to uh, you know, for safety mech 64 00:02:58,440 --> 00:03:01,080 Speaker 3: you know, processors looking to see if people are. 65 00:03:00,880 --> 00:03:03,800 Speaker 2: Not wearing hard hats. You know, I mean, it's as 66 00:03:03,840 --> 00:03:04,560 Speaker 2: simple as that. 67 00:03:04,680 --> 00:03:07,320 Speaker 3: There's a lot of really interesting things that AI is 68 00:03:07,360 --> 00:03:11,720 Speaker 3: actually doing. Everyone sees AI or here's it and thinks terminator, No, no, no, 69 00:03:12,040 --> 00:03:13,880 Speaker 3: you know, We're far from there. I'm not saying we're 70 00:03:13,880 --> 00:03:16,000 Speaker 3: not going to get there, but you know, right now, 71 00:03:16,960 --> 00:03:19,520 Speaker 3: they're really interesting tools that we can use to our advantage. 72 00:03:19,560 --> 00:03:24,760 Speaker 3: I use chat GPT to brainstorm, and as you ask 73 00:03:24,840 --> 00:03:27,320 Speaker 3: for an assistant, I'll need one because I have these 74 00:03:27,360 --> 00:03:30,520 Speaker 3: AI tools now to create frameworks for code whenever I 75 00:03:30,560 --> 00:03:31,880 Speaker 3: need it. 76 00:03:32,120 --> 00:03:33,840 Speaker 1: Give me a project you were working on where you 77 00:03:33,880 --> 00:03:35,800 Speaker 1: did that. Because I'm not I'm not a big tech person, 78 00:03:35,800 --> 00:03:38,360 Speaker 1: but I understand how it can be. Give me a 79 00:03:38,400 --> 00:03:40,240 Speaker 1: real life example of when you used it recently. 80 00:03:41,680 --> 00:03:44,520 Speaker 3: So just writing queries, I can tell it what the 81 00:03:44,640 --> 00:03:48,360 Speaker 3: data structures look like and give them, you know, the 82 00:03:48,400 --> 00:03:51,800 Speaker 3: information that shows them what data I'm dealing with, tell 83 00:03:51,840 --> 00:03:54,520 Speaker 3: them what's there, and you know, the more experience you 84 00:03:54,560 --> 00:03:57,040 Speaker 3: have with them, and the more detailed and the better 85 00:03:57,160 --> 00:03:59,960 Speaker 3: the question if you will to the AI, the better 86 00:04:00,000 --> 00:04:03,000 Speaker 3: sponsor you're going to get. So a very detailed set 87 00:04:03,040 --> 00:04:05,840 Speaker 3: of information with guidelines or rules. I gave it that, 88 00:04:05,920 --> 00:04:07,760 Speaker 3: and it was able to write a query that might 89 00:04:07,760 --> 00:04:10,760 Speaker 3: have taken me forty five minutes of you know, ironing 90 00:04:10,800 --> 00:04:12,440 Speaker 3: and ironing out and tweaking. 91 00:04:13,280 --> 00:04:15,280 Speaker 2: It was able to do almost instantaneous. 92 00:04:15,440 --> 00:04:18,400 Speaker 3: Now I've not got one piece of code or anything 93 00:04:18,480 --> 00:04:20,560 Speaker 3: back from any of the big aips and I use 94 00:04:20,600 --> 00:04:24,000 Speaker 3: the Big three eye tools from Google, Tragedy too and profit. 95 00:04:24,560 --> 00:04:26,640 Speaker 2: I'm not getting anything that's not wrong on the first go. 96 00:04:26,880 --> 00:04:29,200 Speaker 3: You have to look at it, you have to supervise 97 00:04:29,360 --> 00:04:32,159 Speaker 3: the work, and I have to change something on every piece. 98 00:04:32,400 --> 00:04:36,200 Speaker 3: But it's giving me the head start. It's doing, you know, 99 00:04:36,279 --> 00:04:39,600 Speaker 3: forty percent minimum of the foundation of the core code, 100 00:04:39,680 --> 00:04:41,920 Speaker 3: the framework, and I ask it for framework more than anything, 101 00:04:42,279 --> 00:04:45,320 Speaker 3: and then I'll fill in the you know, the pieces 102 00:04:45,360 --> 00:04:47,200 Speaker 3: that that I know it's not going to do because 103 00:04:47,200 --> 00:04:48,600 Speaker 3: it doesn't have experience, it doesn't. 104 00:04:48,400 --> 00:04:49,320 Speaker 2: Know that data like I do. 105 00:04:50,480 --> 00:04:54,320 Speaker 3: But those that's just one example, you know, just brainstorming anything, 106 00:04:54,400 --> 00:04:56,120 Speaker 3: any types of ideas out you know, I was talking 107 00:04:56,160 --> 00:04:58,239 Speaker 3: about AI on you rigsone. You know, we're looking at 108 00:04:58,800 --> 00:05:00,000 Speaker 3: putting ending pages together. 109 00:05:00,040 --> 00:05:02,880 Speaker 2: They're around that to show people, you know, like. 110 00:05:02,839 --> 00:05:05,400 Speaker 3: I said, salary, Well, people can't go and think on 111 00:05:05,400 --> 00:05:07,680 Speaker 3: their own. Let's asked, well, we'll prevent will present them 112 00:05:07,680 --> 00:05:10,480 Speaker 3: a bunch of salary information. Culture recruiters that are using 113 00:05:10,520 --> 00:05:13,720 Speaker 3: our site, are using our recruitment services and for our 114 00:05:13,760 --> 00:05:16,039 Speaker 3: candidates just to get an idea of kind of what 115 00:05:16,080 --> 00:05:17,960 Speaker 3: are ranges looking like for this type of role? 116 00:05:18,000 --> 00:05:21,120 Speaker 2: What does entry level? What does experience? Mid level or senior? 117 00:05:21,920 --> 00:05:23,920 Speaker 2: You know, we'll generate all of that and create it 118 00:05:24,040 --> 00:05:24,360 Speaker 2: for them. 119 00:05:24,440 --> 00:05:26,200 Speaker 3: So I was looking at categories, you know, I had 120 00:05:26,200 --> 00:05:27,840 Speaker 3: my idea of what they could be. Hey, what are 121 00:05:27,839 --> 00:05:29,200 Speaker 3: some other ones I may be overlooking? 122 00:05:29,320 --> 00:05:33,480 Speaker 2: Right again? As a brainstorming tool, it's it's brilliant. 123 00:05:33,680 --> 00:05:35,640 Speaker 1: Well, I don't want to sound like a shameless shield 124 00:05:35,640 --> 00:05:38,120 Speaker 1: for the folks who love our business series at Oracle, 125 00:05:38,200 --> 00:05:40,880 Speaker 1: but as you know, that's what NetSuite does is a 126 00:05:41,000 --> 00:05:45,479 Speaker 1: CFO needs information and making sense of data. And so 127 00:05:45,880 --> 00:05:48,160 Speaker 1: I'm not a person who uses that, but I am 128 00:05:48,200 --> 00:05:51,000 Speaker 1: a person who has people who use that. When I 129 00:05:51,040 --> 00:05:55,520 Speaker 1: ask my CPA at Deroch Partners, hey can you tell 130 00:05:55,560 --> 00:05:58,239 Speaker 1: me what I should be paying this employee for this level? 131 00:05:58,640 --> 00:06:01,719 Speaker 1: They can pull data in a much faster that is, 132 00:06:01,800 --> 00:06:04,280 Speaker 1: actual data from real data sets and make some sense 133 00:06:04,279 --> 00:06:06,400 Speaker 1: of it in so many different ways for me to 134 00:06:06,440 --> 00:06:09,159 Speaker 1: make better decisions. And so I think that's what people. 135 00:06:09,680 --> 00:06:13,000 Speaker 1: You know, I was originally afraid of AI because you know, 136 00:06:13,080 --> 00:06:15,960 Speaker 1: there's all the robot movies, but it's gonna happen one 137 00:06:15,960 --> 00:06:17,760 Speaker 1: way or another. And it's a question of using it 138 00:06:17,800 --> 00:06:19,440 Speaker 1: as a tool. I mean, I don't know how old 139 00:06:19,480 --> 00:06:21,320 Speaker 1: you are. I'm fifty four. When I was a kid, 140 00:06:21,360 --> 00:06:23,560 Speaker 1: we were so afraid of technology because technology was going 141 00:06:23,640 --> 00:06:26,400 Speaker 1: to be awful. But in most cases, technology has made 142 00:06:26,440 --> 00:06:27,200 Speaker 1: my life easier. 143 00:06:27,480 --> 00:06:27,600 Speaker 2: Right. 144 00:06:27,640 --> 00:06:30,080 Speaker 1: We bitch about cell phones, but I can call my 145 00:06:30,160 --> 00:06:32,479 Speaker 1: wife while I'm driving home and say, honey, I'll be 146 00:06:32,520 --> 00:06:34,880 Speaker 1: home in twenty minutes, and she says, oh great, I 147 00:06:34,880 --> 00:06:37,080 Speaker 1: can put the cornbread in, whereas I don't have to 148 00:06:37,080 --> 00:06:38,720 Speaker 1: wait to get there. And I mean it's little things, 149 00:06:38,800 --> 00:06:39,160 Speaker 1: but it. 150 00:06:39,040 --> 00:06:40,880 Speaker 2: Matters, right, Yeah, of course. 151 00:06:41,080 --> 00:06:42,719 Speaker 3: It's what Bill Gates said right when it's talking about 152 00:06:42,720 --> 00:06:45,200 Speaker 3: the Internet in his early landmark book. You know, it's 153 00:06:45,200 --> 00:06:47,159 Speaker 3: like it's going to wash over the world like a wave, 154 00:06:47,279 --> 00:06:50,279 Speaker 3: and it has all technology. Does that like what the 155 00:06:50,279 --> 00:06:52,880 Speaker 3: iPhone is, like what social media has done? You know, 156 00:06:53,040 --> 00:06:55,560 Speaker 3: not always sometimes it is to the detriment, but in 157 00:06:55,600 --> 00:06:59,520 Speaker 3: general it makes data accessible and data is the big 158 00:06:59,520 --> 00:07:03,240 Speaker 3: difference you talked about, NetSuite. I can tell you just 159 00:07:03,279 --> 00:07:04,800 Speaker 3: talking to the folks that are AKO and others that 160 00:07:04,880 --> 00:07:08,960 Speaker 3: are leveraging AI for you know, field operations for optimization 161 00:07:09,680 --> 00:07:11,760 Speaker 3: out in the field and wells and drilling and you know, 162 00:07:11,960 --> 00:07:13,720 Speaker 3: geophysical where are we going to drill. 163 00:07:13,680 --> 00:07:14,920 Speaker 2: All of these types of things. 164 00:07:15,440 --> 00:07:18,120 Speaker 3: One thing that's really important that data scientists are doing 165 00:07:18,240 --> 00:07:20,520 Speaker 3: is they're not spending as much time on the modeling. 166 00:07:20,880 --> 00:07:22,960 Speaker 3: They're spending more time on the data that's going into 167 00:07:23,000 --> 00:07:26,560 Speaker 3: a terabytes, massive exobites, massive amounts of data that's going 168 00:07:26,600 --> 00:07:29,760 Speaker 3: in cleaning that data to where it's actually usable. That's 169 00:07:29,800 --> 00:07:31,680 Speaker 3: where they're spending a good portion of their time and 170 00:07:32,160 --> 00:07:36,200 Speaker 3: expertise is taking all this data that these tools out 171 00:07:36,240 --> 00:07:39,680 Speaker 3: in the field spin out and putting it in a 172 00:07:39,720 --> 00:07:41,960 Speaker 3: format to where it's actually usable. You know, in the 173 00:07:42,080 --> 00:07:45,400 Speaker 3: in tech they have of saying garbage in garbage out right, 174 00:07:45,720 --> 00:07:47,320 Speaker 3: You've got to give it the right things. It's the 175 00:07:47,320 --> 00:07:49,679 Speaker 3: same as a question to an AI, you know tool 176 00:07:49,800 --> 00:07:51,880 Speaker 3: a large language model. You've got to ask it the 177 00:07:51,960 --> 00:07:53,880 Speaker 3: right questions and frame it properly, and then you're going 178 00:07:53,920 --> 00:07:55,680 Speaker 3: to get some pretty interesting things out of it, and 179 00:07:55,720 --> 00:07:56,800 Speaker 3: it'll really be useful. 180 00:07:56,920 --> 00:08:00,000 Speaker 1: Americans a nation that can be defined in a single world. 181 00:08:00,600 --> 00:08:02,720 Speaker 1: I was gonna foot him at number. 182 00:08:03,240 --> 00:08:07,480 Speaker 3: Not only was it authentic frontier jibbery, an expressed. 183 00:08:06,960 --> 00:08:09,679 Speaker 1: Their courage scene of this day and the Michael Berry 184 00:08:09,760 --> 00:08:13,960 Speaker 1: show Chat Norville is our guest. He is the CEO 185 00:08:14,200 --> 00:08:19,560 Speaker 1: of rigzone dot com, which is a marketplace of information, news, 186 00:08:19,800 --> 00:08:26,680 Speaker 1: insight analysis on energy jobs so drilling, refining, downhol downstream, upstream, 187 00:08:26,680 --> 00:08:31,280 Speaker 1: midstream investment, and the largest job placement for people in 188 00:08:31,320 --> 00:08:35,920 Speaker 1: the energy industry. Which is so your website, rigzone dot 189 00:08:35,920 --> 00:08:39,320 Speaker 1: com says seven hundred and twenty thousand industry professionals can't 190 00:08:39,320 --> 00:08:42,360 Speaker 1: be wrong. Is that how many people accume your site 191 00:08:42,400 --> 00:08:43,679 Speaker 1: or what does that number represent? 192 00:08:44,960 --> 00:08:47,520 Speaker 3: Yeah, it's actually small when you consider it from that term. 193 00:08:47,559 --> 00:08:50,240 Speaker 3: Seven hundred thousand plus is how many just receive our 194 00:08:50,320 --> 00:08:53,360 Speaker 3: daily newsletter every day and we have well over one 195 00:08:53,440 --> 00:08:56,120 Speaker 3: hundred and twenty thousand that open it every day. It's 196 00:08:56,160 --> 00:08:58,240 Speaker 3: not the same that are opening it every day. We 197 00:08:58,320 --> 00:09:01,040 Speaker 3: have six to seven hundred thousand different and industry professionals 198 00:09:01,040 --> 00:09:02,440 Speaker 3: that get impressions. 199 00:09:01,880 --> 00:09:03,360 Speaker 2: From rig zone every day. 200 00:09:03,480 --> 00:09:06,240 Speaker 3: Outside of that, so across emails, the website, all of 201 00:09:06,240 --> 00:09:09,000 Speaker 3: our social channels and digital marketing mechanisms. 202 00:09:09,880 --> 00:09:11,839 Speaker 2: It's broad. It's vast that you know, we have. 203 00:09:11,960 --> 00:09:14,080 Speaker 3: We touched a lot of parts of the industry, you know, 204 00:09:14,080 --> 00:09:16,280 Speaker 3: across all of our jobs, news events. 205 00:09:16,800 --> 00:09:19,040 Speaker 2: Uh, yeah, it's vast, to say the least. 206 00:09:20,200 --> 00:09:25,480 Speaker 1: It's uh, it's just incredible how little information bleeds out 207 00:09:25,520 --> 00:09:29,600 Speaker 1: that's truthful and useful to the general public. When this is, 208 00:09:29,840 --> 00:09:32,439 Speaker 1: you know, energy, people forget energy. People think of it 209 00:09:32,520 --> 00:09:37,040 Speaker 1: as just jobs, or just oil or gasoline. Etchy. Energy 210 00:09:37,120 --> 00:09:39,080 Speaker 1: is at the core of everything we do, not just 211 00:09:39,080 --> 00:09:41,680 Speaker 1: heating and cooling, every product that we use. I mean, 212 00:09:41,760 --> 00:09:44,920 Speaker 1: it's just incredible. By the way, I don't know what 213 00:09:44,960 --> 00:09:47,960 Speaker 1: the stock market's done today. I haven't checked, but energy 214 00:09:48,120 --> 00:09:51,840 Speaker 1: is at the heart of your stock portfolio, which when 215 00:09:51,840 --> 00:09:54,520 Speaker 1: you retire, your four oh one K is going The 216 00:09:54,520 --> 00:09:58,160 Speaker 1: bedrock of most four oh one K plans today is 217 00:09:58,160 --> 00:10:01,200 Speaker 1: those safe blue chip inner g stocks, and you know 218 00:10:01,480 --> 00:10:04,360 Speaker 1: the greeny winnies want to attack them. You better hope 219 00:10:04,480 --> 00:10:08,040 Speaker 1: those companies that are called evil and their profits continue 220 00:10:08,040 --> 00:10:10,360 Speaker 1: to be profitable because that's what's holding up your stock 221 00:10:10,400 --> 00:10:14,000 Speaker 1: price for school teachers and plumbers and everybody else. And 222 00:10:14,080 --> 00:10:17,120 Speaker 1: that that is easy to forget. Chad, I wanted you 223 00:10:17,160 --> 00:10:18,760 Speaker 1: to finish that sentence if you remember what you were 224 00:10:18,800 --> 00:10:20,959 Speaker 1: saying before I filibustered you, And then I want to 225 00:10:20,960 --> 00:10:23,480 Speaker 1: ask for your advice for people wanting to into the industry. 226 00:10:23,520 --> 00:10:24,760 Speaker 1: Do you remember what you were saying or did I 227 00:10:24,920 --> 00:10:25,760 Speaker 1: did I throw you off? 228 00:10:26,880 --> 00:10:27,439 Speaker 2: I can't remember. 229 00:10:27,559 --> 00:10:29,880 Speaker 1: Okay, well let me ask you this. You were talking 230 00:10:29,920 --> 00:10:33,360 Speaker 1: about who's hiring. Let's start with entry level. Let's say 231 00:10:33,520 --> 00:10:35,640 Speaker 1: I get a lot of emails from people who've just 232 00:10:35,720 --> 00:10:39,280 Speaker 1: gotten out of the military, and they say, what should 233 00:10:39,280 --> 00:10:42,040 Speaker 1: I do? Where should I go? Who's hiring? They want 234 00:10:42,040 --> 00:10:44,280 Speaker 1: a career, not just a job, right, So they don't 235 00:10:44,280 --> 00:10:46,320 Speaker 1: want to go do fast food. They want to start 236 00:10:46,320 --> 00:10:49,040 Speaker 1: in a career. And I tell people find a job 237 00:10:49,080 --> 00:10:51,800 Speaker 1: in energy because the upsides are crazy. What do you 238 00:10:51,880 --> 00:10:53,760 Speaker 1: say to that guy, he just got out of the Marines. 239 00:10:55,240 --> 00:10:58,559 Speaker 3: Yeah, So, first and foremost, the very explicit oil and 240 00:10:58,640 --> 00:11:03,079 Speaker 3: guys roles and in training and education is going to 241 00:11:03,200 --> 00:11:05,320 Speaker 3: be there for a long time as long as someone 242 00:11:05,400 --> 00:11:07,440 Speaker 3: at that point would be able to fulfill a career 243 00:11:07,480 --> 00:11:11,400 Speaker 3: with it. So, whether that's patrol engineering or mechanical engineering 244 00:11:11,400 --> 00:11:15,960 Speaker 3: focus on oil and gas, geology, chemical engineering, and electional 245 00:11:16,000 --> 00:11:19,440 Speaker 3: engineering focusing on oil and gas, those things are going 246 00:11:19,520 --> 00:11:21,400 Speaker 3: to be there for the foreseeable future. I mean for 247 00:11:21,440 --> 00:11:24,640 Speaker 3: the next to twenty fifty I would guess at least, 248 00:11:24,920 --> 00:11:27,119 Speaker 3: you know, like I said, emerging markets are coming online 249 00:11:27,559 --> 00:11:29,920 Speaker 3: We're not going to see a significant change in at 250 00:11:30,000 --> 00:11:31,880 Speaker 3: least the demand side of oil and gas for a 251 00:11:31,920 --> 00:11:32,840 Speaker 3: good while. 252 00:11:33,240 --> 00:11:35,600 Speaker 2: So I think they could still fulfill a strong career. 253 00:11:35,640 --> 00:11:36,280 Speaker 2: And here's the thing. 254 00:11:36,640 --> 00:11:38,880 Speaker 3: Some people might be reticent to go get a patrol 255 00:11:38,960 --> 00:11:41,319 Speaker 3: engineer degree, so there's gonna be less competition. There's a 256 00:11:41,360 --> 00:11:42,520 Speaker 3: lot of people with a lot of experience. 257 00:11:42,559 --> 00:11:43,120 Speaker 2: They're going to be. 258 00:11:43,040 --> 00:11:45,080 Speaker 3: Retiring, right the boomers and all of them have already 259 00:11:45,120 --> 00:11:48,520 Speaker 3: started to. But there's going to be openings and opportunities there. 260 00:11:48,400 --> 00:11:49,319 Speaker 2: For those folks. 261 00:11:50,240 --> 00:11:54,360 Speaker 3: You know, there's a lot of opportunities still in those fields. 262 00:11:54,360 --> 00:11:57,640 Speaker 3: So I would tell them you probably have more opportunity 263 00:11:57,640 --> 00:12:00,080 Speaker 3: because this can be more demand for you because it'll. 264 00:11:59,920 --> 00:12:00,480 Speaker 2: Be year of you. 265 00:12:01,320 --> 00:12:04,079 Speaker 3: Aside from that, if you are concerned and you're wanting 266 00:12:04,120 --> 00:12:05,319 Speaker 3: something more transferable. 267 00:12:06,120 --> 00:12:08,400 Speaker 2: We talked earlier about the tech roles. Uh. 268 00:12:08,720 --> 00:12:12,480 Speaker 3: You know, electrical and instrumentation are massive and you don't 269 00:12:12,480 --> 00:12:14,800 Speaker 3: have to get a full batch first degree to do that. 270 00:12:14,960 --> 00:12:19,520 Speaker 3: You could get an associates or certification. So for electrical, Uh, 271 00:12:19,600 --> 00:12:24,920 Speaker 3: there's electrical engineering technology, power distribution technicians are in massive demand. 272 00:12:25,120 --> 00:12:28,720 Speaker 3: Huge old services companies I know right now, are you 273 00:12:28,720 --> 00:12:31,080 Speaker 3: know jumping at the bits to get power distribution folks, 274 00:12:31,760 --> 00:12:36,120 Speaker 3: power plant technology, energy systems, uh, industrial maintenance technology, so 275 00:12:36,160 --> 00:12:38,600 Speaker 3: you can be a maintenance tech. They're massive demand and 276 00:12:38,640 --> 00:12:40,080 Speaker 3: they're transferable skills. 277 00:12:40,559 --> 00:12:43,440 Speaker 2: Uh. Those are associates degree certifications. There's a. 278 00:12:45,080 --> 00:12:50,600 Speaker 3: SEE certify, there's a power systems tech electrical power distributions certifications. 279 00:12:50,640 --> 00:12:54,319 Speaker 3: I know those are out there industrial electricians. 280 00:12:54,360 --> 00:12:56,120 Speaker 2: You could do any of those things, right. 281 00:12:56,400 --> 00:12:58,320 Speaker 3: That could be as little as three or six months 282 00:12:58,520 --> 00:13:00,560 Speaker 3: on those certifications, and you could at a job. There 283 00:13:00,600 --> 00:13:02,840 Speaker 3: are those roles out there for those folks, and they'd 284 00:13:03,000 --> 00:13:06,479 Speaker 3: love to train you up. And like I said, it's transferable. 285 00:13:06,520 --> 00:13:08,200 Speaker 3: You could do a lot of different things. A lot 286 00:13:08,200 --> 00:13:11,360 Speaker 3: of industries you know, require those skills. On the instrumentation 287 00:13:11,440 --> 00:13:14,720 Speaker 3: and you know you talked earlier about valves automatically changing 288 00:13:14,880 --> 00:13:19,400 Speaker 3: and whatnot. That's PLC programming right, it's uh, the programmable 289 00:13:19,640 --> 00:13:21,280 Speaker 3: programmable logic controllers. 290 00:13:21,360 --> 00:13:21,480 Speaker 2: Right. 291 00:13:21,520 --> 00:13:24,760 Speaker 3: These automation and control technologies same thing. 292 00:13:24,800 --> 00:13:28,720 Speaker 2: You can get a socius degree and instrumentation or controls automation. Uh. 293 00:13:28,760 --> 00:13:31,200 Speaker 3: They have robotics technology which is cool that goes into 294 00:13:31,240 --> 00:13:33,600 Speaker 3: a ROV. We have huge companies we work with that 295 00:13:33,840 --> 00:13:37,040 Speaker 3: just focus on that oceaneering is huge in that space. 296 00:13:37,240 --> 00:13:38,920 Speaker 2: Uh, there's a few other companies we work with that 297 00:13:39,040 --> 00:13:39,560 Speaker 2: do that as well. 298 00:13:40,000 --> 00:13:42,480 Speaker 3: Obviously, electrical engineering you don't have to have a double E. 299 00:13:42,800 --> 00:13:44,720 Speaker 2: It's a fantastic degree. I would encourage you to get 300 00:13:44,720 --> 00:13:46,000 Speaker 2: it if you have the time and the means. 301 00:13:46,400 --> 00:13:50,040 Speaker 3: But you can get an electrical Engineering Technology Associates. Uh, 302 00:13:50,559 --> 00:13:53,120 Speaker 3: that's your maintenance placing here too, and instrumentation and automate 303 00:13:53,280 --> 00:13:56,520 Speaker 3: automation roles. So uh those as sociates degree, spend two 304 00:13:56,600 --> 00:13:59,280 Speaker 3: years user Uh, you know your grant from the military 305 00:13:59,320 --> 00:14:01,760 Speaker 3: and go do that. You need to work and you 306 00:14:01,800 --> 00:14:04,280 Speaker 3: want to do something shorter term. The certifications and automation 307 00:14:04,400 --> 00:14:05,840 Speaker 3: and instrumentation too. 308 00:14:05,880 --> 00:14:07,679 Speaker 2: There's control systems. 309 00:14:07,280 --> 00:14:11,640 Speaker 3: Tech certifications, there's automation professionals. You can get a PLC 310 00:14:11,760 --> 00:14:15,880 Speaker 3: Programming certification. Those exist for someone coming in. Those are 311 00:14:15,920 --> 00:14:19,720 Speaker 3: really highly transferable skills and things that aren't massively time 312 00:14:19,760 --> 00:14:22,320 Speaker 3: consuming to go get a certification or associate's. 313 00:14:21,760 --> 00:14:23,720 Speaker 2: Degree on the government that you've earned and you know, 314 00:14:23,760 --> 00:14:25,840 Speaker 2: we appreciate you and please take advantage of it. 315 00:14:26,760 --> 00:14:28,640 Speaker 3: I would say that for that person from the military 316 00:14:28,680 --> 00:14:30,560 Speaker 3: looking into it, those are you know, good skills that 317 00:14:30,600 --> 00:14:32,120 Speaker 3: are going to be there no matter what happens at 318 00:14:32,200 --> 00:14:34,360 Speaker 3: set your mind at ease. If you were concerned about 319 00:14:34,400 --> 00:14:38,720 Speaker 3: the industry, which I'm not. You mentioned certifications earlier, if 320 00:14:38,760 --> 00:14:41,160 Speaker 3: you have worked in the old patch at all, or 321 00:14:41,240 --> 00:14:43,440 Speaker 3: you have some kind of experience. 322 00:14:43,040 --> 00:14:43,920 Speaker 2: Around certain things. 323 00:14:44,000 --> 00:14:47,720 Speaker 3: API American Patrol Institute, which is a massive partner of ours. 324 00:14:48,760 --> 00:14:53,400 Speaker 3: They have really great certification programs, so they do a 325 00:14:53,400 --> 00:14:59,440 Speaker 3: lot of inspection different certifications, so piping, pressure vessels, tank inspectors, 326 00:14:59,480 --> 00:15:03,160 Speaker 3: you know, HSC related things and inspections always going to 327 00:15:03,680 --> 00:15:06,160 Speaker 3: be really highly needed and sought after. 328 00:15:06,280 --> 00:15:09,560 Speaker 2: So those are really good certifications to get Q one 329 00:15:09,640 --> 00:15:10,120 Speaker 2: and Q too. 330 00:15:10,200 --> 00:15:14,160 Speaker 3: This is more of a senior professional type of role, 331 00:15:14,240 --> 00:15:17,680 Speaker 3: but those are great certifications at API as well, you know, 332 00:15:17,720 --> 00:15:20,840 Speaker 3: designing implementing quality management systems kind of in line with 333 00:15:20,840 --> 00:15:21,400 Speaker 3: the ISO. 334 00:15:22,080 --> 00:15:24,440 Speaker 1: And so do you go to API to get that certification? 335 00:15:25,560 --> 00:15:27,440 Speaker 3: Yes, yeah, you reach out to them and they have 336 00:15:27,800 --> 00:15:29,840 Speaker 3: folks on staff and'd be more than happy to talk 337 00:15:29,880 --> 00:15:32,640 Speaker 3: to you about what your experience has been and you 338 00:15:32,680 --> 00:15:34,760 Speaker 3: know what might fit starting from scratch. I don't know 339 00:15:34,800 --> 00:15:36,920 Speaker 3: that those would necessarily be useful, you'd probably be more 340 00:15:37,240 --> 00:15:39,600 Speaker 3: Those are folks probably that have been around it or 341 00:15:39,640 --> 00:15:41,280 Speaker 3: have a little more experience. But again you could talk 342 00:15:41,320 --> 00:15:43,400 Speaker 3: to them. I don't know from the ground up what 343 00:15:43,760 --> 00:15:45,440 Speaker 3: you know. They all have available, like I said, the 344 00:15:45,480 --> 00:15:48,440 Speaker 3: other associates and certifications or things I know a bit 345 00:15:48,440 --> 00:15:50,000 Speaker 3: more about where I think they could get right in 346 00:15:50,040 --> 00:15:52,400 Speaker 3: without any experience in any of those technologies. 347 00:15:52,800 --> 00:15:57,400 Speaker 1: Chad Norville is the CEO of rigzone dot com and 348 00:15:57,480 --> 00:16:02,440 Speaker 1: they have job hostings there in the energy industry. I 349 00:16:02,480 --> 00:16:04,880 Speaker 1: get a lot of emails from you folks out there 350 00:16:05,480 --> 00:16:08,360 Speaker 1: looking for a job, have just come out of the military, 351 00:16:08,400 --> 00:16:10,280 Speaker 1: and this is where I'll send you more with Chadnorville 352 00:16:10,640 --> 00:16:11,840 Speaker 1: rig zone dot com coming. 353 00:16:11,680 --> 00:16:32,120 Speaker 4: Up, Michael, as part of our continuing series of Insights 354 00:16:32,280 --> 00:16:33,560 Speaker 4: from business Leaders. 355 00:16:34,800 --> 00:16:39,000 Speaker 1: Actually they call it ramon do you know what oracle? 356 00:16:39,120 --> 00:16:43,800 Speaker 1: They call it success from scratch and they heard what 357 00:16:43,880 --> 00:16:47,240 Speaker 1: we're doing with business leaders. We had Russell Leborrow last 358 00:16:47,240 --> 00:16:50,200 Speaker 1: week and they loved it, and so they said, we 359 00:16:50,240 --> 00:16:53,440 Speaker 1: would love to just sponsor your show and tie in 360 00:16:53,880 --> 00:16:56,760 Speaker 1: because of what we do. Over forty one thousand businesses 361 00:16:56,760 --> 00:16:59,720 Speaker 1: of upgraded to net Suite bio Oracle. They use their 362 00:16:59,760 --> 00:17:03,320 Speaker 1: a in machine learning to make better decisions, especially CFOs, 363 00:17:03,680 --> 00:17:07,040 Speaker 1: which is why netsweet dot com forward slash berries where 364 00:17:07,040 --> 00:17:09,720 Speaker 1: you can find that netswite dot com forward slash berry, 365 00:17:09,840 --> 00:17:16,119 Speaker 1: Especially if you're a CFO looking for more help assessing, understanding, 366 00:17:16,359 --> 00:17:20,520 Speaker 1: making sense of all the data you have. Let me 367 00:17:20,560 --> 00:17:24,960 Speaker 1: ask you an operational question. Do you say Norville or 368 00:17:25,000 --> 00:17:26,120 Speaker 1: do you say Norville? 369 00:17:27,640 --> 00:17:31,119 Speaker 3: Everyone says Norville. My grandfather told me it was Norville. 370 00:17:31,320 --> 00:17:32,359 Speaker 3: I'll respond to either. 371 00:17:32,640 --> 00:17:33,359 Speaker 1: Where are you from? 372 00:17:34,840 --> 00:17:35,600 Speaker 2: I'm from Houston. 373 00:17:35,960 --> 00:17:37,280 Speaker 1: Where'd you go? Where'd you grow up? 374 00:17:39,080 --> 00:17:39,600 Speaker 2: Deer Park? 375 00:17:40,359 --> 00:17:41,399 Speaker 1: Where'd you go to high school? 376 00:17:42,800 --> 00:17:43,480 Speaker 2: Park? High School? 377 00:17:43,520 --> 00:17:44,560 Speaker 1: Did you know Andy Pettitt? 378 00:17:47,080 --> 00:17:49,000 Speaker 3: No, I've been around him. He was a little before me. 379 00:17:49,960 --> 00:17:54,280 Speaker 3: I'm mid forty, so he was a little older. But yeah, 380 00:17:54,359 --> 00:17:56,960 Speaker 3: so I'm a church you know, my cousins, my in 381 00:17:57,040 --> 00:18:00,320 Speaker 3: law's go to his church, and so you know, I'd 382 00:18:00,320 --> 00:18:03,160 Speaker 3: see them all around a lot. But you know, we 383 00:18:03,160 --> 00:18:05,200 Speaker 3: weren't friends, friends or anything of that nature. 384 00:18:05,440 --> 00:18:10,000 Speaker 1: Did you ever find yourself stopping and marveling at how 385 00:18:10,160 --> 00:18:13,080 Speaker 1: high he kicked his right leg when he would throw 386 00:18:13,119 --> 00:18:15,240 Speaker 1: those big looping curveballs. 387 00:18:16,960 --> 00:18:20,200 Speaker 2: Oh yeah, amazing? Right, So you know who else did 388 00:18:20,200 --> 00:18:20,639 Speaker 2: that ramon? 389 00:18:21,160 --> 00:18:23,440 Speaker 1: You might know? Are you a baseball fan, Chad? 390 00:18:25,000 --> 00:18:26,400 Speaker 2: Oh of course, huge fan. 391 00:18:26,840 --> 00:18:31,320 Speaker 1: So uh, there was a picture for the Oakland A's 392 00:18:31,480 --> 00:18:34,280 Speaker 1: named Barry he had he was a lefty. He also 393 00:18:34,520 --> 00:18:38,280 Speaker 1: what Zeno Berry Zito he also had that you never 394 00:18:38,320 --> 00:18:41,119 Speaker 1: see right handed pitchers do this. They have that pitch 395 00:18:41,440 --> 00:18:44,560 Speaker 1: that feels like, I mean, it looks to me when 396 00:18:44,600 --> 00:18:46,879 Speaker 1: you see the ball coming in, it looks like the 397 00:18:46,880 --> 00:18:49,960 Speaker 1: ball came from behind their head, like in the in 398 00:18:50,040 --> 00:18:53,119 Speaker 1: the ball of your neck. And it's just just big, looping, 399 00:18:54,320 --> 00:19:00,760 Speaker 1: off speed pitch that gives batters fits. And Pettitt had it, 400 00:19:00,840 --> 00:19:03,159 Speaker 1: and Barry Zito had it. And by the way, for 401 00:19:03,280 --> 00:19:07,200 Speaker 1: anybody out there listening, I have a number of mutual 402 00:19:07,240 --> 00:19:10,760 Speaker 1: friends with Andy Pettitt who have politely explained to him 403 00:19:10,760 --> 00:19:13,159 Speaker 1: that I would like to be his best friend. And 404 00:19:13,400 --> 00:19:16,720 Speaker 1: it hasn't worked out yet, and so I don't know 405 00:19:16,760 --> 00:19:20,360 Speaker 1: how to do that without it being weird. Just hold on, Chad, 406 00:19:20,400 --> 00:19:23,120 Speaker 1: this is very important. But since you're from Deer Park, 407 00:19:23,160 --> 00:19:25,600 Speaker 1: I need to get somebody out there is going to 408 00:19:25,640 --> 00:19:28,480 Speaker 1: be close friends with Andy and he's going to say, oh, 409 00:19:29,040 --> 00:19:31,200 Speaker 1: I'll put y'all together and then it's just going to 410 00:19:31,280 --> 00:19:34,600 Speaker 1: happen and he can work on my pitching mechanics. Did 411 00:19:34,680 --> 00:19:35,520 Speaker 1: you play baseball? 412 00:19:37,240 --> 00:19:37,560 Speaker 2: I did? 413 00:19:38,880 --> 00:19:41,639 Speaker 1: Did soccer in high school if you went on to 414 00:19:41,640 --> 00:19:42,520 Speaker 1: play college. 415 00:19:43,440 --> 00:19:45,679 Speaker 3: Well, yeah, of course, but like everyone, you play all 416 00:19:45,680 --> 00:19:47,800 Speaker 3: the sports and you kind of end up sticking. 417 00:19:47,480 --> 00:19:48,440 Speaker 2: With what you're best at. 418 00:19:48,480 --> 00:19:50,760 Speaker 3: So I was pretty fast and pretty good at soccer, 419 00:19:50,840 --> 00:19:52,920 Speaker 3: so the rest went away. 420 00:19:53,240 --> 00:19:56,000 Speaker 1: You know, what was your in high school? What did 421 00:19:56,000 --> 00:19:56,880 Speaker 1: you graduate at? 422 00:19:58,359 --> 00:20:01,120 Speaker 3: I was just sort of sick foot and probably won 423 00:20:01,280 --> 00:20:02,399 Speaker 3: seventy five. 424 00:20:03,520 --> 00:20:05,600 Speaker 1: Ramon says, if you say just under six foot, you 425 00:20:05,600 --> 00:20:07,920 Speaker 1: were actually five to ten broll. You don't know him 426 00:20:08,080 --> 00:20:08,720 Speaker 1: enough to say. 427 00:20:08,520 --> 00:20:14,040 Speaker 2: That, I'll at least five to eleven. Okay, guaranteed. 428 00:20:14,240 --> 00:20:17,520 Speaker 1: What was your forty time? Would you guess? 429 00:20:18,720 --> 00:20:20,600 Speaker 2: I think at my peak i'd probably touch four or 430 00:20:20,600 --> 00:20:24,359 Speaker 2: five in the four fives for six four seven was easy. 431 00:20:24,840 --> 00:20:28,440 Speaker 1: Hold on, you think you ran a forty in high 432 00:20:28,480 --> 00:20:30,399 Speaker 1: school at four or five? 433 00:20:32,160 --> 00:20:34,280 Speaker 3: Well, that probably right after high school when I. 434 00:20:34,240 --> 00:20:34,880 Speaker 2: Went to college. 435 00:20:35,800 --> 00:20:38,600 Speaker 1: That's human for a white boy. That's fast. 436 00:20:41,600 --> 00:20:45,800 Speaker 3: I mean, okay, I think I probably hit a high 437 00:20:45,840 --> 00:20:48,240 Speaker 3: four or five at some point. I never did, but 438 00:20:48,520 --> 00:20:51,200 Speaker 3: I'm assuming I probably could have at some point at my. 439 00:20:51,200 --> 00:20:56,480 Speaker 2: Peak fitness level. I'm projecting. I'll admit, don't have proof 440 00:20:56,520 --> 00:20:57,760 Speaker 2: from that. I know. 441 00:20:58,160 --> 00:21:01,280 Speaker 1: If you know, look, if you were fast. You know 442 00:21:01,320 --> 00:21:03,920 Speaker 1: you were fast. I mean, I don't think a guy's 443 00:21:03,920 --> 00:21:06,800 Speaker 1: going to say there were four or five. If you 444 00:21:06,840 --> 00:21:10,399 Speaker 1: know they played O line, you know for Nebraska, that 445 00:21:10,520 --> 00:21:13,679 Speaker 1: means you were fast. I'm not doubting it. I'm saying 446 00:21:14,000 --> 00:21:17,800 Speaker 1: I'm I'm putting a marker on this moment so that 447 00:21:17,960 --> 00:21:20,600 Speaker 1: I think about it later that that I'm putting a 448 00:21:20,680 --> 00:21:23,280 Speaker 1: ribbon on it. That's a big deal. Okay. So then 449 00:21:23,320 --> 00:21:27,479 Speaker 1: you go off to Iowa to en Sioux City at 450 00:21:27,480 --> 00:21:29,600 Speaker 1: the little school you wouldn't hardly give me the name of. 451 00:21:29,960 --> 00:21:31,280 Speaker 1: And then where did you go from there? 452 00:21:33,359 --> 00:21:35,760 Speaker 2: Yeah? So it had some Japanese affiliation. 453 00:21:35,840 --> 00:21:38,199 Speaker 3: In the nineties they had a great depression basically, so 454 00:21:38,440 --> 00:21:40,680 Speaker 3: started pulling out money and had accreditation issues. 455 00:21:41,680 --> 00:21:43,119 Speaker 2: You know, I was making pretty good, good grades. I 456 00:21:43,119 --> 00:21:44,480 Speaker 2: didn't want to stick around for that, so I. 457 00:21:44,520 --> 00:21:47,920 Speaker 3: Transferred by U of H got into programming. Like I said, 458 00:21:47,920 --> 00:21:52,600 Speaker 3: I was doing a joint program on chemical plant operations. 459 00:21:52,640 --> 00:21:55,320 Speaker 2: So I fum one credit, shy of having an associate 460 00:21:55,320 --> 00:21:57,480 Speaker 2: screen and that I was going to program SCATA and 461 00:21:58,000 --> 00:21:58,840 Speaker 2: do that for the plants. 462 00:21:58,840 --> 00:22:00,280 Speaker 3: It was kind of the thinking at the time, But 463 00:22:00,320 --> 00:22:03,880 Speaker 3: then I started really liking the computer programming, and uh 464 00:22:03,920 --> 00:22:06,919 Speaker 3: so I kind of let that go and ended up 465 00:22:06,920 --> 00:22:09,760 Speaker 3: finishing my bachelor science degree and information systems and then 466 00:22:09,800 --> 00:22:10,200 Speaker 3: I got an. 467 00:22:10,200 --> 00:22:11,800 Speaker 1: MBA where did you get your. 468 00:22:13,760 --> 00:22:14,160 Speaker 2: Hula? 469 00:22:14,520 --> 00:22:16,240 Speaker 1: And then were you working at the time? 470 00:22:17,600 --> 00:22:17,959 Speaker 2: I was. 471 00:22:18,119 --> 00:22:19,720 Speaker 3: I was going to score at night for AT and T, 472 00:22:20,160 --> 00:22:24,320 Speaker 3: which was an amazing experience because the space program was 473 00:22:24,440 --> 00:22:26,600 Speaker 3: the Shuttle program was still going in full force. So 474 00:22:26,680 --> 00:22:30,720 Speaker 3: my mentors were double PhDs, you know, directors of the 475 00:22:30,800 --> 00:22:33,640 Speaker 3: International Space Station before it was called Space Station Freedom. 476 00:22:34,000 --> 00:22:37,280 Speaker 2: Uh that was one of my mentors. So it was 477 00:22:37,320 --> 00:22:37,960 Speaker 2: really interesting. 478 00:22:38,160 --> 00:22:40,480 Speaker 3: I got to do that and talk to those folks, 479 00:22:40,680 --> 00:22:43,280 Speaker 3: and then I got to you know, at AT and T. 480 00:22:43,400 --> 00:22:45,919 Speaker 3: I developed some code and programs that kind of got 481 00:22:45,960 --> 00:22:49,879 Speaker 3: some attention and ended up uh meeting some of the 482 00:22:50,000 --> 00:22:52,760 Speaker 3: C suite folks who kind of took me under their wing. 483 00:22:52,840 --> 00:22:56,640 Speaker 3: And Karen Jennings, who was time twenty five most influential women, 484 00:22:57,520 --> 00:22:59,720 Speaker 3: helped me out a bit. And you know, just to 485 00:22:59,800 --> 00:23:02,080 Speaker 3: get manage of different opportunities when there was that's the 486 00:23:02,080 --> 00:23:05,480 Speaker 3: whole thing, right, It's about you know, it's about playing 487 00:23:05,520 --> 00:23:06,000 Speaker 3: ball whenever. 488 00:23:06,200 --> 00:23:08,240 Speaker 1: Of course the time time, of course, what did your 489 00:23:08,320 --> 00:23:08,720 Speaker 1: dad do. 490 00:23:10,960 --> 00:23:11,480 Speaker 2: Construction? 491 00:23:13,600 --> 00:23:17,320 Speaker 1: So your interest in computer programming. And I asked this 492 00:23:17,600 --> 00:23:23,040 Speaker 1: because I had no interest in computers or certainly not 493 00:23:23,119 --> 00:23:25,919 Speaker 1: making it figuring out how one worked. What do you 494 00:23:26,000 --> 00:23:29,000 Speaker 1: think sparked the interesting computer program because I my nephew 495 00:23:29,040 --> 00:23:31,920 Speaker 1: does it, and I think it's a great field. By 496 00:23:31,960 --> 00:23:34,480 Speaker 1: the way, Oh, by the way, Chad, I don't know 497 00:23:34,480 --> 00:23:37,280 Speaker 1: if you're hiring or not, but my nephew needs a job. 498 00:23:37,600 --> 00:23:40,600 Speaker 1: He just graduated from Lamar with like a three to eight. 499 00:23:41,000 --> 00:23:45,080 Speaker 1: It's my brother, my late brother's son, and he's starting 500 00:23:45,080 --> 00:23:47,280 Speaker 1: to work on his NBA. And if you were to 501 00:23:47,320 --> 00:23:49,240 Speaker 1: hire him as part of this interview, that'd be great. 502 00:23:49,240 --> 00:23:52,080 Speaker 1: When it ramoned, Ramone said that'd be great. I'm just 503 00:23:52,160 --> 00:23:53,800 Speaker 1: kidding you, but I am looking for him a job. 504 00:23:53,880 --> 00:23:55,840 Speaker 1: No pressure, Yeah, yeah, no pressure at all. You don't 505 00:23:55,880 --> 00:23:57,959 Speaker 1: have to make the decision right now. I'll send you 506 00:23:58,040 --> 00:24:01,720 Speaker 1: the his resume during the break. But here's what's weird. 507 00:24:01,720 --> 00:24:04,440 Speaker 1: And I tell him his name is Braiden. Braiden, what 508 00:24:04,480 --> 00:24:07,200 Speaker 1: made you want to be a computer programmer? Our family 509 00:24:07,359 --> 00:24:11,159 Speaker 1: is cops and oil fill workers and one guy who 510 00:24:11,240 --> 00:24:14,239 Speaker 1: talks on the radio. You literally have nobody in our 511 00:24:14,280 --> 00:24:16,919 Speaker 1: family who can do anything more than turn a computer 512 00:24:17,000 --> 00:24:20,439 Speaker 1: on and that's a big deal. Like why it's just 513 00:24:20,520 --> 00:24:24,159 Speaker 1: so odd to me that people have that interest. I 514 00:24:24,160 --> 00:24:28,399 Speaker 1: guess just because it doesn't come naturally to me. Maybe 515 00:24:28,520 --> 00:24:32,080 Speaker 1: that's the reason we're talking to Chad Norville or Norville 516 00:24:32,440 --> 00:24:35,320 Speaker 1: of rigzone dot com and we will continue our conversation 517 00:24:35,359 --> 00:24:36,000 Speaker 1: with him coming up. 518 00:24:36,960 --> 00:24:43,080 Speaker 2: Story Kung on Michael Bay Good Shoga on dog Lump. 519 00:24:45,520 --> 00:24:51,000 Speaker 1: Rigzone dot com is the site of where the energy 520 00:24:51,200 --> 00:24:54,480 Speaker 1: industry goes to find jobs, to post jobs, to get 521 00:24:54,520 --> 00:24:57,879 Speaker 1: inside information, to talk about what oil prices are, what 522 00:24:57,960 --> 00:25:02,440 Speaker 1: futures are doing, who's buying, who's selling, what the trends are. 523 00:25:02,880 --> 00:25:06,600 Speaker 1: Rigzone dot com. They are not a sponsor Ramon an 524 00:25:06,600 --> 00:25:09,000 Speaker 1: answer your question, but they one day will be because 525 00:25:09,000 --> 00:25:11,120 Speaker 1: it's a perfect partnership. But that's not why he's our guest. 526 00:25:11,160 --> 00:25:13,040 Speaker 1: He's our guest because I've been wanting to talk energy 527 00:25:13,080 --> 00:25:17,400 Speaker 1: for a while. So for folks that are simply saying, hey, 528 00:25:17,480 --> 00:25:19,320 Speaker 1: I don't have any special skills, I go back to 529 00:25:19,320 --> 00:25:21,159 Speaker 1: my marine that just got out. Because this comes up 530 00:25:21,160 --> 00:25:23,679 Speaker 1: a lot. Is there a company I get I might 531 00:25:23,720 --> 00:25:25,720 Speaker 1: get you in trouble if you pick one, But is 532 00:25:25,760 --> 00:25:28,080 Speaker 1: there a company that you are a mean? Can they 533 00:25:28,080 --> 00:25:29,800 Speaker 1: go to rigzone and put their information on there, and 534 00:25:29,800 --> 00:25:31,840 Speaker 1: they're gonna because nobody wants to do monster or any 535 00:25:31,840 --> 00:25:34,199 Speaker 1: of that anymore. Somebody wants to get hired right now. 536 00:25:34,200 --> 00:25:36,040 Speaker 1: They're willing, willing to work hard, and they're willing to 537 00:25:36,080 --> 00:25:38,439 Speaker 1: travel as far as Midland, not further. Well, they'll go 538 00:25:38,560 --> 00:25:41,359 Speaker 1: Midland to the west and Homa to the east. Are 539 00:25:41,440 --> 00:25:42,840 Speaker 1: they going to Is there a job waiting for them 540 00:25:42,920 --> 00:25:43,320 Speaker 1: right now? 541 00:25:43,840 --> 00:25:45,280 Speaker 2: Yeah? Potentially, I think. 542 00:25:45,400 --> 00:25:49,120 Speaker 3: You know, Unfortunately, everything is technology based now, so it's 543 00:25:49,200 --> 00:25:51,680 Speaker 3: kind of you know, entry paid entry. 544 00:25:51,760 --> 00:25:53,880 Speaker 2: Right. You have to have a CV or resume of some. 545 00:25:53,800 --> 00:25:56,040 Speaker 3: Sorts and you need to upload it for our website. 546 00:25:56,040 --> 00:25:58,879 Speaker 3: You upload it to rig zone, activate your your account, 547 00:25:58,960 --> 00:26:02,000 Speaker 3: your CV, do some searching, do some applying. 548 00:26:02,040 --> 00:26:02,199 Speaker 2: You know. 549 00:26:02,240 --> 00:26:04,639 Speaker 3: We have AI mechanisms in there that will do what 550 00:26:04,720 --> 00:26:06,399 Speaker 3: it can to help you. It will look at what 551 00:26:06,440 --> 00:26:08,920 Speaker 3: your qualifications are, It will look at what job titles 552 00:26:08,960 --> 00:26:11,240 Speaker 3: you've had previously, or what your experiences are. It will 553 00:26:11,359 --> 00:26:12,919 Speaker 3: keep an eye out on those. As long as you have, 554 00:26:13,280 --> 00:26:16,280 Speaker 3: for instance, emails activated, it will look at those things, 555 00:26:16,320 --> 00:26:18,600 Speaker 3: and as jobs become available that you qualify for, it 556 00:26:18,600 --> 00:26:20,919 Speaker 3: will send you those and it's tiered, so it's going 557 00:26:21,000 --> 00:26:24,040 Speaker 3: to give you the most optimal job for your experiences 558 00:26:23,760 --> 00:26:27,520 Speaker 3: and what you're looking for right then, and then it'll 559 00:26:27,560 --> 00:26:29,359 Speaker 3: tear down and say, okay, let's step out a little 560 00:26:29,400 --> 00:26:31,200 Speaker 3: more broadly and see if there's anything in the space 561 00:26:31,280 --> 00:26:33,360 Speaker 3: maybe that you know might work for you. And then 562 00:26:33,400 --> 00:26:36,080 Speaker 3: it'll go even more general. So not everything is going 563 00:26:36,119 --> 00:26:38,800 Speaker 3: to be on the nose, but it's looking all the time. 564 00:26:38,880 --> 00:26:40,160 Speaker 2: So dismiss the ones. 565 00:26:39,960 --> 00:26:42,240 Speaker 3: That aren't that you don't think work. Keep an eye 566 00:26:42,240 --> 00:26:44,320 Speaker 3: out because when the ones do. When the market does 567 00:26:44,359 --> 00:26:46,359 Speaker 3: start picking up, and like I said earlier, we are 568 00:26:46,680 --> 00:26:48,760 Speaker 3: a lot of folks are expecting that to start happening. 569 00:26:48,760 --> 00:26:52,920 Speaker 3: As you know, all of these unleashed American energy policies 570 00:26:52,960 --> 00:26:54,960 Speaker 3: start really taking hold. In one of those you know, 571 00:26:55,000 --> 00:26:57,920 Speaker 3: I talked about some of the policy for the regulations 572 00:26:57,920 --> 00:26:59,560 Speaker 3: and the red tape being removed. 573 00:27:00,080 --> 00:27:01,400 Speaker 2: He gave them thirty days. 574 00:27:01,200 --> 00:27:03,680 Speaker 3: To do this, so some of us might start happening 575 00:27:03,680 --> 00:27:06,159 Speaker 3: pretty quick, and the industry is, you know, anxious for it. 576 00:27:07,040 --> 00:27:09,880 Speaker 3: They'll start happening and popping on the website. We start 577 00:27:09,880 --> 00:27:11,440 Speaker 3: sending emails to those folks. As I told you, we 578 00:27:11,520 --> 00:27:12,800 Speaker 3: send thirty million emails a month. 579 00:27:13,280 --> 00:27:15,240 Speaker 2: That's not spam. Those are people that wanted to be 580 00:27:15,240 --> 00:27:17,400 Speaker 2: on our website. If someone's getting emails because they asked 581 00:27:17,400 --> 00:27:18,320 Speaker 2: to on our website. 582 00:27:18,400 --> 00:27:20,520 Speaker 3: If someone has a job on our website one of 583 00:27:20,520 --> 00:27:22,960 Speaker 3: our recruiters, it's because that does an active job that 584 00:27:23,000 --> 00:27:24,920 Speaker 3: they want on our website. We don't discourge them each 585 00:27:24,960 --> 00:27:28,480 Speaker 3: stuff there. Like all of these other generalists and other competitors, 586 00:27:29,000 --> 00:27:30,800 Speaker 3: those are people we work with. If you see people 587 00:27:30,880 --> 00:27:33,320 Speaker 3: on our website, we talk to those companies. Most of 588 00:27:33,359 --> 00:27:34,679 Speaker 3: them we talked to you for a long time and 589 00:27:34,720 --> 00:27:37,840 Speaker 3: pretty consistently, so you know, we're doing our best for 590 00:27:37,880 --> 00:27:39,800 Speaker 3: the candidates to really try to help them find those 591 00:27:39,920 --> 00:27:42,439 Speaker 3: roles on the website. We have job fairs. Go to 592 00:27:42,480 --> 00:27:44,280 Speaker 3: our events and look at what job fairs are coming 593 00:27:44,320 --> 00:27:46,359 Speaker 3: up and you can go and talk to those folks 594 00:27:46,440 --> 00:27:49,080 Speaker 3: on site. Almost every event will have someone that they're 595 00:27:49,119 --> 00:27:52,120 Speaker 3: looking to train up and give you know, entry level 596 00:27:52,119 --> 00:27:56,320 Speaker 3: without experience, and it's broad right. There's a lot of 597 00:27:56,320 --> 00:27:59,280 Speaker 3: different types of roles that they'll take in and they'll 598 00:27:59,280 --> 00:28:02,560 Speaker 3: train you up. Some of them are a little harder. 599 00:28:02,560 --> 00:28:04,919 Speaker 3: You have to have certifications for some kind of training 600 00:28:05,200 --> 00:28:07,920 Speaker 3: in order to do it. Like electricity, there's liability issues 601 00:28:07,920 --> 00:28:10,560 Speaker 3: I can't just take anywhere. But there are a lot 602 00:28:10,600 --> 00:28:12,840 Speaker 3: of other types rules, you know, floral and decands. A 603 00:28:12,880 --> 00:28:14,080 Speaker 3: lot of people make a lot of money in this 604 00:28:14,160 --> 00:28:16,160 Speaker 3: industry that started kind of at the bottom. 605 00:28:15,880 --> 00:28:16,800 Speaker 2: And worked their way up. 606 00:28:16,840 --> 00:28:20,000 Speaker 3: And you can do it quickly, you know, in some instances, 607 00:28:20,040 --> 00:28:25,600 Speaker 3: so they're still offshore. There's floating production. There's engineering and 608 00:28:25,640 --> 00:28:28,040 Speaker 3: procurement in construction, right, they call them PPC. 609 00:28:27,880 --> 00:28:30,600 Speaker 2: Companies, ministry pipelines. 610 00:28:30,640 --> 00:28:34,120 Speaker 3: There's welding, massive you know, mechanics or fruly high demands, 611 00:28:35,200 --> 00:28:39,360 Speaker 3: like very high demand, actually engineering and designs. There's just 612 00:28:39,480 --> 00:28:45,080 Speaker 3: so many ultra equipment cranes, operators, you know, heavy machinery operators. 613 00:28:45,880 --> 00:28:48,040 Speaker 3: Last year, I saw that job at our job fairs 614 00:28:48,080 --> 00:28:51,120 Speaker 3: as much as any job probably if you just you know, 615 00:28:51,320 --> 00:28:53,640 Speaker 3: operate a hydro machinery, you have experience doing that in 616 00:28:53,640 --> 00:28:54,200 Speaker 3: the military. 617 00:28:54,320 --> 00:28:57,280 Speaker 1: Imagine are out there, Yeah, and hey those are the 618 00:28:57,280 --> 00:29:01,200 Speaker 1: real toys, right. If you can drive a tank and 619 00:29:01,680 --> 00:29:07,880 Speaker 1: veer away from IED's under fire air and ground assault, 620 00:29:08,240 --> 00:29:10,400 Speaker 1: then yeah, I think you can operate this piece of 621 00:29:10,440 --> 00:29:14,400 Speaker 1: equipment for one of the rig Zone dot Com sponsors, 622 00:29:14,440 --> 00:29:16,160 Speaker 1: one of the companies out in the offield. I didn't 623 00:29:16,160 --> 00:29:18,040 Speaker 1: think about that, but I mean talk about an experience. 624 00:29:18,240 --> 00:29:20,280 Speaker 1: But a lot of guys in your industry tell me 625 00:29:21,000 --> 00:29:26,120 Speaker 1: that they consciously look for veterans because these are guys 626 00:29:26,120 --> 00:29:29,880 Speaker 1: that work on a team, that make sacrifice, that are disciplined, 627 00:29:30,040 --> 00:29:33,880 Speaker 1: that are tough, and it's something that is an ideal 628 00:29:33,960 --> 00:29:36,479 Speaker 1: set of talents, particularly for that field. 629 00:29:36,720 --> 00:29:39,760 Speaker 3: Yeah, so look for our industry and every industry says this, 630 00:29:39,840 --> 00:29:44,320 Speaker 3: but you know they say communication. It's almost a cliche, right, communications, 631 00:29:44,360 --> 00:29:48,840 Speaker 3: and you know, the intangibles, those are off the charts 632 00:29:48,880 --> 00:29:51,280 Speaker 3: for these folks, right, They're they're like the best of 633 00:29:51,320 --> 00:29:54,560 Speaker 3: the best when it comes to those skills, those off 634 00:29:54,600 --> 00:29:57,720 Speaker 3: the paper skills, if you will. So they absolutely, you know, 635 00:29:57,880 --> 00:30:00,480 Speaker 3: want those those types of candidates. When we we did 636 00:30:00,480 --> 00:30:03,320 Speaker 3: one in San Antonio last year, I believe this last year. 637 00:30:03,680 --> 00:30:05,720 Speaker 3: We do them every year, they're pretty much but we 638 00:30:05,840 --> 00:30:07,880 Speaker 3: did one out there and they focus on Eagle Forward. 639 00:30:07,920 --> 00:30:10,760 Speaker 2: But we had the there's. 640 00:30:10,600 --> 00:30:12,880 Speaker 3: A lot of military influence at San Antonio, right, they 641 00:30:12,880 --> 00:30:17,680 Speaker 3: have bases out there, and the NSA has people out 642 00:30:17,680 --> 00:30:20,480 Speaker 3: there that work with the UTSA. My son's actually studying 643 00:30:20,520 --> 00:30:23,880 Speaker 3: cybersecurity at UTSA. It's about to be a senior So 644 00:30:24,160 --> 00:30:26,640 Speaker 3: that's why because they're one of the few institutions in 645 00:30:26,640 --> 00:30:29,600 Speaker 3: the United States that has a relationship with the NESSA. Uh, 646 00:30:29,640 --> 00:30:31,520 Speaker 3: but they have a lot of military personnel there. So 647 00:30:32,080 --> 00:30:33,680 Speaker 3: for the job fair, we reached out to all those 648 00:30:33,760 --> 00:30:35,600 Speaker 3: organizations and said, look, these companies. 649 00:30:35,320 --> 00:30:37,560 Speaker 2: Would love to talk to you. Please come out and 650 00:30:37,600 --> 00:30:39,480 Speaker 2: have a conversation with them and see if there's something 651 00:30:39,480 --> 00:30:40,680 Speaker 2: there for you. Uh. 652 00:30:41,240 --> 00:30:44,480 Speaker 3: You know, I would encourage our military and ex military 653 00:30:44,520 --> 00:30:46,040 Speaker 3: to always come to our job fair as I talk 654 00:30:46,080 --> 00:30:49,240 Speaker 3: to those folks because they are wanted, they're highly regarded, 655 00:30:49,280 --> 00:30:52,880 Speaker 3: and they're you know, strong employees that I think most 656 00:30:52,920 --> 00:30:55,800 Speaker 3: of our companies would absolutely, you know, love to have. 657 00:30:55,880 --> 00:30:57,680 Speaker 3: And like I said, there are there's a lot of 658 00:30:57,760 --> 00:30:59,560 Speaker 3: things that you can do in the military. It's not 659 00:30:59,640 --> 00:31:01,280 Speaker 3: just like infantry in the front. 660 00:31:01,320 --> 00:31:04,080 Speaker 2: There's you know, people do communications, that do technology, they 661 00:31:04,080 --> 00:31:04,760 Speaker 2: do heavy. 662 00:31:04,600 --> 00:31:08,680 Speaker 3: Machinery, and those were all heavily required skills and roles 663 00:31:08,680 --> 00:31:11,480 Speaker 3: in our industry. You know, like I said, I I 664 00:31:11,480 --> 00:31:14,640 Speaker 3: can say without a doubt, I in tech and heavy machinery, 665 00:31:14,680 --> 00:31:17,840 Speaker 3: operator and operators and other types of machinery. Those are 666 00:31:18,000 --> 00:31:20,680 Speaker 3: For the last twelve months, I've seen those out the 667 00:31:20,760 --> 00:31:23,000 Speaker 3: job fairs, probably more than any of the other roles. 668 00:31:23,080 --> 00:31:27,520 Speaker 1: That's interesting, and you foresee that continuing for some time. 669 00:31:28,200 --> 00:31:31,680 Speaker 3: Yeah, would it would even more so, right the quantity 670 00:31:31,720 --> 00:31:31,960 Speaker 3: of them. 671 00:31:32,000 --> 00:31:34,560 Speaker 2: You would have other roles that would be equally needed. 672 00:31:35,520 --> 00:31:38,640 Speaker 3: As things start kicking off again, whenever Trump's policies really 673 00:31:38,680 --> 00:31:41,520 Speaker 3: start taking hold, I would see more of the other 674 00:31:41,560 --> 00:31:44,440 Speaker 3: types of roles in addition to those. But those wouldn't 675 00:31:44,440 --> 00:31:47,080 Speaker 3: be falling back, right, the others would just be gaining 676 00:31:47,120 --> 00:31:50,600 Speaker 3: in quantity. So yeah, that's not going to change. It's 677 00:31:50,600 --> 00:31:52,480 Speaker 3: still those needs are going to be there out in 678 00:31:52,520 --> 00:31:56,200 Speaker 3: the wherever. Maybe maybe on our old field or maybe 679 00:31:56,280 --> 00:31:59,360 Speaker 3: on a it could be. There's a lot of different variants, 680 00:31:59,360 --> 00:32:01,720 Speaker 3: like I said, prayings and you know, all kinds of 681 00:32:01,720 --> 00:32:02,480 Speaker 3: different machinery. 682 00:32:03,120 --> 00:32:08,200 Speaker 1: It is. It's so interesting because the energy industry being 683 00:32:08,280 --> 00:32:12,000 Speaker 1: such a critical part of our economy. You know, you 684 00:32:12,000 --> 00:32:15,200 Speaker 1: think of healthcare, you think of energy, think of agriculture. 685 00:32:15,200 --> 00:32:18,200 Speaker 1: I mean, these are the big ones, and it affects 686 00:32:18,240 --> 00:32:20,840 Speaker 1: every aspect of our lives, from the gas we put 687 00:32:20,840 --> 00:32:24,440 Speaker 1: in our car to every product on your desk, every plastic, 688 00:32:24,560 --> 00:32:28,440 Speaker 1: every implant, every you know, fluid. It all comes from 689 00:32:28,440 --> 00:32:32,120 Speaker 1: the energy industry, and then it underpins your four oh 690 00:32:32,120 --> 00:32:35,880 Speaker 1: one K, your retirement, your investments. But it's also of 691 00:32:35,920 --> 00:32:38,880 Speaker 1: critical importance, and particularly to me, because if you don't 692 00:32:38,880 --> 00:32:41,600 Speaker 1: have a job, then politics matters a lot less to 693 00:32:41,640 --> 00:32:45,120 Speaker 1: you than putting food on the table. And that's why 694 00:32:45,120 --> 00:32:48,760 Speaker 1: I wanted to talk to rigzone dot com. Chad Noorville, 695 00:32:48,840 --> 00:32:51,120 Speaker 1: you are a great guest. I appreciate you devoting so 696 00:32:51,200 --> 00:32:53,720 Speaker 1: much time to us. Let's talk again, and next time 697 00:32:53,760 --> 00:32:56,080 Speaker 1: you're having a job fair here in Houston, if you'll 698 00:32:56,080 --> 00:32:58,120 Speaker 1: shoot me an email, I will gladly promote it on 699 00:32:58,120 --> 00:32:59,560 Speaker 1: the air because that helps our people. 700 00:33:00,080 --> 00:33:00,280 Speaker 2: Yeah. 701 00:33:00,320 --> 00:33:02,920 Speaker 3: So we do Houston at least at least three times 702 00:33:02,920 --> 00:33:04,000 Speaker 3: a year, sometimes four. 703 00:33:04,240 --> 00:33:06,520 Speaker 2: So we have one there March fifth. 704 00:33:07,560 --> 00:33:09,880 Speaker 1: All right, as we get closer, I will Is it 705 00:33:09,880 --> 00:33:12,720 Speaker 1: free to somebody to the to the interviewee, to the. 706 00:33:12,680 --> 00:33:17,040 Speaker 3: Prospect, Yeah, our candidates and professionals, it's absolutely free. We 707 00:33:17,200 --> 00:33:19,760 Speaker 3: recommend you sign up, you know, create an account on 708 00:33:19,760 --> 00:33:22,320 Speaker 3: the rig Zone, upload your CV, you know, set that. 709 00:33:22,320 --> 00:33:24,000 Speaker 2: Up, and then you know sign. 710 00:33:23,800 --> 00:33:26,239 Speaker 3: Up register for the event because you know we'll get 711 00:33:26,280 --> 00:33:30,000 Speaker 3: you right in whenever you say, because they're busy Houston especially. 712 00:33:29,680 --> 00:33:32,800 Speaker 1: Yes, and I'd love to hear that, so Chad I'm 713 00:33:32,840 --> 00:33:34,280 Speaker 1: up against a break. Thank you for being our guest. 714 00:33:34,320 --> 00:33:37,520 Speaker 1: Thank you for doing on a short notice. Chadnoorville, rigzone 715 00:33:37,680 --> 00:33:40,280 Speaker 1: dot com