Cross Reference to Related Applications

[0001] This application is a non-provisional application which claims priority from U.S. provisional application number 62/582,717, filed November 7, 2017, which is incorporated by reference herein in its entirety.

Technical Field/Field of the Disclosure

[0002] The present disclosure relates generally to detection and location of slugs, wax buildup, and hydrate buildup in pipelines.

Background of the Disclosure

[0003] As described by typical flow mechanics, slug flow is a multiphase-fluid flow pattern with a series of liquid slugs separated by gas pockets. Slugs occur in pipelines, such as offshore pipelines, that carry mixtures of oil and gas, for example. The gas and liquid may not be evenly distributed throughout the transport pipelines, such that the gas and liquid may instead travel as a plugged train.

[0004] Slugs may result from a number of causes. Slug flow may begin with an accumulation of oil and water in low-lying parts of a pipeline (the slug). Gas may then collect downstream of the growing slug, causing an increase in pressure. When the pressure reaches a certain level, the slug moves towards the pipeline outlet. This process may then repeat itself. Terrain- induced slugging may be caused by, for instance, gravity induced accumulation of liquid in a riser. Pigging may also cause slugging. Slugs may form even in a horizontal pipeline at certain liquid and gas velocities. Because slugs are typically intermittent and difficult to monitor, determining the causes of slugging may be difficult. While lab studies may permit limited predictions of the formation of plugs, slugs may be difficult to predict in field conditions, as minor changes in pipe geometry, fluctuations in velocities and fluid properties will disturb the flow and produce slugs differently than those that predicted by lab studies. Further, because slugs are typically intermittent and difficult to monitor, determining the causes of slugging may be difficult.

[0005] Slugs may damage pipeline integrity and pipeline equipment. For instance, slug impact loads may induce structural vibrations and lead to component failures as a result of resonance or fatigue. Slugs may also result in emergency shutdown of pipeline equipment and offshore platforms, disrupting production.

[0006] Traditionally, effective monitoring of slugs in pipelines has not been accomplished. While pipeline system modeling has been used to redesign and therefore reduce the occurrence of slugs, methods of detection such as measurement of pipeline pressure over time typically do not detect slugs until the slug has reached the pressure monitor, if at all.

[0007] Paraffin precipitation and deposition in flowlines and pipelines may impact the development of subsea hydrocarbon reservoirs. The buildup of paraffin deposits decreases the pipeline cross-sectional area, restricts operating capacities, and places additional strain on pumping equipment. At temperatures below the cloud point, the n-paraffin components begin to crystallize into solid wax particles. The wax particles can adhere to one another when the wax-containing hydrocarbon comes in contact with any surface that has a temperature below the wax appearance temperature (WAT) and provides a heat sink.

[0008] During the natural gas transportation through pipelines and under certain thermodynamic conditions, considering pressure, temperature and composition, crystalline compounds, consisting of a gas molecule and water, are formed. These ice- like compounds are known as "gas hydrates" or "gas clathrates". Hydrate formation in pipelines typically requires three conditions: low temperature and high pressure; the presence of hydrate formers such as CH4, C2H4, CO2 and H2S; and sufficient quantities of water and formation time. Gas hydrates may result in pipeline blockage, threatening the foundations of deep-water platforms and pipelines, plugging blowout preventers during the production and causing tubing and casing collapse.

[0009] Distributed Acoustic Sensing (DAS) systems operate using principles similar to Optical Time-Domain Reflectometry (OTDR). In OTDR, a fiber-optic cable is probed with a laser pulse from an interrogation unit. Defects in the glass backscatter the pulse (Rayleigh scattering) as it propagates along the fiber and the backscattered photons are received in a photodetector. The data is used to map the reflectivity of the fiber along its length. In DAS, external acoustic disturbances modulate the Rayleigh backscattered light from certain sections of the fiber. By recording the Coherent Rayleigh Noise traces, DAS transforms the fiber into a large number of distributed microphones or acoustic sensors.

Summary

[0010] The present disclosure provides a method. The method includes providing a DAS apparatus. The DAS apparatus includes a fiber optic cable, the fiber optic cable wound or positioned about a pipeline and a DAS interrogator, the DAS interrogator in light communication with the fiber optic cable. The method also includes measuring Rayleigh backscattered light using the DAS interrogator and determining the existence of a slug in the pipeline from the Rayleigh backscattered light, wherein the Rayleigh backscattered light corresponds to a Coherent Rayleigh Noise signal.

[0011] The present disclosure also provides for a method. The method includes providing a DAS apparatus. The DAS apparatus includes a fiber optic cable, the fiber optic cable wound about a pipeline and a DAS interrogator, the DAS interrogator in light communication with the fiber optic cable. The method also includes measuring Rayleigh backscattered light using the DAS interrogator. The method further includes measuring Raman DTS using the DAS interrogator and measuring Brillouin BOTDR/BOTDA using the DAS interrogator. In addition, the method includes determining the existence of hydrate or wax formation or deposition in the pipeline from the Rayleigh backscattered light, wherein the Rayleigh backscattered light corresponds to a Coherent Rayleigh Noise signal, the temperature using Raman DTS and pressure drop using Brillouin BOTDR/BOTDA.

Brief Description of the Drawings

[0012] The present disclosure is best understood from the following detailed description when read with the accompanying figures. It is emphasized that, in accordance with the standard practice in the industry, various features are not drawn to scale. In fact, the dimensions of the various features may be arbitrarily increased or reduced for clarity of discussion.

[0013] FIGs. 1 - 1C depict a pipeline slug monitoring system consistent with certain embodiments of the present disclosure.

[0014] FIG.2 is a cross-sectional view of a fiber optic cable consistent with certain embodiments of the present disclosure.

[0015] FIG. 3 depicts an exemplary coherent Rayleigh Noise Signal from a section of pipeline with slugging as measured by a DAS apparatus in conjunction with a cross-section of pipeline consistent with certain embodiments of the present disclosure.

[0016] FIG. 4 depicts a horizontal well facility as described in the Examples.

[0017] FIG. 5 is an exemplary waterfall graph from a DAS apparatus.

[0018] FIG. 6 is a waterfall graph from a DAS apparatus in conjunction with a time versus amplitude graph.

[0019] FIG. 7 is a time versus amplitude graph. [0020] FIG. 8 is series of graphs depicting conversion of signals from a DAS apparatus through FFT.

[0021] FIG. 9 is a spectrogram of a series of overlapped FFTs for a series of slugs.

[0022] FIG. 10 is an acoustic spectrum as described in Example 1.

[0023] FIG. 11 is an acoustic spectrogram of the tests of Example 2.

[0024] FIG. 12 depicts a waterfall diagram of the results of Example 3.

[0025] FIG. 13 depicts a spectrogram of the results of Example 3.

[0026] FIG. 14 depicts a waterfall diagram of the results of Example 4.

[0027] FIG. 15 depicts a spectrogram of the results of Example 4.

[0028] FIG. 16 is a depiction of a turbulent boundary layer flow in a pipeline resulting from wax buildup.

[0029] FIG. 17 depicts an exemplary coherent Rayleigh Noise Signal from a section of pipeline as measured by a DAS apparatus in conjunction with a cross-section of pipeline having wax buildup consistent with certain embodiments of the present disclosure.

Detailed Description

[0030] It is to be understood that the following disclosure provides many different embodiments, or examples, for implementing different features of various embodiments. Specific examples of components and arrangements are described below to simplify the present disclosure. These are, of course, merely examples and are not intended to be limiting. In addition, the present disclosure may repeat reference numerals and/or letters in the various examples. This repetition is for the purpose of simplicity and clarity and does not in itself dictate a relationship between the various embodiments and/or configurations discussed.

[0031] FIG. 1C depicts a typical, non-limiting example of Distributed Acoustic Sensing System (DAS) 10. DAS 10 includes coherent light source 20 coupled to fiber optic cable 120 through circulator 30. Coherent light source 20 may be a pulsed light source. As coherent light source 20 is propagated through fiber optic cable 120, vibrations 40 may cause backscatter noise in the coherent light, as further described below. The returning coherent light from fiber optic cable 120 passes through circulator 30, it is collected by photodiode 50 and processed within DAS interrogator 130.

[0032] DAS is a variant of an Optical Time Domain Reflectometer (OTDR) that monitors the coherent Rayleigh backscatter noise signature in fiber optic cable 120 as pulsed light is sent into the fiber. The coherent Rayleigh noise generates fine structure in the backscatter signature of fiber optic cable 120. The DAS focuses on the Raleigh component to increase the prominence of the Raleigh component in the backscatter trace.

[0033] DAS may measure small changes in the coherent Rayleigh noise structure that occurs from pulse to pulse. Because the coherent Rayleigh noise structure is generated interferometrically within the fiber by the relative locations and strengths of local scattering centers intrinsic to the structure of the glass of the fiber, very small physical (acoustic or vibration) disturbances at a point in the fiber may make detectable changes in the interferometric signal. For example, if the optical pulses are made with a narrow line width, high coherence laser, then these scattered return light signals will interfere with each other causing signal ripples that superimpose the loss trace. These ripples, because they are related to the fixed Rayleigh scatter sites within a fiber, are static as long as the fiber is static. If the fiber experiences any perturbations, or external forces, which strain the fiber, the positions of the scatter sites change. This in turn changes the interferometric induced ripples.

[0034] FIG. 1 depicts pipeline slug monitoring system 100 consistent with certain embodiments of the present disclosure. Pipeline slug monitoring system 100 includes pipeline 110 upon which fiber optic cable 120 is wound or positioned. Fiber optic cable 120 terminates in DAS interrogator 130. Fiber optic cable 120 is shown in FIG. 1 as having a helix configuration with a long pitch. Alternative configurations are shown in FIGs. 1A and IB, wherein fiber optic cable 120 has a helix configuration with a short pitch and separated cables (120a, 120b), respectively. In certain embodiments, as shown in FIG. IB, separated cables 120a, 120b are positioned about 180° apart on the outside surface of pipeline 110. Without being bound by theory, helix configurations and separated cables positioned about 180° apart allows better detection of the noise within the pipeline, as described below, as it allows noise detection of different positions about the pipeline, e.g., top, bottom, and sides. Such a configuration may allow for detection of slug flow, for instance, when gas is in the upper part of the pipeline and liquid in the lower part. The shorter the pitch of the cable, the more closely slugs may be localized and the higher the spatial resolution of slug length and frequency characterization. In certain embodiments, a short helix configuration may allow one meter or less spatial resolution of the slug.

[0035] Fiber optic cables 120, 120a, 120b are mechanically attached along at least a portion of the length of fiber optic cables 120, 120a, 120b to pipeline 110. As used hereinbelow, fiber optic cables 120 (or 120a, 120b) in conjunction with DAS interrogator 130 is referred to as a "DAS apparatus." The DAS apparatus may be easily attached or adapted to existing fiber optic cable, such as telecommunications fiber on pipeline 110. The tighter or more closely attached the fiber optic cable is to the pipeline, the more sensitive the DAS apparatus is to vibration/noise and the better the data regarding slug localization, slug length, and slug frequency or translation velocity may be determined.

[0036] In certain embodiments, each fiber optic cable 120, 120a, 120b may include at least two single mode (SM) and one multimode (MM) fiber. In other embodiments, each fiber optic cable 120, 120a, 120b may include one SM fiber, or one SM fiber and one MM fiber. SM fiber has a small diametral core that allows only one mode of light to propagate. The number of light reflections created as the light passes through the core decreases in SM fiber, lowering attenuation and creating the ability for the signal to travel further. In contrast, MM fiber has a large diametral core that allows multiple modes of light to propagate. The number of light reflections created as the light passes through the core increases in MM fiber, creating the ability for more data to pass through at a given time. Because of the high dispersion and attenuation rate with this type of fiber, the quality of the signal may be reduced over long distances.

[0037] Optical fibers, as described below, are mechanically tight to each other within fiber optic cable 120, 120a, 120b and to pipeline 110. Where pipeline slug monitoring system 100 may include at least two single mode (SM) and one multimode (MM) fiber, different fibers may be used to make different measurements:

[0038] For example and without limitation, DAS using Coherent Rayleigh Noise Back Scattering effect may be accomplished with a SM optical fiber. Amplitude and frequency spectra (10 to 50000 Hz) of acoustic signals may be measured approximately every meter over the length of pipeline 110. Distributed Temperature Sensing (DTS) using Raman Backscattering effect may be accomplished with a multi-mode fiber. Like DAS, DTS may measure temperature every meter. Distributed Strain Sensing (DSS) using Brillouin Backscattering (BOTDR or BOTDA) effect may be accomplished with a single-mode fiber. Distributed strain and temperature may be made approximately every meter. As is evident to one of ordinary skill in the art, when only DAS is desired, a single SM fiber may be used.

[0039] FIG.2 is a cross-sectional view of a non-limiting example of fiber optic cable 120, 120a, 120b consistent with certain embodiments of the present disclosure. Fiber optic cable 120 may include tension member 125, tension member coating 140, one or more optical fibers (SM or MM) 150, filling 160, overcoat 170, and jacket 180. Tension member 125 may be used to provide strength and durability to the fiber optic cable. Filling 160 may keep optical fibers 150 within proper position and overcoat 170 and jacket 180 may protect optical fibers 150 from damage due to abrasion or corrosion.

[0040] In the present disclosure, Rayleigh backscattered light may be used for determining and monitoring slug flow. Rayleigh backscattered light forms 80-90 percent of the total backscattered light in an optical fiber. The Rayleigh backscattered light has the same wavelength as the incident light. Further, the amplitude of the Rayleigh backscattered light is much higher and closer to the amplitude of the incident light in comparison of Raman and Brillouin backscattered light. As a result, Rayleigh backscattered light is very responsive to vibrations/noise in both time and space, allowing use of Raleigh backscattered light for optical fibers up to 50 miles in length and high time-variant disturbances like acoustical and vibrational disturbances found in slugs.

[0041] DAS interrogator 130 may use time-resolved monitoring from the Distributed Acoustic Sensing intensity-based (DASI) form. DASI relies on the Coherent Optical Time Domain Reflectometry (COTDR), where the intensity signal resulting from self-interfering backscattered optical pulses is measured. High-sensitivity photodetectors may be used for DASI-based interrogators. The result of COTDR using DASI is a nonlinear and compressed measure of the acoustic & vibration signals. DASI interrogators are effective in detecting and localizing acoustic signals as transferred to the fiber optic cable.

[0042] In other embodiments, DAS interrogator 130 may use a phase-based approach (DASP). DASP adopts an interferometry approach, where optical phase demodulation is used to obtain a measure of the acoustic signal. This approach may be used to provide for linear representations of the distributed acoustic signals and is appropriate for coherent array processing, commonly used for conventional geophones, accelerometer and hydrophone sensor arrays for vertical seismic profile (VSP) methods in reservoir characterization, for instance.

[0043] As discussed above, by measuring flow noise along pipeline 110 using a coherent Rayleigh Noise signal from the DAS apparatus, the DAS apparatus may differentiate different sections of pipeline 110 for multiphase flows, indicative of:

• sections of the pipeline 110 where a turbulent slug is filled with mostly fluid (more noisy).

• sections of pipeline 110 where fluid moves at the lower portion of the pipeline section and gas at the upper portion of the pipeline section. Sections of pipeline 110 having this gas/fluid characteristic in this section are less noisy and may be defined as "background noise."

[0044] FIG. 3 depicts exemplary coherent Rayleigh Noise signal 200 from a section of pipeline 110 as measured by the DAS apparatus in conjunction with a cross-section of pipeline 110 showing slugs detected. Rayleigh Noise signal graph 210 depicts coherent Rayleigh Noise signal 200 as measured by the DAS apparatus along a section of fiber optic cable 120 along a section of pipeline 110. From Rayleigh Noise signal 200, the DAS apparatus may determine peaks 230, 230', noise intensity h 220 of each peak 230, 230', width 250 of peak 230, progression 260 of peak 230, peak-to-peak distance 265 and noise background 240.

[0045] Noise background 240 may correspond to the noise generated by flow through pipeline 1 10 when no slug is present, as shown in flow 290 of cross section 270 of pipeline 1 10. Noise background 240 may be determined, for example and without limitation, by flowing a liquid through pipeline 1 10 and measuring noise background 240 using the DAS apparatus. Once noise background 240 has been determined, the DAS apparatus may be used to identify any anomalies such as a peak in Rayleigh noise for a section of pipeline 1 10. Where peaks are detected, DAS may determine peak characteristics of first peak 230 and second peak 230' . For instance, as noise intensity 220 rises, peak 230 height h, i. e. , amplitude, may be determined. Through measurements along section of fiber optic cable 120, width 250 of peak 230 may be determined. Further measurement of noise intensity 220 as a function of time may be used to calculate progression 260 of peak 230. In addition, as noise background 240 is known, deviations of Rayleigh Noise signal 200 from noise background 240 may be used to determine peak initiation 262, 262' . Once peak initiation 262 and peak initiation 262' are known, peak- to-peak difference 265 may be calculated.

[0046] Cross-section 270 of pipeline 1 10 corresponds to Rayleigh Noise signal graph 210. As shown in cross-section 270, first slug 280 and second slug 280' correspond to fist peak 230 and second peak 230', respectively. Noise background 240 corresponds with non-peak flow 290. Width 250 of first peak 230 corresponds with slug length 300 of first slug 280. Progression 260 of first peak 230 corresponds with slug velocity 310. In addition, peak-to-peak difference 265 corresponds with slug frequency 320. Thus, Rayleigh noise signal graph 210 may be used to identify the slug flow and determine the length of the slug, the velocity of the slug along the pipeline, and the frequency of slugs in the pipeline. [0047] An example of a test facility is shown in FIG. 4 and described hereinbelow. As shown in FIG. 5, as slugs travel along a lateral section of pipeline (from right to left), the slugs generate sections of high localized noise that may be detected using the DAS apparatus. By plotting noise level along 410 versus time, as shown in waterfall chart FIG. 5, the areas of high noise are easily noticeable on the DAS Waterfall (black/white stripes). FIG. 5 depicts high noise level as lighter in color. The progression of slugs along 410 is visible by the sloping of the white stripes. Slug velocities may be assessed by analyzing the stripes' slopes. As shown in FIG. 6, noise amplitude at one location along 410, shown as position P as shown in the black zone) may be used to determine the slug frequency and length at this location.

[0048] As shown in FIG. 7, once slug velocity is known, slug length may be calculated by multiplying the slug velocity by total time of the slug. Slug frequency may be determined from the number of noise peaks in a period of time, as described above. In the waterfall graph of FIG. 5, frequency is not displayed. Spectral analyses such as FFT or spectrograms may be used to determine frequency. Information such as velocity, period, average peak amplitude, and high order flow characteristics may be determined from frequency. FFT may be used to compute a discrete Fourier transform (DFT). As shown in FIG. 8, a vibrational waveform signal is transformed to the acoustic spectrum through FFT computation. This Fourier transform outputs vibration amplitude as a function of frequency. The frequency resolution in a FFT is directly proportional to the signal length and sample rate. To improve the resolution, the time of the recording may be extended.

[0049] A spectrogram may take a series of FFTs and overlap the series of FFTs to illustrate how the spectrum (frequency domain) changes with time. If vibration analysis is being done on a changing environment, a spectrogram may illustrate exactly how that spectrum of the vibration changes. An example of such a spectrogram is shown in FIG. 9, which depicts a series of slugs over time.

[0050] With respect to wax formation, waxes may precipitate in pipelines due to temperature and due to a concentration gradient between the bulk center low and the fluid closer to the wall of the pipeline. An increase in velocity due to the decrease in flow area, i.e. , wax thickness increases inside the pipeline, and changes in the shear rates and shear stress result. Further, roughness on the pipeline wall will be changed, modifying turbulences and pressure drop along the line. Such turbulence is depicted, as a non-limiting example, in FIG. 16. Without being bound by theory, in one mechanism, wax builds along the plate, the laminar flow may be disrupted, resulting in an aerodynamic component. The aerodynamic component causes an acoustic component which radiates as vibration waves. Thus, flow in the pipeline may be disturbed by wax deposition and wax precipitates in bulk. The disruption in flow may modify sound propagation in relation to wax presence.

[0051] By measuring flow acoustic signals, temperature and pressure along the pipeline, it is possible to determine certain characteristics about wax precipitation and deposition using coherent Rayleigh noise (CRN) in DAS and DTS. Higher acoustic noise amplitude is measured where wax forms due to high turbulences and eddies using CRN DAS measurements. Higher frequency of acoustic noise is measured as wall roughness causes larger vortices at the boundary layer of the pipe using CRN DAS measurements. Further, higher fluid velocity will be measured (Doppler shift of sound of speed through CRN DAS measurements). In addition, lower temperature along the pipeline may show wax formation. The temperature of the pipeline wall may be measured through Raman DTS. Further, higher pressure drop along the pipeline, which may be detected using change of hoop distributed pipe strain, may be determined using Brillouin BOTDR/BOTDA with tight helix configuration on the fiber optic cable.

[0052] FIG. 17 depicts exemplary coherent Rayleigh Noise signal 500 from a section of pipeline 110 as measured by the DAS apparatus in conjunction with cross-section of pipeline 110 showing wax deposition. Rayleigh Noise signal graph 210' depicts coherent Rayleigh Noise signal (CRN) 500 as measured by the DAS apparatus along a section of fiber optic cable 120 along a section of pipeline 110' . From CRN signal 500, the DAS apparatus may determine peak 530, noise intensity h' 520 of peak 530 and noise background 540. Noise background 540 may correspond to the noise generated by flow through pipeline 110' when no wax deposit 600 is present, as shown by flow 590 of cross section 570 of pipeline 110'. Noise background 540 may be determined, for example and without limitation, by flowing a liquid through pipeline 110' and measuring noise background 540 using the DAS apparatus. Once noise background 540 has been determined, the DAS apparatus may be used to identify any anomalies such as a peak in Rayleigh noise for a section of pipeline 110'. Such a peak may identify the wax deposit.

[0053] When hydrates form in flowlines, the hydrates may be solid structures that move with the flow and no deposition occurs (case 1) or may form as deposits, typically on the bottom of the pipeline (case 2). In the first case, hydrate formation changes the rheology of the fluid and consequently the velocity profiles and pressure gradients. Together with the exothermic process of hydrates formation, the presence of hydrates in a pipeline may be identified. Fluids with different phases generate noises with different acoustical properties (intensity and frequency). Thus, the DAS apparatus may be used to determine these different acoustical properties of the multi-phase fluids. For example, a higher pressure drop along the pipeline may be determined by a change of Hoop Distributed Pipe Strain through Brillouin BOTDR/BOTDA using the DAS Apparatus having the tight helix configuration. As shown in FIG. 17, lower temperatures on particular sections of pipeline walls is usually the cause of wax formation. In certain embodiments of the present disclosure, temperature of the pipeline wall may be measured through Raman DTS, Further, by using the DAS Apparatus configuration with two longitudinal optical cables (upper and lower cables), hydrate deposits may be detected through the contrast between the flow noise measured by both upper and lower cables. Thus, DAS and DTS may detect the formation of a hydrate blockage in a pipe as this will be indicated acoustically by an increase in flow noise/vibration at the location of the formation and an increase of pressure at the same location. Exothermic reaction of hydrate formation can also be localized trough DTS.

Examples

[0054] As shown in FIG. 4, 6-in. horizontal well facility 400 was constructed and used to model slug flow. Horizontal well facility 400 was upward inclined (+1°). Lateral section 410 was 6-in. ID acrylic pipe and vertical section 420 was 2-in. ID PVC pipe. Compressed air and water were used as fluids. 15 -ft curvature 430 was used to change the flow direction from slightly upward inclined to vertical. The pipe diameter was reduced from 6-in. to 2-in. at the vertical section 420 base. Horizontal well facility 400 operated at ambient temperature and a maximum pressure of 30 psig. Inlet 440 and bubble chamber 450 are shown. The instrumentation allowed monitoring of liquid holdup, pressure gradient and flow patterns. Optical fiber cable was taped on lateral section 410 and vertical section 420. Slugs were generated in bubble chamber 450. Slugs were detected using a DAS apparatus as described above.

Example 1 [0055] In Example 1, only liquid was circulated through horizontal well facility 400 and the liquid was travelling at different velocities. The DAS apparatus was used to measure the Rayleigh backscattering. The example was repeated six times. The acoustic spectrum of the flow is shown in FIG. 10. The acoustic spectrum shows two frequency modes at 120 and 240 Hz.

Example 2

[0056] Example 2 was performed in accordance with Example 1, but bubbles were added into horizontal well facility 400. Different liquid and gas velocities were tested six times. An acoustic spectrogram of the tests of Example 2 is shown in FIG. 11.

Example 3

[0057] Example 3 was performed in accordance with Example 1, but with a single long bubble representing a single slug traveling along the pipe at three different filling portions, i.e., maximum, ½ full, and ¼ full. The progression of the bubble is shown by the white diagonal line. FIG. 12 depicts a waterfall diagram of the results of Example 3. FIG. 13 depicts a spectrogram of the results of Example 3. As is evident from FIG. 12, the area of high noise produces high noise level that are easily noticeable on the DAS Waterfall (black/white stripes). FIG. 12 depicts high noise level as lighter in color. The progression of the slug is visible by the sloping of the white stripe. Slug velocities may be assessed by analyzing the stripe's slope. As shown in FIG. 13 (black arrow), the single bubble is evident.

Example 4

[0058] Example 4 was performed in accordance with Example 1, but with different gas and liquid velocities. Slug position, velocity, length, and frequency were calculated as described hereinabove. FIG. 14 depicts a waterfall diagram of the results of Example 4. FIG. 15 depicts a spectrogram of the results of Example 4. As is evident from FIG. 14, the areas of high noise produce high noise levels that are easily noticeable on the DAS Waterfall (black/white stripes). FIG. 14 depicts high noise level as lighter in color. The progression of the slugs are visible by the sloping of the white stripes. Slug velocities may be assessed by analyzing the stripes' slopes. As shown in FIG. 15, multiple bubbles are evident.

[0059] The foregoing outlines features of several embodiments so that a person of ordinary skill in the art may better understand the aspects of the present disclosure. Such features may be replaced by any one of numerous equivalent alternatives, only some of which are disclosed herein. One of ordinary skill in the art should appreciate that they may readily use the present disclosure as a basis for designing or modifying other processes and structures for carrying out the same purposes and/or achieving the same advantages of the embodiments introduced herein. One of ordinary skill in the art should also realize that such equivalent constructions do not depart from the spirit and scope of the present disclosure and that they may make various changes, substitutions, and alterations herein without departing from the spirit and scope of the present disclosure.