WEBVTT Kind: captions Language: en-US 00:00:01.100 --> 00:00:03.280 [Silence] 00:00:03.280 --> 00:00:05.880 Okay. Good morning, everybody, and thank you 00:00:05.890 --> 00:00:14.450 for joining today’s ESC seminar. I see we have currently 34 people on. 00:00:14.450 --> 00:00:18.140 And I think we’ll have a few more as people log on. 00:00:19.240 --> 00:00:25.480 This is – first, I want to remind everybody just to make sure during 00:00:25.480 --> 00:00:30.340 the seminar that your video is off and that you’re muted. 00:00:31.080 --> 00:00:36.300 Just to make sure everything goes smoothly. 00:00:36.300 --> 00:00:40.440 I would like to remind you also that, if you want to – if you need to enter 00:00:40.449 --> 00:00:45.329 full-screen mode, you can actually – in Microsoft Teams, in those three dots 00:00:45.329 --> 00:00:49.760 with more options, you can enter full-screen mode, and that allows you 00:00:49.760 --> 00:00:54.550 to see the slides a little bit larger on your screen. 00:00:54.550 --> 00:00:59.370 Next week’s seminar is next Wednesday, July 8th, at 10:30 a.m., 00:00:59.370 --> 00:01:03.880 and our seminar speaker will be Eileen Martin from Virginia Tech. 00:01:05.940 --> 00:01:11.540 And finally, an announcement about questions for this week’s seminar. 00:01:11.550 --> 00:01:15.550 Unlike usual, we’ll have – Nate will take questions at 00:01:15.550 --> 00:01:19.990 a few points throughout the talk, through the chat window. 00:01:19.990 --> 00:01:25.160 And then we’ll also do questions in the normal, like, moderated format at the 00:01:25.160 --> 00:01:30.420 end, where you can type through chat, or you can unmute yourself. 00:01:30.430 --> 00:01:35.670 But just remember, and keep in mind, that you can ask a couple – 00:01:35.670 --> 00:01:39.450 that you can ask questions through chat at a few points throughout, 00:01:39.450 --> 00:01:42.390 and Nate can answer those questions. 00:01:42.390 --> 00:01:46.590 So that’s all, and at this point, I’ll hand it over to Andy Barbour 00:01:46.590 --> 00:01:49.280 to introduce our speaker. 00:01:49.280 --> 00:01:52.840 - Thanks, Kathryn. Yeah, it’s my distinct pleasure today 00:01:52.840 --> 00:01:56.750 to introduce our speaker, Dr. Nate Lindsey. 00:01:56.750 --> 00:02:03.230 In 2019, just last year, Nate received his Ph.D. in geophysics from UC-Berkeley. 00:02:03.230 --> 00:02:08.050 And now he’s the George Thompson postdoctoral fellow 00:02:08.050 --> 00:02:12.600 in geophysics at Stanford University. 00:02:12.600 --> 00:02:15.500 I’m really excited to have Nate. I think, you know, it’s clear that 00:02:15.500 --> 00:02:19.720 he’s at the fore of a very exciting branch of seismology that uses 00:02:19.730 --> 00:02:22.909 fiber optics for sensing rather than traditional instrumentation. 00:02:22.909 --> 00:02:28.890 So recently, he’s been focused on just what’s called distributed acoustic 00:02:28.890 --> 00:02:34.049 sensing, also known as DAS, in looking at calibration methods 00:02:34.049 --> 00:02:39.040 and how to apply DAS in marine and urban environments. 00:02:39.040 --> 00:02:41.660 So really looking forward to your talk today, Nate. 00:02:41.660 --> 00:02:45.920 And if you’re ready, go ahead. Take it away. 00:02:45.920 --> 00:02:47.480 - Great. 00:02:47.480 --> 00:02:50.000 Thanks, Andy. And, thanks, Kathryn. 00:02:50.000 --> 00:02:53.000 I’m just going to share my screen here. 00:02:55.520 --> 00:03:03.220 [Silence] 00:03:03.220 --> 00:03:09.300 Okay. Hopefully someone can confirm that you can see my screen. 00:03:11.400 --> 00:03:12.800 - Yeah, that’s good. - Yep. 00:03:12.800 --> 00:03:14.640 - Okay, thank you. 00:03:14.640 --> 00:03:17.060 So, yeah, so thank you very much for having me today. 00:03:17.079 --> 00:03:21.700 I’m going to talk about distributed acoustic sensing, a fiber optic 00:03:21.700 --> 00:03:27.140 seismology method – an emerging method of arrayed seismology. 00:03:27.140 --> 00:03:32.029 So this is kind of one image from a DAS. 00:03:32.029 --> 00:03:37.040 So we’re looking at – the X axis is space, so 1 kilometer sampled every 00:03:37.040 --> 00:03:41.780 2 meters of a fiber optic cable laid in a trench in Sacramento, California. 00:03:41.780 --> 00:03:46.320 And I’m showing you just a few minutes of a teleseismic arrival from Alaska. 00:03:46.320 --> 00:03:50.460 Magnitude 7.9 earthquake from 2018. 00:03:50.469 --> 00:03:53.291 And the red star is showing the location of a broadband seismometer – 00:03:53.291 --> 00:03:55.519 the horizontal component in the direction of the fiber. 00:03:55.519 --> 00:04:00.010 And you can see that the arrival of the body waves, and also the 00:04:00.010 --> 00:04:08.510 large surface wave, which has very long-period energy, 00:04:08.510 --> 00:04:13.540 is very clearly recorded coherent across this whole kilometer. 00:04:13.540 --> 00:04:18.400 So this DAS record – I wanted to start out by showing this image because 00:04:18.400 --> 00:04:23.000 I think it motivates this idea that DAS – distributed acoustic sensing – 00:04:23.000 --> 00:04:26.699 a method that’s really come out of the oil and gas industry as a replacement 00:04:26.700 --> 00:04:34.900 for cheap geophones, has incredibly long-period recording potential. 00:04:34.900 --> 00:04:39.759 And this raises a ton of questions about instrument response and how we can 00:04:39.760 --> 00:04:45.500 apply this distributed acoustic sensing method to study Earth science questions. 00:04:45.500 --> 00:04:50.620 So I motivate this by talking about this kind of open question of whether 00:04:50.620 --> 00:04:56.730 we’re talking about something that’s cheap and just 10,000 sensors, 00:04:56.730 --> 00:04:59.930 or if it’s something that we need to kind of consider the – 00:04:59.930 --> 00:05:05.780 as a geodetic tool in addition to being a short-period seismic tool. 00:05:05.780 --> 00:05:09.400 So that’ll be – that’ll be the focus of today’s talk. 00:05:09.400 --> 00:05:15.060 So I think – I kind of got into this by looking at geotechnical applications. 00:05:15.060 --> 00:05:17.200 So here’s that recording from Sacramento. 00:05:17.200 --> 00:05:20.820 We were just looking at a 1-kilometer section in the previous 00:05:20.820 --> 00:05:24.740 plot from this area of the cable. But you can see that, over the 00:05:24.759 --> 00:05:28.690 full 20 kilometers of the cable, we can see bridge resonance. 00:05:28.690 --> 00:05:35.690 We can see cars moving at a mile per hour of 60 to 70 miles per hour. 00:05:35.690 --> 00:05:38.550 You can see surface waves emanating from the vehicles. 00:05:38.550 --> 00:05:42.819 And, in some cases, from this – from this location, you know, 00:05:42.819 --> 00:05:46.909 traveling some – a few kilometers from the location of the source. 00:05:46.909 --> 00:05:49.400 So you can imagine, this is very interesting for dispersion imaging 00:05:49.400 --> 00:05:55.919 and vehicle tracking and all sorts of hydrological studies. 00:05:55.919 --> 00:06:00.370 But I’m also going to be interested today in thinking about what the actual – 00:06:00.370 --> 00:06:04.430 in addition to just velocity information, what the actual amplitude is. 00:06:04.430 --> 00:06:08.120 So this axis over here, the color is actually showing 00:06:08.120 --> 00:06:11.020 the strain rate that we’re recording. 00:06:11.020 --> 00:06:13.460 And the amplitude information of DAS data sets has not been 00:06:13.460 --> 00:06:18.039 used very much to date. And so today’s talk will be 00:06:18.040 --> 00:06:23.300 very focused on the kind of meaning of this color plot in the background. 00:06:25.060 --> 00:06:30.480 So when we think about DAS versus the kind of dirt cheap array that 00:06:30.480 --> 00:06:32.460 I want to talk about, I want to motivate this in terms of 00:06:32.460 --> 00:06:38.460 thinking about – thinking about fiber. So here, single-component array 00:06:38.460 --> 00:06:42.400 shooting laser pulses into the cable and recording seismic wave fields 00:06:42.409 --> 00:06:46.840 along that cable. Against something that has 00:06:46.840 --> 00:06:50.830 kind of been evolving at the same time – this kind of smartphone seismology. 00:06:50.830 --> 00:06:56.970 So my friend and colleague, Qingkai, has been working at Berkeley for the 00:06:56.970 --> 00:07:02.440 last many years looking at smartphone – the ability to use smartphone technology 00:07:02.440 --> 00:07:07.900 to record across the entire globe – you know, tens of thousands, 00:07:07.910 --> 00:07:12.340 even millions, of points to record ground motion. 00:07:12.340 --> 00:07:15.219 But this is a short-period accelerometer, right? 00:07:15.219 --> 00:07:19.620 So there’s a lot of limitations when we start talking about smartphones. 00:07:19.620 --> 00:07:23.380 But I kind of wanted – I wanted to just kind of trace this through the literature. 00:07:23.380 --> 00:07:30.090 We were publishing very similar papers, you know, with major figures that 00:07:30.090 --> 00:07:31.890 showed basically the same information. 00:07:31.890 --> 00:07:37.210 Smartphones recording the move-out of seismic waves from different events. 00:07:37.210 --> 00:07:39.639 Fiber showing the same thing. 00:07:39.640 --> 00:07:45.640 The comparison to other sensors is a good way to kind of do validation 00:07:45.640 --> 00:07:48.620 experiments where you show that what you were using with this 00:07:48.629 --> 00:07:52.340 new emerging tool is actually recording a P and an S wave 00:07:52.340 --> 00:07:55.720 and the codas decaying as expected. 00:07:55.720 --> 00:07:59.229 We can then take it into the lab and put – you know, Qingkai 00:07:59.229 --> 00:08:03.340 was putting a bunch of competing seismometers – cell phones – 00:08:03.340 --> 00:08:08.590 smartphones – on a shake table and basically exciting a ground motion – 00:08:08.590 --> 00:08:13.039 a synthetic ground motion that would be recorded by the instrument and 00:08:13.039 --> 00:08:17.409 then measuring how different sensors compared against one another – 00:08:17.409 --> 00:08:19.080 how they record that ground motion. 00:08:19.080 --> 00:08:22.740 We can do the same thing in the fiber case by stretching the fiber. 00:08:22.740 --> 00:08:26.430 And we’ll look at – look at this case today. 00:08:26.430 --> 00:08:31.060 But when we start talking about the data that’s actually recorded, 00:08:31.060 --> 00:08:34.280 smartphones have kind of a limitation in thinking about 00:08:34.289 --> 00:08:36.120 where this is – where this is coming from. 00:08:36.120 --> 00:08:38.440 So we’re talking about the oil and gas industry, right, so we 00:08:38.440 --> 00:08:41.139 have a deviated well. We have the toe of the – 00:08:41.139 --> 00:08:45.329 kind of horizontal deviated section and the vertical section. 00:08:45.329 --> 00:08:50.060 And this is high-frequency, like what a smartphone could record. 00:08:50.060 --> 00:08:56.180 But the array density of these channels actually allows you to see the P wave 00:08:56.180 --> 00:09:02.000 field and actually the S wave field, and, through the deviated section, actually 00:09:02.000 --> 00:09:07.420 downgoing reflected waves that are actually – as they go up the well, 00:09:07.420 --> 00:09:11.460 actually slowing down. So this kind of reflected energy 00:09:11.460 --> 00:09:15.040 is actually really densely sampled with DAS. 00:09:15.040 --> 00:09:18.040 And I think this is a kind of a breakthrough technology for oil and gas 00:09:18.050 --> 00:09:22.490 because of these kind of images that DAS is developing with the sensors 00:09:22.490 --> 00:09:28.920 that’s inside of the well without any additional electronics downhole. 00:09:30.980 --> 00:09:35.560 So smartphones kind of, again, don’t really have – you know, they 00:09:35.579 --> 00:09:39.330 begin to really be limited when you start talking about long-period energy. 00:09:39.330 --> 00:09:43.950 So whereas, in the oil and gas earthquake case, we – in this case, 00:09:43.950 --> 00:09:47.550 we are up at hundreds of hertz – tens to hundreds of hertz. 00:09:47.550 --> 00:09:53.769 But, in this case, this hydrologic oscillator experiment in a lab 00:09:53.769 --> 00:10:00.300 is modulating the strain of the fiber at a diurnal period. 00:10:00.300 --> 00:10:04.640 And so a smartphone is not going to record that type of long-period motion. 00:10:04.640 --> 00:10:09.430 So, in this case, they took this kind of rotating disc and basically forced the 00:10:09.430 --> 00:10:14.730 fiber strain at this period and then recorded this response in terms of 00:10:14.730 --> 00:10:18.520 a strain or a displacement over the gauge length of the fiber. 00:10:18.520 --> 00:10:24.180 And this kind of response is much larger than what an Earth tide amplitude's 00:10:24.180 --> 00:10:30.730 would be by about 100,000 times the amplitude of the Earth tide. 00:10:30.730 --> 00:10:36.600 But it’s actually – we’ve recorded something similar to this kind of 00:10:36.600 --> 00:10:44.020 hydrological – hydrodynamic kind of signal in the field with this kind of a 00:10:44.030 --> 00:10:50.550 response of a fiber in Monterey Bay. So this is offshore recording where data 00:10:50.550 --> 00:10:55.660 over a few days shows this very strong, long-period response. 00:10:55.660 --> 00:10:58.380 And so, again, smartphones are not going to be able to record 00:10:58.380 --> 00:11:04.279 this type of motion, specifically offshore underneath the water. 00:11:04.279 --> 00:11:09.490 So only – let’s kind of, you know, think just about the fiber now, 00:11:09.490 --> 00:11:11.140 thinking about the DAS. 00:11:11.140 --> 00:11:17.680 What do we actually need to be able to use this new signal in greater detail? 00:11:17.699 --> 00:11:21.440 Well, we need to kind of characterize it as we would a seismometer. 00:11:21.440 --> 00:11:25.110 So a seismometer has a known instrument response function. 00:11:25.110 --> 00:11:27.829 It has precise timing. 00:11:27.829 --> 00:11:33.410 And it has a coupled rigid frame that records the Earth’s ground motion. 00:11:33.410 --> 00:11:38.180 So a lot of these are actually – have been worked out in DAS 00:11:38.180 --> 00:11:42.250 over the last five years. So originally there were timing issues. 00:11:42.250 --> 00:11:44.449 There are – continue to be coupling issues. 00:11:44.449 --> 00:11:48.820 And there’s additional work now looking at the instrument response. 00:11:48.820 --> 00:11:54.199 So we can actually begin to think of DAS more as an actual seismic 00:11:54.199 --> 00:11:59.019 instrument and less as just a detector that records something 00:11:59.020 --> 00:12:02.960 that we don’t really understand what it – what was recorded. 00:12:04.500 --> 00:12:09.380 So this is the kind of theoretical response of DAS. 00:12:09.380 --> 00:12:12.480 And I plotted against other known instrument response functions. 00:12:12.480 --> 00:12:14.670 So the poles and zeroes of an instrument would plot 00:12:14.670 --> 00:12:21.250 on this amplitude and phase diagram as a function of period. 00:12:21.250 --> 00:12:26.370 So a kind of nodal seismometer – maybe a short-period seismometer – 00:12:26.370 --> 00:12:32.339 something like a geophone or even a smartphone would have a response 00:12:32.339 --> 00:12:36.889 at short periods but then fall off at long periods, like I was describing. 00:12:36.889 --> 00:12:39.680 The DAS is flat to very long periods. 00:12:39.680 --> 00:12:44.730 And so this response that I’m going to be talking about today when we think about 00:12:44.730 --> 00:12:51.050 different Earth signals, similar to a broadband seismometer, shown here. 00:12:51.050 --> 00:12:54.360 At short periods, the DAS actually has a notch. 00:12:54.360 --> 00:12:57.519 And this is related to the gauge length of the – 00:12:57.519 --> 00:13:01.670 of which we’re measuring optical phase changes. 00:13:01.670 --> 00:13:03.820 In phase, we’re flat. 00:13:03.820 --> 00:13:08.910 So there should be no delay between different frequencies. 00:13:08.910 --> 00:13:13.290 The kind of signals that I’ll be talking about, in terms of microseism and 00:13:13.290 --> 00:13:16.899 teleseism are plotted here along the X axis just to show the 00:13:16.900 --> 00:13:19.860 kind of bandwidth that we can probe this instrument response 00:13:19.860 --> 00:13:24.160 function with using natural Earth signals. 00:13:25.180 --> 00:13:31.339 So, if you’re interested, you could look up these kind of – you know, there’s 00:13:31.339 --> 00:13:36.070 a group called SEAFOM, which has developed some performance standards. 00:13:36.070 --> 00:13:40.850 And so this is just basically to say that the response function that 00:13:40.850 --> 00:13:46.160 I’ll be talking about ticks the boxes of a number of these characteristics. 00:13:46.160 --> 00:13:49.910 And there’s developing interest in actually standardizing the way that 00:13:49.910 --> 00:13:54.860 DAS instruments are described in terms of these specifications. 00:13:54.860 --> 00:13:57.459 So this SEAFOM group is from the industry. 00:13:57.459 --> 00:14:00.800 And they’re asking different vendors to actually go through and describe, 00:14:00.800 --> 00:14:03.690 you know, what is the self-noise of your instrument and conduct 00:14:03.690 --> 00:14:05.639 a few tests to do that. 00:14:05.639 --> 00:14:09.471 So this has not been done yet, and the instrument response function 00:14:09.471 --> 00:14:13.180 is not handed to us when we do DAS experiments. 00:14:13.180 --> 00:14:17.139 So I think this is really an important step to understanding 00:14:17.140 --> 00:14:19.800 what we’re recording in the field. 00:14:19.800 --> 00:14:24.300 Just to kind of show the potential in this talk what we’ll – what we’d 00:14:24.300 --> 00:14:27.980 be able to look at with our DAS, we have microearthquake recordings 00:14:27.980 --> 00:14:32.319 from the FORGE geothermal site in Utah, which kind of occupies a higher 00:14:32.319 --> 00:14:36.810 frequency range around the range of this notch. 00:14:36.810 --> 00:14:40.639 So there’s the P wave and S wave coming up the well with geophones 00:14:40.640 --> 00:14:44.440 plotted in white and DAS plotted in the image behind. 00:14:44.440 --> 00:14:49.840 We’ll look at teleseismic recordings from this kind of band here. 00:14:49.840 --> 00:14:55.279 And then we’ll also – if there’s interest at the end, we’ll talk about 00:14:55.279 --> 00:14:59.040 kind of thermal strain, which is – or even Earth tides, which are 00:14:59.040 --> 00:15:03.930 occupying a much longer period range – well below 1,000 seconds. 00:15:03.930 --> 00:15:10.240 So here I’m showing DAS from a – from a well in Vancouver, 00:15:10.240 --> 00:15:16.779 British Columbia, which is showing a trend that has a diurnal signal. 00:15:16.779 --> 00:15:22.230 And the amplitude of the signal is actually too high to be the Earth tide. 00:15:22.230 --> 00:15:26.470 So the actual response is due to thermal strain, which needs to 00:15:26.470 --> 00:15:30.220 be removed before we actually can see the Earth tide. 00:15:30.220 --> 00:15:33.800 And so the interest in looking at this would be to actually be able to record 00:15:33.800 --> 00:15:40.110 a vertical record – or an array of Earth tide would be very – of the 00:15:40.110 --> 00:15:43.480 kind of solid Earth tidal deformation would be interesting. 00:15:43.480 --> 00:15:46.480 But this thermal strain creates an issue. 00:15:48.140 --> 00:15:52.420 So I’ll talk a little bit – this is kind of our outline for today. 00:15:52.420 --> 00:15:56.000 I’ll describe the kind of – what is DAS actually measuring. 00:15:56.009 --> 00:16:00.069 And then show some laboratory calibrations where we attempted 00:16:00.069 --> 00:16:04.199 to measure the instrument response in a very controlled setting. 00:16:04.199 --> 00:16:07.459 And then I’ll think about the kind of instrument response 00:16:07.460 --> 00:16:09.040 through three applications. 00:16:09.040 --> 00:16:15.460 So, first, we’ll look at field calibration where we took a Güralp sensor – 00:16:15.460 --> 00:16:18.879 CMG-3T broadband seismometer to Sacramento, California, 00:16:18.880 --> 00:16:23.000 and deployed it on a telecom line, recording teleseisms. 00:16:23.000 --> 00:16:26.840 And then, in the FORGE well, looking at microseisms against geophones, 00:16:26.850 --> 00:16:31.339 where we have a 12-level, three-component geophone array 00:16:31.339 --> 00:16:35.579 buried at depth – very nice array deployed by Schlumberger, 00:16:35.579 --> 00:16:38.709 and we’ll compare that to the DAS. 00:16:38.709 --> 00:16:43.100 And then, in the third case, we have a submarine fiber, which unfortunately, 00:16:43.100 --> 00:16:45.510 there was no sensor deployed with the cable. 00:16:45.510 --> 00:16:50.279 But there’s a seismometer on shore – the San Andreas Fault Observatory 00:16:50.279 --> 00:16:53.660 station near Monterey. So we can compare microseism 00:16:53.660 --> 00:16:58.069 observations between the seismometer and the cable to understand what the 00:16:58.069 --> 00:17:02.920 cable is actually recording under the water – or, at least, begin to do that. 00:17:03.980 --> 00:17:08.220 So, to begin, DAS – I kind of described this at the very start. 00:17:08.230 --> 00:17:13.650 DAS is sending laser pulses into a cable and recording the back-scattered light. 00:17:13.650 --> 00:17:16.559 So it does this through the property of Rayleigh scattering. 00:17:16.559 --> 00:17:21.130 So, silica glass has imperfections in its index of refraction. 00:17:21.130 --> 00:17:25.560 And that leads to scattered light whenever you send in a pulse of 00:17:25.560 --> 00:17:30.860 photons. And the two-way travel time of out from the instrument – 00:17:30.860 --> 00:17:38.900 called the interrogator – to this point and back is traveling at a known speed 00:17:38.900 --> 00:17:42.250 in the silica glass based on its index of refraction. 00:17:42.250 --> 00:17:45.360 And so this allows us to do a time-for-distance transform, 00:17:45.360 --> 00:17:49.200 where we send in a pulse of light, record the backscattered energy, 00:17:49.200 --> 00:17:52.870 and that backscattered profile in time can be linked to the changes 00:17:52.870 --> 00:17:55.820 in scattering throughout the fiber. 00:17:55.820 --> 00:18:01.130 So, in a little bit, you know, simple description, this is the kind of shorthand. 00:18:01.130 --> 00:18:04.220 We’re looking at changing any sort of single-mode fiber – 00:18:04.220 --> 00:18:07.530 that’s like the telecom arrays or fiber you deploy yourself – 00:18:07.530 --> 00:18:11.880 into a single-component array of strain rate sensors. 00:18:11.880 --> 00:18:16.000 So this is the kind of principle at which fiber optics operates – 00:18:16.000 --> 00:18:20.460 total internal reflection. So the kind of wave guide of light 00:18:20.460 --> 00:18:26.170 that you’re seeing here is traveling because there’s a difference in index 00:18:26.170 --> 00:18:29.330 of refraction between this piece of plastic and the air surrounding it. 00:18:29.330 --> 00:18:34.720 So that’s allowing the light to be guided down this piece of plastic. 00:18:34.720 --> 00:18:37.980 And there’s scattering at this point, which is scattering some of that 00:18:37.980 --> 00:18:41.880 photonic energy back into the camera lens, right? 00:18:41.880 --> 00:18:45.490 So some of that energy is traveling out in the [inaudible] and never 00:18:45.490 --> 00:18:49.140 returns to the detector, in the case of the fiber optic. 00:18:49.140 --> 00:18:52.640 But some of it does return back to the source. 00:18:52.640 --> 00:18:56.880 And so that’s that two-way travel time I’m talking about. 00:18:56.880 --> 00:18:59.020 So we can actually account for how much energy – 00:18:59.020 --> 00:19:03.880 how many scatterers there are. Just due to natural properties 00:19:03.890 --> 00:19:07.890 of silica glass and variation in that refractive index. 00:19:07.890 --> 00:19:12.350 So if you – if you do this kind of calculation based on known scattering 00:19:12.350 --> 00:19:16.890 principles of Rayleigh scattering inside of telecom and the amount of energy 00:19:16.890 --> 00:19:20.980 that we send into the cable per pulse of light, we find 00:19:20.980 --> 00:19:23.590 there’s around 1,000 scatterers per meter. 00:19:23.590 --> 00:19:27.580 So this is – I kind of worked this out just to say that we’re not adding anything 00:19:27.580 --> 00:19:34.420 to the fiber itself. We’re just using the native scattering profile of the cable. 00:19:35.420 --> 00:19:39.400 And that kind of provides us with a scattering profile. 00:19:41.560 --> 00:19:47.600 So the pulse that we send in provides an electromagnetic wave. 00:19:47.600 --> 00:19:53.510 So we’re going to do optical interferometry on a reference phase 00:19:53.510 --> 00:19:56.780 and the light that comes back from the cable. 00:19:56.780 --> 00:20:02.820 And that provides a phase measurement, which we can use to look at strain. 00:20:02.820 --> 00:20:07.159 So the phase – the kind of phase or change in phase that we measure 00:20:07.159 --> 00:20:10.850 is directly proportional to strain because we’re using laser light. 00:20:10.850 --> 00:20:14.180 So laser light has a known relationship between its distance 00:20:14.180 --> 00:20:18.440 traveled and its optical phase. And that provides – so we can 00:20:18.440 --> 00:20:23.480 measure some change in phase between the reference light 00:20:23.490 --> 00:20:26.940 returning from a position in the cable, and that tells us how this – 00:20:26.940 --> 00:20:31.000 how the cable has strained if we do that through time. 00:20:32.700 --> 00:20:38.400 So some basic parameters about how DAS is typically run. 00:20:38.400 --> 00:20:43.799 The gauge length – the length of the cable that we’re sampling with our 00:20:43.799 --> 00:20:48.650 strain, we’re looking at changes in displacement over about 10 meters. 00:20:48.650 --> 00:20:52.970 And, after about 30 kilometers, we typically run out of light. 00:20:52.970 --> 00:20:58.290 And there’s kind of newer ways to push this number out to maybe 90 kilometers. 00:20:58.290 --> 00:21:02.441 But we eventually will run into an issue because we’re 00:21:02.441 --> 00:21:05.260 using the backscattered energy. 00:21:05.260 --> 00:21:09.100 So we’re going to sample the cable at thousands of times per second and then 00:21:09.100 --> 00:21:13.929 digitize that at a seismic sampling rate. And this kind of operation means that 00:21:13.929 --> 00:21:20.840 we’re going to record tens – onward of 1 to 10 terabytes per day, 00:21:20.840 --> 00:21:24.580 depending on what your sampling choice is in space and time. 00:21:28.100 --> 00:21:30.800 So I’m going to kind of skip through this next section. 00:21:30.809 --> 00:21:35.620 But the point of kind of drawing this diagram and linking it 00:21:35.620 --> 00:21:38.740 to this equation is that we can strain – 00:21:38.740 --> 00:21:41.500 so the actual measurement that we’re making is strain. 00:21:41.500 --> 00:21:45.480 And when you compare that to what a geophone records as 00:21:45.480 --> 00:21:49.970 a kind of displacement or velocity, that would be the strain – 00:21:49.970 --> 00:21:53.659 the actual measurement that we make – strain – would be, like, a 00:21:53.660 --> 00:21:59.160 difference of two geophones differenced in time separated by the gauge length. 00:22:00.820 --> 00:22:05.510 So that has implications – you know, just like any implications that are, 00:22:05.510 --> 00:22:08.779 you know, almost a century old thinking about what strain meters 00:22:08.780 --> 00:22:12.780 are recording versus what inertial sensors record. 00:22:12.780 --> 00:22:16.640 And I put this up kind of just to describe that the particle motion is very different. 00:22:16.640 --> 00:22:20.560 It has this kind of cosine-squared falloff instead of cosine – 00:22:20.560 --> 00:22:24.940 instead of cosine for longitudinal P waves, for example. 00:22:24.940 --> 00:22:29.529 And it also has polarity differences for different quadrants, which is kind of 00:22:29.529 --> 00:22:34.679 hydraulic fracture experiment recording showing the P wave and S wave. 00:22:34.679 --> 00:22:39.830 I put this image up here just to kind of show that the polarity differences that 00:22:39.830 --> 00:22:44.809 were kind of proven in theory are actually beginning to be seen with these 00:22:44.809 --> 00:22:48.020 kind of very close near-field recordings. 00:22:48.020 --> 00:22:51.520 So that’s kind of a very nice a test of the theory. 00:22:53.780 --> 00:22:56.480 And there’s also important implications about the fact that 00:22:56.480 --> 00:23:00.300 we’re doing optical interferometry. So we have fading, right? 00:23:00.300 --> 00:23:03.640 Wherever there’s destruction interference in our optical 00:23:03.640 --> 00:23:08.820 interferometry phase measurement, we don’t record as strong – 00:23:08.830 --> 00:23:11.400 we basically record zero at that location. 00:23:11.400 --> 00:23:15.179 There’s no way to retrieve the actual strain at that location. 00:23:15.179 --> 00:23:19.870 And so DAS arrays will have these kind of faded locations, which are 00:23:19.870 --> 00:23:24.090 just related to the kind of random photonic phase difference that is 00:23:24.090 --> 00:23:30.160 measured between the experimental phase and the reference phase. 00:23:33.000 --> 00:23:37.940 Coupling is also very important. But I’ll just kind of leave that as a – 00:23:37.940 --> 00:23:41.289 as a very important statement for future talks. 00:23:41.289 --> 00:23:46.309 I think there’s beginning to be interesting results where coupling 00:23:46.309 --> 00:23:51.540 conditions are being compared between trenched-in cables and conduit cables, 00:23:51.540 --> 00:23:54.540 for example. Here’s showing an earthquake from The Geysers 00:23:54.549 --> 00:23:59.100 in Sacramento. You can see the surface wave energy – the kind of 00:23:59.100 --> 00:24:02.120 longer-period surface wave energy is a little bit gained up by just 00:24:02.120 --> 00:24:08.240 additionally burying the conduit and cables in an additional conduit. 00:24:08.240 --> 00:24:13.850 So just that – this change from here to here gains up this kind of surface wave. 00:24:13.850 --> 00:24:19.659 So understanding these differences in a – kind of a bottom-up principle 00:24:19.659 --> 00:24:22.690 of understanding, maybe in a finite element method, 00:24:22.690 --> 00:24:26.299 how the addition of a conduit could lead to differences 00:24:26.300 --> 00:24:30.299 in instrument response will be important going forward. 00:24:32.440 --> 00:24:38.040 So, at this point, I just kind of break and say – ask if there are any questions. 00:24:38.040 --> 00:24:42.180 I know I kind of whizzed through a lot of the details of the experiment – 00:24:42.180 --> 00:24:46.280 or, sorry, of the instrument. And before I talk about 00:24:46.280 --> 00:24:50.220 the experiments, are there any questions that anyone has? 00:24:52.960 --> 00:24:56.160 [Silence] 00:24:56.160 --> 00:24:58.520 - Yeah. Hi, Nate. This is Steve Hickman. 00:24:58.529 --> 00:25:01.070 You mentioned that the – it looked like the coupling was better in a conduit 00:25:01.070 --> 00:25:04.029 than buried directly in the ground. Is the conduit – that was a bit surprising. 00:25:04.029 --> 00:25:07.539 Is the conduit actually filled with some kind of other material 00:25:07.539 --> 00:25:10.690 to couple the fibers to the conduit itself? 00:25:10.690 --> 00:25:16.659 - So these conduits are typically packed over time with additional cable. 00:25:16.660 --> 00:25:24.099 And so there can be quite a tight coupling inside of the conduit. 00:25:25.120 --> 00:25:27.180 - Okay, thanks. 00:25:29.760 --> 00:25:32.940 [Silence] 00:25:32.940 --> 00:25:38.160 - I have a really basic question about how the interrogators work. 00:25:38.169 --> 00:25:40.370 - Yeah. - So your observations are 00:25:40.370 --> 00:25:46.120 effectively the reflection from each scatterer that you’re seeing. 00:25:46.120 --> 00:25:50.350 So somehow the interrogator is disentangling all of these? 00:25:50.350 --> 00:25:53.590 Is that right? And is it making some assumption that you have just 00:25:53.590 --> 00:25:58.780 a straight path that’s a reflection? Or how does that work? 00:25:58.780 --> 00:26:02.210 - Yeah. There’s an assumption of a – of a two-way travel time out and 00:26:02.210 --> 00:26:05.900 back from the interrogator unit to the scattering location. 00:26:05.900 --> 00:26:09.039 And then there’s a spatial averaging of this gauge length of 10 meters. 00:26:09.039 --> 00:26:12.020 So it’s not that we’re just looking at one scattering point. 00:26:12.020 --> 00:26:15.990 It’s that we’re looking at the average – the average time 00:26:15.990 --> 00:26:19.480 out and back to a 10-meter section in the cable. 00:26:21.210 --> 00:26:24.600 And that’s done by basically sampling – after you send in a pulse, you’re going 00:26:24.610 --> 00:26:28.350 to sample in time, and that sampling in time is going to look deeper 00:26:28.350 --> 00:26:31.350 and deeper into the fiber. And because we know the 00:26:31.350 --> 00:26:35.570 speed of light in silica glass, we can – we can know exactly 00:26:35.570 --> 00:26:39.320 where we are on the cable under those assumptions. 00:26:41.300 --> 00:26:44.660 Good question, though. I’m going to talk next about the 00:26:44.669 --> 00:26:50.980 instrument calibrated in the lab. So that might add some information – 00:26:50.980 --> 00:26:55.710 kind of an additional layer of information about what we’re recording. 00:26:55.710 --> 00:26:58.900 So working with the student Aleksei Titov, who is now at 00:26:58.900 --> 00:27:03.200 Colorado School of Mines, we were kind of interested in testing 00:27:03.200 --> 00:27:10.480 this Silixa iDAS v2, which is a highly – widely used, now, 00:27:10.480 --> 00:27:16.860 DAS in kind of oil and gas and also in academic areas to record earthquakes 00:27:16.860 --> 00:27:22.559 and look at geotechnical [inaudible]. So what we do is, we hooked a – 00:27:22.559 --> 00:27:30.679 kind of a 1-gauge 11-meter section of fiber in a thermally insulated pipe. 00:27:30.679 --> 00:27:36.019 And then we drove with that a little mechanical slide that could make 00:27:36.019 --> 00:27:40.299 very small steps in displacement. And, by measuring the strain – 00:27:40.299 --> 00:27:45.330 or the strain rate, actually, over the one gauge, we could then 00:27:45.330 --> 00:27:49.580 kind of drive this at a known strain and measure what we recorded. 00:27:50.940 --> 00:27:54.019 So I’m just going to kind of list out the different results here. 00:27:54.019 --> 00:27:56.760 And Aleksei is working on a publication now, which would be one of the first 00:27:56.760 --> 00:28:02.570 publications of this kind of information about this particular iDAS. 00:28:02.570 --> 00:28:05.480 So the – we kind of recorded over multiple hours. 00:28:05.480 --> 00:28:09.409 You can actually see that there’s a trend. There’s a drift in the – 00:28:09.409 --> 00:28:14.140 in the optical phase measurement. So the strain measurement. 00:28:14.140 --> 00:28:19.000 And that might be related to temperature trends, 00:28:19.010 --> 00:28:22.370 but it could also be internal to the optics chain that’s actually 00:28:22.370 --> 00:28:25.640 maybe some sort of laser drift, for example. 00:28:26.760 --> 00:28:30.559 The response function – the amplitude response function, 00:28:30.559 --> 00:28:35.549 by driving this at increasingly longer periods, we could see what 00:28:35.549 --> 00:28:40.390 the kind of recovered DAS strain was. And we saw that, over this whole 00:28:40.390 --> 00:28:45.919 broadband – three decades of signal period here, that there 00:28:45.919 --> 00:28:50.250 was a relatively flat amplitude function here. 00:28:50.250 --> 00:28:57.460 And that there is a slight reduction from a perfect 1 value to about 0.8, 00:28:57.460 --> 00:29:01.520 and that could be related to coupling, the way that this is actually clamped, 00:29:01.520 --> 00:29:05.779 or the fact that it’s being driven on this side and actually fixed on the far side. 00:29:05.779 --> 00:29:08.700 So the way that coupling is actually operating, even in this 00:29:08.700 --> 00:29:12.010 very controlled lab setting, is not perfect. 00:29:12.010 --> 00:29:15.660 And so that might be related to why we see this difference. 00:29:17.260 --> 00:29:23.060 This spatial resolution – so I’m talking here about kind of a one-gauge average, 00:29:23.060 --> 00:29:28.200 right, so we have this kind of strain across a 10-meter section. 00:29:28.200 --> 00:29:30.960 So at what point could you actually measure two separate 00:29:30.960 --> 00:29:35.600 signals next to each other? And if you kind of think about that, 00:29:35.600 --> 00:29:39.880 that’s exactly 2 times the gauge length plus one channel – so one additional 00:29:39.880 --> 00:29:44.760 measurement will allow you separate two different signals in space. 00:29:44.760 --> 00:29:46.990 We can – we can hook up a different instrument to 00:29:46.990 --> 00:29:51.269 another fiber in the same cable. And this instrument is 00:29:51.269 --> 00:29:54.890 a Brillouin sensing method. So, whereas the DAS is measuring 00:29:54.890 --> 00:29:59.240 Rayleigh scattering, the Brillouin instrument is measuring the actual 00:29:59.240 --> 00:30:03.960 Brillouin scattering pattern, which is a nonlinear optics chain that’s sensitive 00:30:03.960 --> 00:30:07.110 to strain and temperature – the absolute strain, in fact. 00:30:07.110 --> 00:30:10.870 And it can make much finer samplings with gauges on the order of millimeters. 00:30:10.870 --> 00:30:15.940 So, with the Luna Brillouin method, we make this kind of measurement of 00:30:15.940 --> 00:30:21.270 very fine sampling of absolute strain. And the issue with this instrument is it’s 00:30:21.270 --> 00:30:26.600 very slow to make these measurements. So you have to average over multiple 00:30:26.600 --> 00:30:31.070 seconds to get any one measurement. So, whereas, the DAS can do 00:30:31.070 --> 00:30:34.200 seismology, for example, the Luna instrument cannot. 00:30:34.200 --> 00:30:37.049 And it’s also very limited in its length over which you can 00:30:37.049 --> 00:30:40.409 make these measurements over only a few tens of meters, 00:30:40.409 --> 00:30:45.549 whereas, the DAS can – the iDAS can do tens of kilometers. 00:30:45.549 --> 00:30:50.520 But the kind of absolute measurement is compared to the Silixa DAS here 00:30:50.520 --> 00:30:54.220 in this plot. And you can see that the DAS signal is this purple line – 00:30:54.220 --> 00:31:01.049 kind of a spatially averaged view of this step function – this kind of hat function. 00:31:01.049 --> 00:31:07.680 And so we can actually do that by kind of convolving the gauge – the kind of 00:31:07.680 --> 00:31:13.320 [inaudible] of the gauge 10-meter filter over this – over this signal 00:31:13.320 --> 00:31:16.620 provides the kind of similar-type signal as 00:31:16.620 --> 00:31:20.840 what’s being recorded with the Luna instrument. 00:31:20.840 --> 00:31:25.570 So we also see a thermal strain effect where we – when we put a piece of 00:31:25.570 --> 00:31:29.800 the fiber into a temperature bath – so we take it out of this pipe, and we 00:31:29.800 --> 00:31:33.909 put it into a regulated bath, and we can actually see that, 00:31:33.909 --> 00:31:38.340 as the temperature went down, the strain of the cable decreased, and we can 00:31:38.340 --> 00:31:45.300 measure exactly what that coefficient of thermal strain is for this particular fiber. 00:31:46.860 --> 00:31:50.960 A very interesting point was this kind of issue of dynamic range, 00:31:50.960 --> 00:31:55.500 which has not been explored. I haven’t seen any description of it. 00:31:55.500 --> 00:31:59.960 And so the interesting thing here is, if you – if you strain the cable faster 00:31:59.970 --> 00:32:06.820 and faster, the – so the actual change in strain here per time is becoming faster 00:32:06.820 --> 00:32:09.700 as you go to later and later experiments. 00:32:09.700 --> 00:32:13.610 Each one of these kind of cycles is one experiment. 00:32:13.610 --> 00:32:17.950 We make the strain faster, and then we make the strain faster here. 00:32:17.950 --> 00:32:22.419 So the difference in color – you can see that, when we sample the cable 00:32:22.420 --> 00:32:28.540 very fast with laser pulses 10,000 times per second – so we’re doing kind of 00:32:28.540 --> 00:32:34.100 pulsed experiments 10,000 times per second, we capture this full – 00:32:34.100 --> 00:32:38.440 the full range of possible strain rates. 00:32:38.440 --> 00:32:41.889 When we slow down the rate at which we’re pulsing this, the amount 00:32:41.889 --> 00:32:48.039 of strain per time step of the optical interferometer is 00:32:48.039 --> 00:32:51.029 becoming less and less and less. And you can see that, for the 00:32:51.029 --> 00:32:55.200 lower strains – I’m sorry, for the lower pulse rates, 00:32:55.200 --> 00:32:59.260 we actually don’t capture the very fastest strains. 00:32:59.260 --> 00:33:01.880 So this is kind of an interesting point. 00:33:01.880 --> 00:33:05.760 And you can imagine that this is related to … 00:33:09.400 --> 00:33:12.480 This is related to this issue. So dynamic range comes into play 00:33:12.480 --> 00:33:18.679 when you want to record high-frequency signals out at very long lengths. 00:33:18.680 --> 00:33:23.180 So I said that, if you’re sampling at 10,000 samples per second, 00:33:23.180 --> 00:33:26.540 each time you send in pulses, you have to wait for all the energy 00:33:26.549 --> 00:33:28.980 to come back before you send in another pulse. 00:33:28.980 --> 00:33:32.510 So, over very long cables, that’s not possible. 00:33:32.510 --> 00:33:35.510 So that means that, over very long cables, 00:33:35.510 --> 00:33:40.320 measuring high-frequency signals, like from whales, is not possible, 00:33:40.320 --> 00:33:43.570 at least in the present way that DAS is being done. 00:33:43.570 --> 00:33:47.760 So this shows that the kind of laser frequency, the pulse – 00:33:47.760 --> 00:33:52.570 the pulse rate versus the fiber length – total fiber length. 00:33:52.570 --> 00:33:56.870 And there’s this kind of maximum sampling frequency limit here 00:33:56.870 --> 00:34:02.400 to keep one pulse in the fiber. And for a chosen fiber length, 00:34:02.400 --> 00:34:05.320 you have this kind of limit of where you can actually – 00:34:05.320 --> 00:34:09.020 what type of signals you can actually record with your cable. 00:34:11.320 --> 00:34:14.740 So does anyone have any questions at this point? 00:34:17.260 --> 00:34:22.380 [Silence] 00:34:22.380 --> 00:34:26.260 If not, I’ll just move – I’ll just keep going, then. 00:34:26.290 --> 00:34:32.420 I think the kind of instrument details of this are really kind of fascinating 00:34:32.430 --> 00:34:36.090 in terms of an instrument geek, but the kind of field calibration, 00:34:36.090 --> 00:34:39.690 or what people want to see, I think it’s really important to 00:34:39.690 --> 00:34:42.880 kind of lay out the differences between inertia seismometers and 00:34:42.880 --> 00:34:47.050 DAS to kind of be able to actually properly interpret what we’re 00:34:47.050 --> 00:34:49.250 seeing with these new DAS arrays. 00:34:49.250 --> 00:34:53.560 So that’s the reason for such belabored points in the previous part of my talk. 00:34:53.560 --> 00:34:58.040 But this next experiment from Sacramento, we connected the iDAS 00:34:58.040 --> 00:35:02.380 that we were testing in the field to a cable buried by a telecommunication 00:35:02.380 --> 00:35:07.000 company in Sacramento, California, and deployed a seismometer like 00:35:07.000 --> 00:35:10.330 we showed data from at the beginning of this talk. 00:35:10.330 --> 00:35:12.911 So the three components of the broadband Güralp sensor 00:35:12.911 --> 00:35:16.010 are deployed here. We can rotate mathematically 00:35:16.010 --> 00:35:19.190 into the direction of the cable and extract the horizontal component 00:35:19.190 --> 00:35:21.970 that’s aligned with the cable. 00:35:21.970 --> 00:35:28.200 The teleseisms recordings are shown here – gray being seismometer velocity 00:35:28.200 --> 00:35:34.310 and DAS strain – so integrated from strain rate to strain – shown in black. 00:35:34.310 --> 00:35:37.980 You can see major body wave arrivals and also the surface waves, for example, 00:35:37.980 --> 00:35:40.980 from that Alaska event that I was showing before. 00:35:40.980 --> 00:35:43.200 Just extracting one trace from the DAS. 00:35:43.200 --> 00:35:47.180 So you have this type of side-by-side comparison. 00:35:47.180 --> 00:35:52.140 So the kind of issue here is that DAS is recording strain, 00:35:52.140 --> 00:35:55.830 whereas the inertial sensor is recording a particle velocity. 00:35:55.830 --> 00:36:02.240 And these quantities of velocity and strain are linked by the phase velocity. 00:36:02.240 --> 00:36:07.160 In this kind of array recording, where we have evenly sampled 00:36:07.160 --> 00:36:10.800 measurements in time and in space – so we measure every 2 meters 00:36:10.810 --> 00:36:15.600 in the spatial direction, we get – we actually capture the wave number 00:36:15.600 --> 00:36:21.330 information, which is typically not captured by a single-point recording. 00:36:21.330 --> 00:36:23.690 We capture the frequency content, of course, but we also capture 00:36:23.690 --> 00:36:26.300 that wave number information. And this means that we can 00:36:26.300 --> 00:36:28.760 do a 2D Fourier transform on this image. 00:36:28.760 --> 00:36:31.830 So, in addition to just doing it in time, we can also do it in – 00:36:31.830 --> 00:36:34.760 we can also capture the spatial frequencies. 00:36:34.760 --> 00:36:38.180 And then we can multiply by the coefficients of frequency and divide 00:36:38.180 --> 00:36:42.970 by the coefficients of wave number to essentially rescale our DAS data 00:36:42.970 --> 00:36:45.500 into units of equivalent particle velocity. 00:36:45.500 --> 00:36:47.780 And this allows a direct comparison between 00:36:47.780 --> 00:36:52.700 DAS recorded data and seismometer recorded data. 00:36:52.700 --> 00:36:54.260 That’s what I’m showing here. 00:36:54.260 --> 00:36:58.720 So these are DAS-equivalent velocity and Güralp velocity. 00:36:58.720 --> 00:37:03.270 So here’s, again, the major body waves, and then this large surface wave 00:37:03.270 --> 00:37:06.190 with an Airy phase. And you can see the scattering 00:37:06.190 --> 00:37:10.740 has a different amplitude between the DAS and the Güralp sensor. 00:37:10.740 --> 00:37:17.040 The major conclusion here is that these are incredibly similar, but the actual – 00:37:17.040 --> 00:37:20.510 still, the difference here is that, while they’re recording the same 00:37:20.510 --> 00:37:23.410 ground motion, if we were to assume that the Güralp is recording 00:37:23.410 --> 00:37:28.920 true ground motion, shown here after removing the instrument response, 00:37:28.920 --> 00:37:32.820 the DAS is recording that same ground motion but convolved with 00:37:32.820 --> 00:37:37.500 its unknown instrument response. So we can do the comparison, 00:37:37.500 --> 00:37:41.190 or essentially a deconvolution, assuming that the ground velocity 00:37:41.190 --> 00:37:44.670 in red here was measured by the seismometer after instrument response. 00:37:44.670 --> 00:37:48.650 That’s the – that’s the way that the ground moved is the red curve. 00:37:48.650 --> 00:37:53.330 And the DAS has this additional component if its response function. 00:37:53.330 --> 00:37:57.100 So doing this deconvolution, we resolve kind of a response 00:37:57.100 --> 00:38:01.340 function shown here in blue in terms of amplitude and phase response. 00:38:01.340 --> 00:38:04.580 And you can see that this kind of is flat at longer periods between 00:38:04.580 --> 00:38:10.240 10 and 100 seconds and ticks up between 1 and 10 seconds. 00:38:10.240 --> 00:38:14.250 The DAS response in phase is rather flat. 00:38:14.250 --> 00:38:18.060 And so, over this whole range, we can assume that different – 00:38:18.060 --> 00:38:21.530 that the phase response can be kind of evenly considered to 00:38:21.530 --> 00:38:26.050 not have to do with whatever is affecting the amplitude. 00:38:26.050 --> 00:38:29.470 So this is really confident-building. You could do kind of long-period 00:38:29.470 --> 00:38:35.530 surface wave dispersion at periods between 10 and 100 seconds without 00:38:35.530 --> 00:38:38.320 kind of worrying about instrument response functions 00:38:38.320 --> 00:38:42.200 in this case at Sacramento. This might be very different 00:38:42.200 --> 00:38:45.960 in a different experiment or a different fiber. 00:38:47.940 --> 00:38:52.740 So we can do a similar comparison with microseisms, but I’ll just kind of 00:38:52.740 --> 00:38:56.780 glance through to the result to show that, for a range of teleseisms, 00:38:56.780 --> 00:38:59.540 and also microseisms, the response function has 00:38:59.540 --> 00:39:02.480 the same shape that I was showing from Alaska. 00:39:02.480 --> 00:39:08.200 It looks elevated at short periods and flat at longer periods. 00:39:08.200 --> 00:39:11.110 And, again, the phase response looks flat. 00:39:11.110 --> 00:39:15.240 So what this means is that, with a couple of recordings of teleseism 00:39:15.240 --> 00:39:19.550 with one sensor deployed on a DAS, we have essentially calibrated that 00:39:19.550 --> 00:39:23.630 experiment – that particular DAS array with that DAS instrument. 00:39:23.630 --> 00:39:29.550 And what that allows us to do is correct recordings down to a line that allows us 00:39:29.550 --> 00:39:35.560 to make measurements of DAS peak ground velocities or DAS amplitudes 00:39:35.560 --> 00:39:41.380 in this seismic band and compare those directly to true ground motions. 00:39:41.380 --> 00:39:45.330 So this kind of calibration exercise could be deployed at other DAS arrays 00:39:45.330 --> 00:39:48.780 to then calibrate those arrays in addition to kind of just 00:39:48.780 --> 00:39:53.460 understanding the kind of response – the elevated response here. 00:39:53.460 --> 00:39:57.220 So maybe I don’t care what my response function actually looks like. 00:39:57.220 --> 00:39:59.980 I just want to remove it. 00:39:59.980 --> 00:40:04.530 It’s kind of separate from the – from the point of what is actually causing this. 00:40:04.530 --> 00:40:08.860 And my hypothesis for what’s causing this is that changing coupling. 00:40:08.860 --> 00:40:12.080 So the addition of conduits is actually leading to enhanced 00:40:12.080 --> 00:40:17.240 ground motion in this band. That’s my hypothesis at this point. 00:40:19.690 --> 00:40:25.500 So the kind of next experiment is from the FORGE well in Utah. 00:40:25.500 --> 00:40:32.820 So this is a enhanced geothermal well deployed for monitoring a stimulation. 00:40:32.820 --> 00:40:39.200 So here’s the kind of granite top and elevated heat therm – heat 00:40:39.210 --> 00:40:47.320 temperature contours shown here. So, in this well, 58-32, there is kind of 00:40:47.320 --> 00:40:51.940 a deployment of a DAS array and also geophone – sorry, 00:40:51.940 --> 00:40:55.390 in 78-32 is the deployment of the DAS array and geophones. 00:40:55.390 --> 00:40:58.960 And then there was stimulation in this well. 00:41:00.180 --> 00:41:04.340 So the interesting thing here was that the actual – the DAS recorded 00:41:04.340 --> 00:41:09.180 about an order of magnitude fewer events than the geophone string. 00:41:09.180 --> 00:41:15.890 And so the DAS community was kind of quite – currently wondering 00:41:15.890 --> 00:41:21.140 why this is – why this is the case. So why the geophone array was 00:41:21.140 --> 00:41:24.700 able to record so many more events. 00:41:24.700 --> 00:41:28.670 And we did point out that there was a nodal surface array which recorded only 00:41:28.670 --> 00:41:33.510 five events, whereas the DAS recorded approximately 40 events. 00:41:33.510 --> 00:41:36.120 But the point still remains that, if you’re going to dig a hole, 00:41:36.120 --> 00:41:41.770 you should probably deploy geophones, after this result – not DAS. 00:41:41.770 --> 00:41:45.790 So why was that? 00:41:45.790 --> 00:41:49.440 So this DAS is actually – while one of the better instruments – 00:41:49.440 --> 00:41:54.330 this is the Carina box, which is actually using the kind of next generation, 00:41:54.330 --> 00:41:58.860 as described by the vendor, optics chain. We don’t really have details about 00:41:58.860 --> 00:42:03.010 what that means. And it’s also engineering the cable to increase 00:42:03.010 --> 00:42:07.860 this profile as a function of distance so that we get more light back. So that 00:42:07.860 --> 00:42:15.370 should enhance the signal-to-noise ratio of the DAS data to typical fiber. 00:42:15.370 --> 00:42:18.900 So the distance between the two wells is about 400 meters. 00:42:18.900 --> 00:42:21.630 And shown here, there’s the granite top. 00:42:21.630 --> 00:42:27.360 The geophones cover the bottom of the well through this granite. 00:42:28.000 --> 00:42:33.760 So the geophones kind of Gutenberg- Richter relationship is shown here for 00:42:33.760 --> 00:42:37.200 the – from the number of events that were recorded at small magnitudes. 00:42:37.200 --> 00:42:42.800 And you can see the DAS kind of falls off in blue here around minus 1.5. 00:42:42.800 --> 00:42:47.040 So this kind of shows that the geophones outperform the DAS by 00:42:47.040 --> 00:42:52.800 approximately a quarter of a magnitude in terms of this local magnitude scaling. 00:42:52.800 --> 00:42:57.370 But there do kind of fall along the line of 1-to-1, approximately. 00:42:57.370 --> 00:43:00.420 So the elevated b values throughout. 00:43:02.140 --> 00:43:07.180 We actually directly related the DAS strain to magnitude using 00:43:07.180 --> 00:43:11.640 this relationship – using the S-minus-P time for the distance 00:43:11.640 --> 00:43:16.180 and a gauge length of 10 meters here to convert from strain to displacement. 00:43:16.180 --> 00:43:20.300 So that allows us to do this vast magnitude estimation. 00:43:21.970 --> 00:43:26.440 My colleague Ariel Lellouch has kind of deployed this in a couple 00:43:26.440 --> 00:43:31.120 of cases where he’s taken the kind of move-out information – this P wave 00:43:31.120 --> 00:43:36.470 and also the S wave and then done a slant stack to essentially adjust and 00:43:36.470 --> 00:43:41.700 build velocity models that are very similar to logging – sonic logs 00:43:41.700 --> 00:43:45.750 in terms of both the P wave and the S wave to then basically use 00:43:45.750 --> 00:43:51.290 this information – this move-out of a few events and capturing the 00:43:51.290 --> 00:43:53.740 velocity profiles based on this. 00:43:53.740 --> 00:43:59.340 It’s a really interesting technique that would probably not be available 00:43:59.340 --> 00:44:03.840 in such a short geophone string. You could adjust in time these 00:44:03.840 --> 00:44:08.030 geophones and try and build a similar model, but it would only be available 00:44:08.030 --> 00:44:12.930 from a certain distance, and the DAS actually covers up to the whole – 00:44:12.930 --> 00:44:17.550 up to shallower depths. I would point out another advantage 00:44:17.550 --> 00:44:20.950 of the DAS here is that, whereas both the geophones 00:44:20.950 --> 00:44:25.740 and the DAS record this P wave move-out, the granite top here at – 00:44:25.740 --> 00:44:28.640 here at this location, you can actually see that this geophone 00:44:28.640 --> 00:44:35.510 looks kind of ring-y, you would say. But the actual – the actual observation 00:44:35.510 --> 00:44:38.640 here in the DAS is that the S wave is coming up here and then splits 00:44:38.640 --> 00:44:42.420 to a P wave and then continues as an S wave also. 00:44:42.420 --> 00:44:47.030 So this conversion is actually quite clear in the DAS data and 00:44:47.030 --> 00:44:50.430 less clear in the geophone data. Although, with the DAS now, 00:44:50.430 --> 00:44:53.720 we can see that maybe this arrival – and you can see the energy of the – 00:44:53.720 --> 00:44:58.360 of the S wave here and also some P wave energy tracking up here. 00:44:58.360 --> 00:45:01.360 Interestingly, it looks like there’s some sort of down-going energy 00:45:01.370 --> 00:45:06.650 or interaction between the up-going and the down-going wave at this location, 00:45:06.650 --> 00:45:09.840 which is recorded over a few gauge lengths in the DAS. 00:45:09.840 --> 00:45:13.760 So these kind of additional observations, both in terms of velocity information 00:45:13.760 --> 00:45:18.160 and the DAS kind of raw observations of the full wavefield here are pretty 00:45:18.160 --> 00:45:22.190 interesting and kind of – I bring them up because I think that, even while 00:45:22.190 --> 00:45:26.900 DAS it not able to record the same – the same number of events, 00:45:26.900 --> 00:45:31.180 there’s additional information here that isn’t available in the geophones 00:45:31.180 --> 00:45:35.280 that helps with the interpretation of the – of the field study. 00:45:36.640 --> 00:45:44.240 So directly comparing the geophone record here to the DAS record, 00:45:44.240 --> 00:45:50.160 with the conversion that I described before, we can compare the DAS noise, 00:45:50.160 --> 00:45:56.780 shown here in the – in the kind of lighter red color to the DAS signal, shown here. 00:45:56.780 --> 00:46:00.130 And you can see that the signal-to-noise ratio would be 00:46:00.130 --> 00:46:07.720 approximately 30 to 40 dB over this range of a couple hundred hertz. 00:46:07.720 --> 00:46:12.960 Whereas, the geophone has a much larger range of signal-to-noise, right? 00:46:12.960 --> 00:46:19.490 So the signal amplitude here is 80 dB of signal. 00:46:19.490 --> 00:46:25.650 This is – this is rather surprising, and I – at this point, there’s kind of 00:46:25.650 --> 00:46:29.740 three possible hypotheses for why this is. 00:46:29.740 --> 00:46:35.370 First of all, there could have been a break in the splice of the cable, 00:46:35.370 --> 00:46:37.810 which would be to a higher-than-usual 00:46:37.810 --> 00:46:43.290 background optical noise elevating this noise level. 00:46:43.290 --> 00:46:48.970 However, tests showed that the noise level was as expected. 00:46:48.970 --> 00:46:51.830 The second idea is that the actual angle differences between 00:46:51.830 --> 00:46:57.360 cosine-squared fall off as a function of azimuth versus DAS – sorry, 00:46:57.360 --> 00:47:02.000 versus the geophone having a cosine falloff does not – would 00:47:02.000 --> 00:47:05.830 kind of explain these differences. And the third hypothesis is that 00:47:05.830 --> 00:47:10.120 we’re measuring – actually, we’re measuring strain versus particle 00:47:10.120 --> 00:47:16.090 motion or velocity with the geophones. And the actual strain field falls off 00:47:16.090 --> 00:47:20.600 differently as a – as a function of space. That is, the far-field term looks a lot 00:47:20.600 --> 00:47:25.160 different than when you look at the strain – the strain solution 00:47:25.160 --> 00:47:30.420 to a point source than it does in the displacement field. 00:47:30.420 --> 00:47:37.180 So those differences – I think the third option is actually the kind of – 00:47:37.180 --> 00:47:42.060 potentially the most interesting and important possibility for what 00:47:42.060 --> 00:47:46.820 would explain this difference in the FORGE case and kind of working 00:47:46.820 --> 00:47:53.660 on quantifying exactly that idea. But I would kind of just move on in 00:47:53.660 --> 00:47:58.500 the interest of time to this third case. We can go back if there’s questions. 00:47:58.500 --> 00:48:04.410 In this case, we recorded along a 52-kilometer cable in Monterey Bay 00:48:04.410 --> 00:48:10.200 looking at just the first 20 kilometers we were actually able to get signal back. 00:48:10.200 --> 00:48:13.220 So this cable was buried at approximately 1 meter depth 00:48:13.220 --> 00:48:17.720 in the ground. And we occupied from a utility closet on the shore. 00:48:17.730 --> 00:48:22.040 The same DAS that we used in previous experiments – the v2. 00:48:22.040 --> 00:48:26.000 So this experiment was only available because they actually take down 00:48:26.000 --> 00:48:29.170 the instrument for a couple days each summer and make 00:48:29.170 --> 00:48:34.870 measurements along the cable. And for those four days, we recorded 00:48:34.870 --> 00:48:40.500 approximately 3-1/2 terabytes of data, and we sampled the DAS data set 00:48:40.500 --> 00:48:43.540 in this manner. So, again, a 10-meter gauge length, 00:48:43.540 --> 00:48:47.680 2-meter sampling, and 500 samples per second. 00:48:47.680 --> 00:48:51.920 So there’s a number of interesting observations made on this cable, and it 00:48:51.920 --> 00:48:57.410 kind of motivates the use of DAS in other marine geophysical experiments. 00:48:57.410 --> 00:49:01.770 So the first is kind of we were able to capture a magnitude 3-1/2 earthquake 00:49:01.770 --> 00:49:09.300 that shows, over the cable kind of aperture here, we see this kind of 00:49:09.300 --> 00:49:15.680 later-arriving S wave drawn down through a zone of known faults that 00:49:15.680 --> 00:49:19.940 were actually mapped by the USGS California Seafloor Mapping Program. 00:49:19.940 --> 00:49:25.270 So, at these three locations of mapped faults from active-source survey, 00:49:25.270 --> 00:49:32.340 we see a draw-down in the arrival time of this phase. The wave front is delayed. 00:49:32.340 --> 00:49:35.590 And also we see scattering between the body wave, and it looks like 00:49:35.590 --> 00:49:39.700 a surface wave move-out of 400 to 800 meters per second, 00:49:39.700 --> 00:49:43.780 which move out from these locations forward and backward. 00:49:44.840 --> 00:49:49.760 Additional work has been done to actually begin to separate out how 00:49:49.760 --> 00:49:54.410 these conversions happen at fault zones. And I’m working with a group – 00:49:54.410 --> 00:50:00.790 the Salvus group to do actually this kind of direct observation, kind of 00:50:00.790 --> 00:50:05.530 backing it up with simulations of actual full wavefield simulations from this 00:50:05.530 --> 00:50:10.540 location through the San Andreas Fault and out into the kind of 00:50:10.540 --> 00:50:14.390 ocean cable locations. So this is the kind of work that 00:50:14.390 --> 00:50:18.190 Afanasiev and others have been doing. These kind of large-wavefield 00:50:18.190 --> 00:50:23.360 simulations are now motivated by direct observations using DAS. 00:50:24.740 --> 00:50:28.820 So during the time when we don’t have earthquakes coming in, we can 00:50:28.820 --> 00:50:33.980 kind of begin to tease apart what DAS is recording on the ocean floor. 00:50:33.980 --> 00:50:37.440 So the kind of five minutes of raw recording are shown here 00:50:37.440 --> 00:50:40.280 over 7 kilometers of the DAS data set. 00:50:40.280 --> 00:50:43.900 The data shown here – this kind of candy striping pattern – 00:50:43.900 --> 00:50:49.790 is recording strain rate information. Tens of nanostrain per second. 00:50:49.790 --> 00:50:54.960 And you can see that it has a dominant velocity, that is the slope here is kind of 00:50:54.960 --> 00:50:59.900 a characteristic around 10 seconds. And it looks like it’s traveling 00:50:59.900 --> 00:51:06.690 inward rather than going outward. So the observation here, it looks like 00:51:06.690 --> 00:51:10.930 likely this is due to the ocean waves or the pressure fields set up 00:51:10.930 --> 00:51:16.270 by these ocean waves. So around this band, we can 00:51:16.270 --> 00:51:22.690 actually be able to predict the microseism amplitude using the kind of 00:51:22.690 --> 00:51:27.080 fundamental equations of how we know microseisms to work on Earth. 00:51:27.080 --> 00:51:32.820 So this equation describes a secondary microseism, which is a little bit higher 00:51:32.820 --> 00:51:37.190 than this band. But the kind of global simulations is something 00:51:37.190 --> 00:51:41.760 I’m working on now at Stanford to basically take an ocean wave model 00:51:41.760 --> 00:51:46.100 and, at each location, propagate with Green’s functions through the Earth 00:51:46.100 --> 00:51:52.160 to the location of the DAS and be able to essentially generate a curve 00:51:52.160 --> 00:51:56.890 that would be the amplitude expected at that location and then compare it to 00:51:56.890 --> 00:52:01.620 what the DAS recorded at that location. So this kind of synthetic is very similar 00:52:01.620 --> 00:52:04.730 to the earthquake case, where we can kind of match synthetics 00:52:04.730 --> 00:52:08.960 and observables to understand what DAS is recording. 00:52:10.420 --> 00:52:15.240 But, you know, until then, we kind of have one instrument recording in the 00:52:15.250 --> 00:52:19.970 same location as our DAS. So, like I said, we took the cable offline 00:52:19.970 --> 00:52:23.900 to be able to do this experiment. So we have one seismometer over here. 00:52:23.900 --> 00:52:29.340 We also have a surface buoy that’s positioned here in Monterey Bay. 00:52:30.780 --> 00:52:35.210 So the – kind of over the four days of the experiment, this is what 00:52:35.210 --> 00:52:40.100 surface wave height looked like. We had kind of an initial storm 00:52:40.100 --> 00:52:42.560 elevating the wave height in Monterey Bay. 00:52:42.570 --> 00:52:47.070 And then the storm kind of died out, and the Pacific kind of went quiet for 00:52:47.070 --> 00:52:50.360 approximately a day and a half. And then there was a second storm 00:52:50.360 --> 00:52:53.310 that churned up at the end of the experiment and kind of 00:52:53.310 --> 00:52:57.660 blew in towards Monterey Bay, elevating wave height again. 00:52:57.660 --> 00:53:03.790 So this is what the buoy recorded – kind of this spectral observations 00:53:03.790 --> 00:53:07.500 averaged every eight minutes – provide this kind of observation that 00:53:07.500 --> 00:53:13.780 shows a strong primary microseism driving force at the beginning of the 00:53:13.790 --> 00:53:17.380 experiment, dying out towards the center of the experiment and kind of 00:53:17.380 --> 00:53:21.280 building back up towards the end of the experiment. So this is what the buoy – 00:53:21.280 --> 00:53:24.820 this is essentially what the wave was – what the water height was doing. 00:53:26.640 --> 00:53:30.970 The DAS and also the microseism observations on the seismometer 00:53:30.970 --> 00:53:34.510 in the northern component showed this kind of observation. 00:53:34.510 --> 00:53:38.441 So that you can see the correspondence between the ocean buoy and the 00:53:38.441 --> 00:53:44.470 seismometer here with the kind of stronger primary and also secondary 00:53:44.470 --> 00:53:49.790 microseism before the kind of – at the early days of the recording. 00:53:49.790 --> 00:53:54.100 And the DAS is also recording that. Then the weaker period of the 00:53:54.100 --> 00:53:58.080 experiment. And the DAS also looks like it’s reducing in amplitude 00:53:58.080 --> 00:54:02.130 at that position at that time. And then strengthening back up 00:54:02.130 --> 00:54:03.940 towards the end of the experiment. 00:54:03.940 --> 00:54:07.770 So there are major differences, both in the frequency content of 00:54:07.770 --> 00:54:13.020 these recordings and also in terms of specifically this characteristic mode 00:54:13.020 --> 00:54:18.260 on March 13th that’s recorded by the wave – the buoy and also 00:54:18.260 --> 00:54:21.720 the seismometer, which doesn’t look like it’s recorded on the DAS. 00:54:21.730 --> 00:54:26.150 And so this is a kind of motivation to put out additional hydrophones and 00:54:26.150 --> 00:54:31.170 broadband seismometers along this DAS and then do this kind of direct 00:54:31.170 --> 00:54:34.200 comparison between what we’re recording with DAS and these 00:54:34.200 --> 00:54:37.730 other sensors at the same location. There could be key differences 00:54:37.730 --> 00:54:40.550 between the fact that the buoy is deployed in deeper water 00:54:40.550 --> 00:54:45.520 and this seismometer is very far away from our – from our DAS. 00:54:47.310 --> 00:54:51.420 One thing that we can do is we can look at the whole run of the cable 00:54:51.430 --> 00:54:56.410 of the DAS crosses different water depths of capital H here. 00:54:56.410 --> 00:54:58.810 And we have, over time of the experiment, 00:54:58.810 --> 00:55:02.400 a range of wave heights – little h here. 00:55:02.400 --> 00:55:06.970 So the kind of description of how the pressure of the – on the seafloor 00:55:06.970 --> 00:55:13.070 at a depth of capital H falls off over wave height is described 00:55:13.070 --> 00:55:16.960 by these white lines here. So this is a model of the pressure of the seafloor. 00:55:16.960 --> 00:55:21.450 And you can see that the data, to first order, follow this model, 00:55:21.450 --> 00:55:25.960 suggesting the DAS is at least recording something about the wave pressure. 00:55:25.960 --> 00:55:31.591 Now, how that vertical pressure is converting to a horizontal strain 1 meter 00:55:31.600 --> 00:55:38.220 below the seafloor mud surface is kind of still an open question to understand. 00:55:39.590 --> 00:55:43.660 So with just a few minutes left, I’m going to kind of describe 00:55:43.660 --> 00:55:47.380 these differences. So that kind of DAS fiber 00:55:47.380 --> 00:55:50.790 does record strain over a broad frequency range that I think is 00:55:50.790 --> 00:55:54.410 applicable to seismology and geodesy. There’s an additional calibration 00:55:54.410 --> 00:55:58.420 needed, both in the lab and also in the field, for this kind of instrument 00:55:58.420 --> 00:56:05.280 comparison and also synthetic observation comparisons. 00:56:05.280 --> 00:56:09.770 We see in different experiments interesting advantages and 00:56:09.770 --> 00:56:12.770 disadvantages of DAS. And I think, specifically in the 00:56:12.770 --> 00:56:19.130 shallow marine case, there’s kind of a real interest in understanding how DAS 00:56:19.130 --> 00:56:25.700 is recording the kind of solid Earth signals and also the ocean signals. 00:56:26.540 --> 00:56:32.040 So I’m going to kind of leave up this slide as I take some questions, 00:56:32.050 --> 00:56:34.600 but if you’re interested in getting some more information about 00:56:34.600 --> 00:56:38.920 DAS or learning more about DAS, I’d encourage you to read our papers 00:56:38.920 --> 00:56:43.640 and also check out this tutorial. You can also sign up for 00:56:43.640 --> 00:56:45.960 a three-day workshop that’s coming up. 00:56:45.960 --> 00:56:49.630 It’s going to be a virtual online workshop that I guess next week’s 00:56:49.630 --> 00:56:53.440 speaker, Eileen Martin, and I are kind of jointly leading. 00:56:53.440 --> 00:56:57.480 So click this link and sign up or look for the announcement 00:56:57.480 --> 00:56:58.920 in the next couple of days. 00:56:58.920 --> 00:57:01.260 Thank you very much for your attention. 00:57:01.920 --> 00:57:05.400 - Thank you very much, Nate. If anybody has a question for Nate, 00:57:05.400 --> 00:57:11.960 you can either unmute yourself and ask or type it into the chat of this meeting. 00:57:15.260 --> 00:57:18.320 - Hey, Nate. It’s Andy. Thanks for a really thorough 00:57:18.320 --> 00:57:23.480 and excellent demonstration of the various things that it can do. 00:57:23.480 --> 00:57:27.980 I’m wondering, in the geothermal case, you know, is there any indication that 00:57:27.980 --> 00:57:34.160 temperature is an issue in terms of reducing the, I don’t know, elasticity 00:57:34.160 --> 00:57:37.740 of the cable, such that if you get higher and higher temperatures, 00:57:37.740 --> 00:57:41.220 you might lose the ability to even measure anything? 00:57:42.960 --> 00:57:47.600 - I’m not – I’m not familiar with kind of coupling consequences 00:57:47.600 --> 00:57:50.920 of the temperature, which is, I think, what you’re saying. 00:57:50.920 --> 00:57:54.780 - Yeah. - The real issues have been 00:57:54.780 --> 00:57:57.540 melting of the fiber. [laughs] - Okay. [laughs] 00:57:57.540 --> 00:58:00.150 - At higher temperatures. Although there’s lots of ways to 00:58:00.150 --> 00:58:03.440 avoid that now with high-temperature coatings. 00:58:03.440 --> 00:58:10.480 The thermal strain issue is quite a significant issue, but I think that that 00:58:10.480 --> 00:58:14.510 would maybe a complementary observable, where you’d have a 00:58:14.510 --> 00:58:18.970 downhole fiber, and you could both measure the thermal strain and also 00:58:18.970 --> 00:58:24.270 the kind of elastic deformation, or brittle deformation, of earthquakes. 00:58:24.270 --> 00:58:26.570 So that – you could also separately measure that 00:58:26.570 --> 00:58:29.820 with a distributed temperature instrument. 00:58:29.820 --> 00:58:34.820 But I’m not – I’m not familiar with any coupling issues. 00:58:34.820 --> 00:58:36.120 - Thanks. 00:58:38.060 --> 00:58:39.780 - Thank you, Nate. - And, Nate, this is Steve – or I see 00:58:39.790 --> 00:58:43.710 Noha might be saying it [chuckles], but I just – I just typed in a question. 00:58:43.710 --> 00:58:47.010 And really nice talk. Great. 00:58:47.010 --> 00:58:49.540 Have you thought about the use of DAS for monitoring of changes in 00:58:49.540 --> 00:58:54.740 fracture permeability over time? Like in the EGS projects, like FORGE. 00:58:54.740 --> 00:58:58.540 Obviously, you showed – you showed there were obviously scattering effects. 00:58:58.540 --> 00:59:01.220 You showed guided wave potential, the effects, and fault zones. 00:59:01.220 --> 00:59:02.670 I’m just thinking about time dependence. 00:59:02.670 --> 00:59:06.060 This is a case where DAS could offer a real advantage over 00:59:06.060 --> 00:59:10.690 a temporarily deployed geophone string at smaller – and of course, 00:59:10.690 --> 00:59:13.400 DAS has much closer spacing. So have you thought about that 00:59:13.400 --> 00:59:15.400 time-dependent question? 00:59:15.410 --> 00:59:21.190 - Yeah. So I think that that – so, in terms of time of deployment, DAS could be 00:59:21.190 --> 00:59:27.060 deployed, you know, today and record in 10 years’ time on the same fiber. 00:59:27.060 --> 00:59:32.580 So the possibility to look at very long times is available with DAS, where it 00:59:32.580 --> 00:59:37.490 might not be available with other sensors that might degrade downhole. 00:59:37.490 --> 00:59:40.790 But I think that your real question about the kind of scientific benefit 00:59:40.790 --> 00:59:46.290 of recording at such a long range of periods and also recording strain is – 00:59:46.290 --> 00:59:49.560 the issue with that is actually getting close enough. 00:59:49.560 --> 00:59:53.720 In the case of FORGE, there’s about 1,000 meters’ difference between the 00:59:53.720 --> 00:59:57.100 depth at which the observation well was dug and where the – where the 00:59:57.100 --> 01:00:01.020 events were actually occurring at a depth of about 2 kilometers and that 01:00:01.020 --> 01:00:06.440 would – the stimulation depth. And that distance means that the 01:00:06.440 --> 01:00:11.280 actual strain that is being communicated through fractures – if your goal is to 01:00:11.280 --> 01:00:14.690 measure fracture permeability, it would be much better to be 01:00:14.690 --> 01:00:18.060 down observing DAS right next to where you’re – 01:00:18.060 --> 01:00:23.240 where you’re creating the fracture. But the – yeah, I think that 01:00:23.250 --> 01:00:27.060 that’s the major issue. But I think that a lot of the 01:00:27.060 --> 01:00:30.700 hydraulic fracturing cases have shown those kind of stimulations 01:00:30.700 --> 01:00:35.840 which generate seismic wavefields that are observed and then flowback, 01:00:35.840 --> 01:00:38.750 and also thermal strain. So you can see a full range 01:00:38.750 --> 01:00:42.870 of physics if you can get down close enough to those events. 01:00:42.870 --> 01:00:46.460 - Yeah. I was also thinking about fault zone drilling projects who are actually 01:00:46.460 --> 01:00:50.000 crossing a fault zone and installing something permanently behind casing. 01:00:50.000 --> 01:00:52.700 DAS could be huge for something like that. 01:00:52.700 --> 01:00:56.390 And even with FORGE, you know, there will be two wells drilled, so it’s 01:00:56.390 --> 01:00:59.700 not impossible you might get close to some of the stimulated fractures. 01:00:59.700 --> 01:01:03.060 So it’s very – you know, I really like the idea of doing the strain and the 01:01:03.060 --> 01:01:05.960 temperature and the broadband seismometry all at the same time. 01:01:05.960 --> 01:01:07.800 That’s a real advantage. 01:01:07.800 --> 01:01:11.260 - I think the scattering – the scattering waves are quite interesting too. 01:01:11.260 --> 01:01:15.770 There’s a lot that can be learned by such dense sampling of that information. 01:01:15.770 --> 01:01:18.140 - Yeah, great, thanks. 01:01:19.200 --> 01:01:22.400 - Are there any more questions for Nate? 01:01:25.800 --> 01:01:42.900 [Silence] 01:01:42.900 --> 01:01:46.020 Just give people a minute – one minute. 01:01:48.060 --> 01:01:52.240 Either unmute yourself or type it into the chat. 01:01:54.720 --> 01:01:59.340 [Silence] 01:01:59.340 --> 01:02:02.380 - I’ve got a question. 01:02:02.380 --> 01:02:06.540 You talked a little bit about this, but you mentioned, at one of the 01:02:06.540 --> 01:02:10.780 experiments, you saw many more earthquakes with the geophone string 01:02:10.790 --> 01:02:17.540 than you did with the – with the DAS. Can you sort of hypothesize why 01:02:17.540 --> 01:02:21.770 that happened and sort of think about how you could get better 01:02:21.770 --> 01:02:24.840 detectability with the DAS? 01:02:27.820 --> 01:02:31.680 - Yeah. So I think, in the case – in the case of FORGE, where the 01:02:31.680 --> 01:02:34.400 geophones are being compared to 01:02:34.400 --> 01:02:38.540 DAS, I would first say that these are state-of-the-art geophones. 01:02:38.540 --> 01:02:42.620 They’re great geophones. And Schlumberger has developed 01:02:42.630 --> 01:02:46.900 a whole processing flow based on these geophones to enhance 01:02:46.900 --> 01:02:50.590 the ability to detect the seismic events. 01:02:50.590 --> 01:02:54.010 But we have, you know, many more events – many more observations of 01:02:54.010 --> 01:02:57.240 each event that we could stack over, for example, of the DAS. 01:02:57.240 --> 01:03:01.600 There’s no reason why we shouldn’t be able to record the same number 01:03:01.610 --> 01:03:08.090 of events with DAS, in my mind, if we were close enough. 01:03:08.090 --> 01:03:13.140 So I think the main issues could be a break in the fiber, which would 01:03:13.140 --> 01:03:17.240 lead to a higher-than-normal backscattered amount of light, 01:03:17.240 --> 01:03:21.790 elevating the noise floor. There could be a difference in terms of 01:03:21.790 --> 01:03:27.060 the azimuth of the incoming wavefield as recorded by a component of a inertial 01:03:27.060 --> 01:03:30.800 sensor versus the DAS, which has this kind of azimuthal difference – 01:03:30.800 --> 01:03:37.120 azimuthal kind of falloff difference. And the third possibility is that the 01:03:37.120 --> 01:03:42.690 actual recording of strain itself is leading to a – kind of a key difference 01:03:42.690 --> 01:03:48.240 in the way that – the amplitude of any sort of signal. 01:03:48.240 --> 01:03:53.540 And that is going to be better in the near-field than in the far-field. 01:03:53.550 --> 01:03:58.150 And there’s kind of some initial work to look at that, but I think that that 01:03:58.150 --> 01:04:01.950 third issue is kind of the most unresolved at this point, 01:04:01.950 --> 01:04:08.510 i.e., the far-field term in terms of a strain versus a displacement field. 01:04:08.510 --> 01:04:12.160 And that comparison could be – could be key. 01:04:14.620 --> 01:04:16.140 - Thanks. 01:04:16.140 --> 01:04:19.080 - Thank you very much, Nate, for the excellent talk. 01:04:19.080 --> 01:04:23.360 Thanks for [audio garbled], and thank you, everyone, for being there today. 01:04:23.360 --> 01:04:24.460 Thank you. 01:04:27.820 --> 01:04:29.920 - Thank you. - Thank you, Nate. 01:04:29.920 --> 01:04:32.920 - Thanks, everyone. - Thanks, Nate. 01:04:32.920 --> 01:04:36.620 [clapping] - Thanks, Nate. 01:04:39.040 --> 01:04:44.780 [Silence]