Distributed Acoustic Sensing Measurements Research Articles

A real scale application of a novel set of spatial and similarity features for detection and classification of natural seismic sources from Distributed Acoustic Sensing data

Summary Distributed Acoustic Sensing (DAS) turns a fiber optic into a very dense network of equally-distributed seismic sensors. We focused on the high-density sampling of the seismic wavefield, expressed in strain rates, measured by DAS. Classical approaches used to identify seismic signals rely on the recorded features at one station, but it is difficult to include spatial information in case of dense seismic station networks. This work aims at introducing new spatial and similarity features for seismic event classification suitable to analyze DAS observations. We propose a processing chain based on the XGBoost algorithm and the use of specifically designed spatio-temporal and similarity features for the event classification, and Markov Random Field for the spatial clustering. The methodology is designated to be applied on a continuous stream of DAS observations. We tested our processing chain to detect earthquakes and quarry blasts recorded in the region by permanent seismic networks and included in the RENASS catalog. These events are part of a strain-rate seismic survey carried out during a 3 weeks campaign of DAS measurements along à 91 km fiber optic cable deployed in the central Pyrenees mountains (France). Despite the high anthropogenic activities along the fiber optic path, the proposed method succeeded in detecting earthquakes of magnitude >0.4 and quarry blasts of magnitude >1.0 while limiting the number of false alarms. This performance is particularly noteworthy for low-magnitude events, where detection is accomplished despite a lower signal-to-noise ratio compared to traditional seismometers. The methodology opens the door to real time detection and classification of seismic events measured with long-distance fiber optic systems.

Evaluation of Fluid Distribution and Perforation Erosion in Multistage Fracture Treatment

Summary Fracture monitoring and diagnosis by fiber-optic sensing technology provides invaluable information about stimulation efficiency. This technology becomes more critical for multistage fracturing over long horizontal wells. The combined analysis of distributed temperature sensing (DTS) and distributed acoustic sensing (DAS) measurements has been used to map the fluid distribution during hydraulic fracturing, and fracture volume at the cluster level and at the stage level can be estimated from the analysis. In this paper, based on the interpretation of models for DTS and DAS, we extend the application to fluid containment and stage isolation evaluation. In plug and perforation hydraulic fracturing, when a stage is finished pumping, the stage is isolated by a plug, and the next stage is perforated and then fractured. If the plug is not functioning correctly, fracture fluid enters the previous stage, causing an uneven fluid distribution, and possibly more severe perforation erosion. Both DAS and DTS monitoring can record this phenomenon when it happens. Interpretation models are built to quantify the fluid distribution with the effect of plug leakage included. From DTS measurements, cooling below the stage being completed is counted as the fluid from the current stage. Given this information, the reservoir thermal model can estimate the volume of leakage. From the DAS measurement, we interpret the volume distribution based on frequency band energy to compare with the DTS interpretation. Perforation erosion measurements from a downhole camera are used to confirm the estimation. With this approach, we assess the fluid distribution, plug performance, and the importance of stage isolation on perforation erosion during a multistage fracture treatment. The information can then be used to analyze and optimize completion and fracture treatment design. Field examples are presented in the paper to support the discussion, findings, and conclusions. Based on the results of the fluid distribution estimated, we observed that higher injection rate and larger fluid volumes may create more uniformly distributed fluid between clusters in a stage. When considering communication between stages, the DTS and downhole camera show that there is a correlation between fluid distribution and perforation eroded area. An inconsistency of eroded area and fluid received is observed at toe-side clusters from DTS, DAS, and downhole images. This could be caused by a short erosion time at the toe-side clusters. In the completion design, only a few parameters show a strong impact on fluid distribution and perforation erosion.

Application of Distributed Acoustic Sensing in Geophysics Exploration: Comparative Review of Single-Mode and Multi-Mode Fiber Optic Cables

The advent of fiber optic technology in geophysics exploration has grown in its use in the exploration, production, and monitoring of subsurface environments, revolutionizing the way data are gathered and interpreted critically to speed up decision-making and reduce expense and time. Distributed Acoustic Sensing (DAS) has been increasingly utilized to build relationships in complex geophysics environments by utilizing continuous measurement along fiber optic cables with high spatial resolution and a frequency response of up to 10 KHz. DAS, as fiber optic technology examining backscattered light from a laser emitted inside the fiber and measuring strain changes, enables the performance of subsurface imaging in terms of real-time monitoring for Vertical Seismic Profiling (VSP), reservoir monitoring, and microseismic event detection. This review examines the most widely used fiber optic cables employed for DAS acquisition, namely Single-Mode Fiber (SMF) and Multi-Mode Fiber (MMF), with the different deployments and scopes of data used in geophysics exploration. Over the years, SMF has emerged as a preferred type of fiber optic cable utilized for DAS acquisition and, in most applications examined in this review, outperformed MMF. On the other side, MMF has proven to be preferable when used to measure distributed temperature. Finally, the fiber optic cable deployment technique and acquisition parameters constitute a pivotal preliminary step in DAS data preprocessing, offering a pathway to improve imaging resolution based on DAS measurement as a future scope of work.

Toward a Metadata Standard for Distributed Acoustic Sensing (DAS) Data Collection

Abstract With increasing geophysical applications using distributed acoustic sensing (DAS) technology, there is a need to implement a metadata standard specifically for DAS to facilitate the integration of DAS measurements across experiments and increase reusability. We propose a metadata standard intended primarily for the DAS research community, which fully describes the five key components of a DAS experiment: (1) interrogator; (2) data acquisition; (3) channels; (4) cable; and (5) fiber. The proposed metadata schema, which is the overall structure of the metadata, is hierarchical based, with a parent “overview” metadata block describing the experiment, and two main child branches describing the instrument (i.e., interrogator, photonics setup, and acquisition parameters) and the sensor locations (i.e., cable installation and fiber properties). The metadata schema is designed to be independent of the time-series data so that corrections and updates can be applied to the metadata without having to manipulate large volumes of time-series data. Unique identifiers are used as pointers that map different components within the metadata schema; they also provide a natural basis for the naming convention (i.e., source identifier) of the time-series data in which the time series can be described using identifiers defined by the metadata standard. We advocate for the metadata to be stored in a separate structure from the data itself. The metadata standard is successfully applied to four common scenarios: horizontal direct buried cable, dark fiber, borehole cable, and active survey, and two hypothetical scenarios: multiple interrogators to a single cable, and a single interrogator to multiple cables. Finally, we use GitHub to implement version control for the metadata standard, to enable community collaboration and facilitate sustainable development of the metadata standard, as the DAS technology and application continue to evolve.

DAS sensitivity to heterogeneity scales much smaller than the minimum wavelength

Distributed Acoustic Sensing (DAS) is a photonic technology allowing toconvert fiber-optics into long (tens of kilometers) and dense (every few meters) arrays of seismo-acoustic sensors which are basically measuring the strain of the cable all along the cable. The potential of such a distributed measurement is very important and has triggered strong attention in the seismology community for a wide range of applications. In this work, we focus on the interaction of such measurements with heterogeneities of scale much smaller than the wavefield minimum wavelength. With a simple 2-D numerical modeling, we first show that the effect of such small-scale heterogeneities, when located in the vicinity of the instruments, is very different depending on whether we measure particle velocity or strain rate: in the case of velocity, this effect is small but becomes very strong in the case of the strain rate. We then provide a physical explanation of these observations based on the homogenization method showing that indeed, the strain sensitivity to nearby heterogeneities is strong, which is not the case for more traditional velocity measurements. This effect appears as a coupling of the strain components to the DAS measurement. Such effects can be seen as a curse or an advantage depending on the applications.

New wiggles from old cables: Data processing and imaging considerations

Distributed acoustic sensing (DAS) using fiber-optic cables as sensors has become a standard measurement technique in many industrialized settings. Geophysical applications have been mainly commercialized in the borehole environment. When deployed on the seabed (SB), horizontal analysis of DAS data poses new challenges due to the particularity of the receiver response and characteristics of DAS data. Recent acquisition of a 2D towed-streamer (TS) survey following the path of a communication cable (installed in 1998), which is interrogated continuously throughout the TS acquisition, enables us to jointly analyze SB-DAS and conventional TS data recorded using modern hydrophone streamer from acquisition, through different processing stages up to a migrated image. The SB-DAS recording from the old communication cable enables us to generate excellent P-wave and converted wave (PS) images of the subsurface. However, care is needed when recovering the high spatial frequencies damped by the nature of DAS measurements (which also may depend on the hardware used) and demonstrating the recovery of the signal within the data processing (DP) sequence. Our focus is on the challenges associated with the DP of entrenched marine cables. Given a simple TS processing sequence as a reference, we examine an equivalent recommended practice for signal analysis, DP, and imaging of SB-DAS data.

Observations of Ocean Surface Wave Attenuation in Sea Ice Using Seafloor Cables

AbstractThe attenuation of ocean surface waves during seasonal ice cover is an important control on the evolution of Arctic coastlines. The spatial and temporal variations in this process have been challenging to resolve with conventional sampling using sparse arrays of moorings or buoys. We demonstrate a novel method for persistent observation of wave‐ice interactions using distributed acoustic sensing (DAS) along existing seafloor fiber optic telecommunications cables. DAS measurements span a 36‐km cross‐shore cable on the Beaufort Shelf from Oliktok Point, Alaska. DAS optical sensing of fiber strain‐rate provides a proxy for seafloor pressure, which we calibrate with wave buoy measurements during the ice‐free season (August 2022). We apply this calibration during the ice formation season (November 2021) to obtain unprecedented resolution of variable wave attenuation rates in new, partial ice cover. The location and strength of wave attenuation serve as proxies for ice coverage and thickness, especially during rapidly evolving events.

Low-frequency laboratory measurements of the elastic properties of solids using a distributed acoustic sensing system

In recent decades, low-frequency (LF) experiments based on the forced-oscillation (FO) method have become common practice in many rock physics laboratories for measuring the elastic and anelastic properties of rocks. However, the use of the electronic displacement sensors in traditional acquisition systems of FO devices such as conventional capacitive transducers or strain gauges seriously limits both the efficiency and productivity of LF measurements, and, due to the limited contact area of the displacement sensors with a sample under test, increases the requirements for sample homogeneity. In this paper, we present the first results obtained in the development of a new laboratory method elaborated to measure the elastic properties of solids. The method is a further development of the FO method where traditional data acquisition is replaced by acquisition based on fiber-optic distributed acoustic sensing (DAS) technology. The new method was tested in a laboratory study using two FO setups designed for measurements under uniaxial and confining pressures. The study was carried out on a sample made from polymethyl methacrylate (PMMA) and an aluminium standard, first under uniaxial pressure at FO frequencies of 1, 10, 30, 60 and 100 Hz, and then under confining pressure at an FO frequency of 1 Hz. Both uniaxial and confining pressures were equal to 10 MPa, and the strain in the PMMA sample in all measurements did not exceed 4 × 10-8. The performance of DAS acquisition was compared with the measurements conducted at a strain of 1 × 10-6 using the traditional FO method based on the use of semiconductor strain gauges and the ultrasonic method. The results of the DAS measurements are in good agreement with the FO measurements carried out using semiconductor strain gauges and with the literature data.

Laboratory Small-Strain Stiffness Measurement Using Distributed Acoustic Sensing

Abstract This article introduces a novel method for measuring the small-strain stiffness of materials at the laboratory scale using the emerging technology of distributed acoustic sensing (DAS). This setup involves modifying the traditional free-free resonant column test by wrapping the DAS fiber optic cable around the sample. Tests are conducted using both active and passive sources. Sample resonances measured by DAS demonstrate a high degree of consistency with conventional accelerometer, indicating that DAS is accurate and reliable at the kilohertz scale. To extract the sample resonant frequency from passive sources in laboratory environments (such as cooling fan noise, mixer vibrations, and manual tamping procedure), the auto-correlation method is employed to enhance the amplitude spectrum’s signal-to-noise ratio. The measured transverse resonance excited by passive sources aligns well with that measured under active sources, suggesting the potential for using nonstationary ambient vibrations for long-term monitoring. The study also reveals that impulse-like forces are more suitable for exciting distinguishable resonant frequency compared to continuous but weak ambient vibrations. In a benchmark study, the repeatability of DAS measurements is verified using fabricated samples with known and stable stiffness. The measured constrained and shear moduli are found to be consistent among DAS, accelerometer, and ground-truth values, confirming the robustness and accuracy of the DAS-based free-free resonance column test. To further demonstrate the practical application of the proposed DAS-based system, a 28-day monitoring of cement-stabilized soil is conducted. The small-strain stiffness evolution is successfully captured by DAS, with marginal differences between measurements under active and passive sources. This outcome highlights the potential quality assurance scenarios for DAS because of its distributed properties and rapid data acquisition capabilities.

The Effect of the Method of Downhole Deployment on Distributed Acoustic Sensor Measurements: Field Experiments and Numerical Simulations.

Distributed acoustic sensing (DAS) is a promising technology for seismic data acquisition, particularly in downhole applications. However, downhole DAS measurements can be affected by the deployment method of the fibre-optic cable. These effects were explored in a field trial in two wells (one vertical and one deviated) drilled at the Otway International Test Centre. The trial in the vertical well shows that (1) fibre-optic cables cemented behind the casing provide data of the highest quality due to the best coupling to the formation, and (2) tubing-conveyed cable shows only slightly weaker coupling, but the data quality can be severely degraded by source-generated noise. A cable loosely suspended in the deviated well provided data quality comparable to that of the cemented DAS cable. To better understand the nature of the observed effects, the field experiments were supplemented by numerical modelling with a 1.5D full wave reflectivity algorithm (3D wave propagation in a 1D model), where cement, casing and wellbore were represented by infinite vertical layers. The results show that (1) a cement layer has only a slight effect (<5%) on the DAS amplitude; (2) the vertical strain in a liquid-filled borehole is comparable to that in the formation; and (3) the strain amplitude in the cable is of the same order of magnitude both in the formation and in the fluid. The strain in the cable is zero both when the cable's Poisson's ratio is zero and when the borehole fluid is air. The results confirm the feasibility of borehole DAS measurements with fibre-optic cables suspended in a borehole liquid (but not gas!).

How the Material Characteristics of Optical Fibers and Soil Influence the Measurement Results of Distributed Acoustic Sensing.

Fiber optic distributed acoustic sensing (DAS) technology is widely used in security surveillance and geophysical survey applications. The response of the DAS system to external vibrations varies with different types of fiber optic cable connections. The mechanism of mutual influence between the cable's characteristics and DAS measurement results remains unclear. This study proposed a dynamic model of the interaction between the optical cable and the soil, analyzed the impact of the dynamic parameters of the optical cable and soil on the sensitivity of the DAS system, and validated the theoretical analysis through experiments. The findings suggest that augmenting the cable's bending stiffness 5.5-fold and increasing its unit mass 4.2-fold result in a discernible reduction of the system's response to roughly 0.15 times of its initial magnitude. Cables with lower unit mass and bending stiffness are more sensitive to vibration signals. This research provides a foundation for optimizing vibration-enhanced fiber optic cables and broadening the potential usage scenarios for DAS systems.

A Self-Supervised Deep Learning Approach for Blind Denoising and Waveform Coherence Enhancement in Distributed Acoustic Sensing Data.

Fiber-optic distributed acoustic sensing (DAS) is an emerging technology for vibration measurements with numerous applications in seismic signal analysis, including microseismicity detection, ambient noise tomography, earthquake source characterization, and active source seismology. Using laser-pulse techniques, DAS turns (commercial) fiber-optic cables into seismic arrays with a spatial sampling density of the order of meters and a time sampling rate up to one thousand Hertz. The versatility of DAS enables dense instrumentation of traditionally inaccessible domains, such as urban, glaciated, and submarine environments. This in turn opens up novel applications such as traffic density monitoring and maritime vessel tracking. However, these new environments also introduce new challenges in handling various types of recorded noise, impeding the application of traditional data analysis workflows. In order to tackle the challenges posed by noise, new denoising techniques need to be explored that are tailored to DAS. In this work, we propose a Deep Learning approach that leverages the spatial density of DAS measurements to remove spatially incoherent noise with unknown characteristics. This approach is entirely self-supervised, so no noise-free ground truth is required, and it makes no assumptions regarding the noise characteristics other than that it is spatio-temporally incoherent. We apply our approach to both synthetic and real-world DAS data to demonstrate its excellent performance, even when the signals of interest are well below the noise level. Our proposed methods can be readily incorporated into conventional data processing workflows to facilitate subsequent seismological analyses.

Observation of Shallow Slow Earthquakes by Distributed Acoustic Sensing Using Offshore Fiber‐Optic Cable in the Nankai Trough, Southwest Japan

AbstractOff Cape Muroto area, along the Nankai Trough in southwest Japan, is a typical area with adjacent occurrences of slow and megathrust earthquakes. High‐resolution monitoring of slow earthquakes is necessary to understand tectonic conditions. In the off Muroto area, distributed acoustic sensing (DAS) measurement, which provides high‐density strain data, has been conducted using offshore fiber‐optic cable. We observed shallow tremors, a type of slow earthquakes, using DAS measurement for the first time. The characteristics of the tremor signals recorded by DAS were longer durations than those recorded in seismographs and composed of several phases with apparent velocities of several hundreds of m/s to several km/s that are coherent only in tens of meters. By combining DAS and seismograph data, we located these tremors around a subducted seamount peak. Therefore, spatial relationship between slow earthquakes and structural characteristics is suggested. This is a pioneering study of slow earthquake observation using DAS.

Distributed acoustic sensing for detecting near surface hydroacoustic signals.

Distributed acoustic sensing (DAS) is a technology that turns a fiber-optic cable into an acoustic sensor by measuring the phase change of backscattered light caused by changes in strain from an acoustic field. In October 2022, 9 days of DAS and co-located hydrophone data were collected in the Puget Sound near Seattle, WA. Passive data were continuously recorded for the duration and a broadband source was fired from several locations and depths on the first and last days. This dataset provides comparisons between DAS and hydrophone measurements and demonstrates the ability of DAS to measure acoustics signals up to ∼700 Hz.

300 km ultralong fiber optic DAS system based on optimally designed bidirectional EDFA relays

Optical fiber distributed acoustic sensing (DAS) based on phase-sensitive optical time domain reflectometry (φ-OTDR) is in great demand in many long-distance application fields, such as railway and pipeline safety monitoring. However, the DAS measurement distance is limited by the transmission loss of optical fiber and ultralow backscattering power. In this paper, a DAS system based on multispan relay amplification is proposed, where the bidirectional erbium-doped fiber amplifier (EDFA) is designed as a relay module to amplify both the probe light and the backscattering light. In the theoretical noise model, the parameters of our system are carefully analyzed and optimized for a longer sensing distance, including the extinction ratio (ER), span number, span length, and gain of erbium-doped fiber amplifiers. The numerical simulation shows that a bidirectional EDFA relay DAS system can detect signals over 2500 km, as long as the span number is set to be more than 100. To verify the effectiveness of the scheme, a six-span coherent-detection-based DAS system with an optimal design was established, where the cascaded acoustic-optic modulators (AOMs) were used for a high ER of 104 dB. The results demonstrate that the signal at the far end of 300.2 km can be detected and recovered, achieving a high signal-to-noise ratio of 59.6 dB and a high strain resolution of 51.8pε/Hz at 50 Hz with a 20 m spatial resolution. This is, to the best of our knowledge, a superior DAS sensing distance with such a high strain resolution.

Degradation Analysis of Single-Mode and Multimode Fibers in a Full-Scale Wellbore and Its Impact on DAS and DTS Measurements

Distributed fiber optic sensors (DFOS) are viewed as a promising technology for efficient, cost-effective, and non-intrusive real-time monitoring for a variety of applications. The chemical passivity, non-magnetic interference behavior, and ability to acquire continuous measurements at high-spatial resolution have made DFOS very attractive for in-situ measurement of temperature, strain, vibration, etc. The accuracy of the measured parameter by the DFOS is highly dependent on the strength and quality of the optical signal returning from the point of interest. The signal degradation in DFOS results from optical losses due to attenuation, absorption, scattering, bending, dispersion, and coupling. This study analyzes the degradation observed in both the single-mode and multimode fibers installed in a 1574 mdeep wellbore for acquiring distributed acoustic sensing (DAS) and distributed temperature sensing (DTS) data, respectively. The degradation was unexpected as it was observed within three years of DFOS installation in an experimental, non-producing well that contains non-corrosive fluids and operates in a low-temperature (<54.4 °C) and low-pressure (<3500 psi or 24131 kPa) environment. A root-cause analysis was performed to investigate the cause of this degradation using time-lapse optical loss measurements acquired at different wavelengths using an optical time-domain reflectometer. Degradation of the multimode fiber was also examined by the time-lapse analysis of the Raman backscatter that is used for DTS measurement. Based on the investigation, microbending was found to be the main cause of the observed degradation. Its impact on the quality of the DAS and DTS measurements was also analyzed both qualitatively and quantitively. Recommendations for minimizing degradation are presented.

Using distributed acoustic sensing for ocean ambient sound analysis

Distributed acoustic sensing (DAS) is a technique that utilizes the back scattering in fiber optic cables to densely sample the strain rate in both space and time. This technique has been widely demonstrated as a powerful tool for seismic sensing, but the efficacy of submerged, under-sea cables for ocean acoustic sensing remains underexplored. The ocean observatories initiative (OOI) conducted a distributed acoustic sensing experiment in November of 2021, where two of the fiber optic cables continuously recorded the strain rate for four days. In this talk, the ambient sound field recorded by the OOI DAS experiment will be explored. A statistical comparison of hydrophone measurements and DAS measurements will be presented. Additionally, the possibility of using ocean ambient sound techniques, such as ambient noise interferometry will be explored and compared to hydrophone analysis. [Work supported by ONR.]

Full-Waveform Inversion of Fiber-Optic VSP Data From Deviated Wells

Distributed acoustic sensing (DAS) technology permits measuring the strain or strain rate along a fiber deployed in a well due to seismic wave propagation. In vertical seismic profiling (VSP) acquisitions where seismic waves are excited at the surface and measured by subsurface receivers in the well, the DAS serves as a fast alternative to a conventional geophone array. Like conventional multicomponent VSP velocity measurements, DAS VSP data contain information about the subsurface properties that are encoded in seismic events and attributes such as compressional and shear direct arrivals, reflections, converted modes, multiples, and amplitude and phase variations. These seismic data can be used to obtain elastic properties of the formation and characterize the reservoir. Full-waveform inversion (FWI) extracts the elastic properties of the formation from the seismic wavefield by minimizing the misfit between real measurements and synthetically modeled wavefields. The synthetically generated wavefields are obtained by solving partial differential equations that accurately model the physical phenomena of the real waveforms. For conventional geophone sensors, FWI is formulated for the particle velocity field. In this paper, we present a formulation of the modeling and inversion specifically for DAS measurements as an averaged strain along the fiber. The algorithm does not require converting the data to velocities. The gradient of the misfit function, by adjoint formulation, is a cross correlation in time of the forward-propagated wavefield and backward-propagated residuals injected from the receivers. For conventional sensors, the residuals are injected as force terms, but for DAS data, the residuals are averaged in space first and then injected as moment tensor sources with radiation patterns determined by the well deviation. For multi-offset in-plane and out-of-plane VSP acquisitions, a two-dimensional (2D) algorithm has been developed that inverts for a 2D distribution of elastic medium properties and includes three-dimensional (3D) well deviation effects. This paper will present the results of applying the inversion to real multi-offset, highly out-of-plane VSP fiber data acquired in a deviated well. Simulations confirm that the well trajectory has a considerable impact on the data amplitude and must be included in the modeling and inversion to reproduce amplitude variations. The inverted compressional and shear velocities agree well with the reference model based on sonic data. Another real data example is a multi-offset walk-above acquisition where a targeted domain is located below a deviated portion of the well. The inversion matches reflections and produces an image in the target area.

Case study on amplitude and phase response comparison between DAS and 3C geophone VSP surveys at a test site in Japan

Distributed acoustic sensing (DAS) is an effective tool for seismic surveys and is widely used as the preferred sensor for acquiring dense Vertical Seismic Profile (VSP). However, DAS has some disadvantages compared to conventional geophone acquisition, such as single-component data, sensor directivity pattern, low S/N, etc. To apply DAS data to VSP processing, it is important to understand the characteristics of DAS measurements. This study first examined DAS and geophone responses for a VSP survey in a 1D earth model. The relationship of signal amplitude as a function of incident angle and phase shift between wavelets was confirmed. Next, we validated this relationship in a walk-away VSP survey, which was conventionally applied to monitor geological CO2 storage. The survey was carried out at a test site in Japan. We obtained both three-component (3C) geophone and DAS data using a single-mode fiber installed behind a casing. The observed amplitudes of the first P-waves by DAS and geophone showed very good agreement with the theoretical expectations. Finally, we performed imaging using acquired DAS data following the workflow for conventional VSP processing. These basic behaviors of DAS are useful for designing further analyses, such as VSP in deviated wells and full waveform inversion.

Extracting high-resolution, multi-mode surface wave dispersion data from distributed acoustic sensing measurements using the multichannel analysis of surface waves

Distributed acoustic sensing (DAS) is a rapidly expanding tool to sense wave propagation and system deformations in many engineering applications. In terms of site characterization, DAS presents the ability to make dynamic strain measurements at scales (e.g., kilometers) and spatial resolutions (e.g., meters) that were previously unattainable with traditional measurement technologies. In this study, we use both vibroseis truck and sledgehammer sources to demonstrate that DAS can be used to make multichannel analysis of surface waves (MASW) dispersion measurements that are equivalent in quality to geophones when: (a) a tight-buffered or strain-sensing fiber-optic cable is used, (b) the cable is buried in a shallow trench to enhance coupling, and (c) short gauge lengths and small channel separations are used. We analytically demonstrate the impact gauge length has on DAS measurements in terms of phase and amplitude for off-end MASW surveys. We further show that the choice of waveform units (i.e., phase, strain, strain-rate, displacement, velocity) do not impact the dispersion results when frequency-dependent normalization is applied to the dispersion images. Finally, we show that shear wave velocity profiles recovered from the DAS data using an uncertainty-consistent, multi-mode inversion agree favorably with cone penetration tests performed at the site. This study demonstrates that DAS, when appropriate considerations are made, can be used instead of traditional sensors (i.e., geophones) for making high-resolution, multi-mode measurements of surface wave dispersion data using the MASW technique.