3D near-surface P-wave velocity structure imaging with Distributed Acoustic Sensing and electric hammer source

Distributed Acoustic Sensing(DAS) is an emerging technique for ultra-dense seismic observation, which provides a new method for high-resolution sub-surface seismic imaging. Recently a large number of linear DAS arrays have been used for two-dimensional S-wave near-surface imaging in urban areas. In order to explore the feasibility of three-dimensional(3D) structure imaging using a DAS array, we carried out an active source experiment at the Beijing National Earth Observatory. We deployed a 1 km optical cable in a rectangular shape, and the optical cable was recast into 250 sensors with a channel spacing of 4 m. The DAS array clearly recorded the P, S and surface waves generated by a hammer source. The first-arrival P wave travel times were first picked with a ShortTerm Average/Long-Term Average(STA/LTA) method and further manually checked. The P-wave signals recorded by the DAS are consistent with those recorded by the horizontal components of short-period seismometers. At shorter source-receiver distances, the picked P-wave arrivals from the DAS recording are consistent with vertical component recordings of seismometers, but they clearly lag behind the latter at greater distances.This is likely due to a combination of the signal-to-noise ratio and the polarization of the incoming wave. Then,we used the Tomo DD software to invert the 3D P-wave velocity structure for the uppermost 50 m with a resolution of 10 m. The inverted P-wave velocity structures agree well with the S-wave velocity structure previously obtained through ambient noise tomography. Our study indicates the feasibility of 3D near-surface imaging with the active source and DAS array. However, the inverted absolute velocity values at large depths may be biased due to potential time shifts between the DAS recording and seismometer at large source-receiver distances.

Preliminary report of coseismic surface rupture(part)of Türkiye's M_(W)7.8 earthquake by remote sensing interpretation

Both M_(W) 7.8 and M_(W) 7.5 earthquakes occurred in southeastern Türkiye on February 6,2023,resulting in numerous buildings collapsing and serious casualties.Understanding the distribution of coseismic surface ruptures and secondary disasters surrounding the epicentral area is important for post-earthquake emergency and disaster assessments.High-resolution Maxar and GF-2 satellite data were used after the events to extract the location of the rupture surrounding the first epicentral area.The results show that the length of the interpreted surface rupture zone(part of)is approximately 75 km,with a coseismic sinistral dislocation of 2-3 m near the epicenter;however,this reduced to zero at the tip of the southwest section of the East Anatolia Fault Zone.Moreover,dense soil liquefaction pits were triggered along the rupture trace.These events are in the western region of the Eurasian Seismic Belt and result from the subduction and collision of the Arabian and African Plates toward the Eurasian Plate.The western region of the Chinese mainland and its adjacent areas are in the eastern section of the Eurasian Seismic Belt,where seismic activity is controlled by the collision of the Indian and Eurasian Plates.Both China and Türkiye have independent tectonic histories.

Energy-distributable waterborne acoustic launcher for directional sensing

Highly directional launch and intensity adjustment of underwater acoustic signals are crucial in many areas such as abyssal navigation,underwater signal communication,and detection for marine biology.Inspired by the phenomenon that aquatic animals like dolphins detect and track prey with high resolution,we propose an energy-distributable directional sensing strategy which can achieve parallel needle-like transmitting sound beams with adjustable energy based on out-coupling valley-polarized edge states.The acoustic spin angular momentum and energy flow distribution at different interfaces inside the phononic crystal are provided and they show tight coupling.Furthermore,a sound beam with a width of 20°and an acoustic intensity enhancement factor≈6.6 are observed in the far field.As an application,we show that this device can be used as an acoustic energy distributor.This communication pattern with excellent functionalities and performance provides a desirable idea for high-energy-level directional collimated underwater sensing and underwater acoustic energy distribution.

Reservoir heterogeneity analysis using multi-directional textural attributes from deep learning-based enhanced acoustic impedance inversion:A study from Poseidon,NW shelf Australia

Reservoir heterogeneities play a crucial role in governing reservoir performance and management.Traditionally,detailed and inter-well heterogeneity analyses are commonly performed by mapping seismic facies change in the seismic data,which is a time-intensive task.Many researchers have utilized a robust Grey-level co-occurrence matrix(GLCM)-based texture attributes to map reservoir heterogeneity.However,these attributes take seismic data as input and might not be sensitive to lateral lithology variation.To incorporate the lithology information,we have developed an innovative impedance-based texture approach using GLCM workflow by integrating 3D acoustic impedance volume(a rock propertybased attribute)obtained from a deep convolution network-based impedance inversion.Our proposed workflow is anticipated to be more sensitive toward mapping lateral changes than the conventional amplitude-based texture approach,wherein seismic data is used as input.To evaluate the improvement,we applied the proposed workflow to the full-stack 3D seismic data from the Poseidon field,NW-shelf,Australia.This study demonstrates that a better demarcation of reservoir gas sands with improved lateral continuity is achievable with the presented approach compared to the conventional approach.In addition,we assess the implication of multi-stage faulting on facies distribution for effective reservoir characterization.This study also suggests a well-bounded potential reservoir facies distribution along the parallel fault lines.Thus,the proposed approach provides an efficient strategy by integrating the impedance information with texture attributes to improve the inference on reservoir heterogeneity,which can serve as a promising tool for identifying potential reservoir zones for both production benefits and fluid storage.

A joint absorbing boundary for the multiple-relaxation-time lattice Boltzmann method in seismic acoustic wavefield modeling

Conventional seismic wave forward simulation generally uses mathematical means to solve the macroscopic wave equation,and then obtains the corresponding seismic wavefield.Usually,when the subsurface structure is finely constructed and the continuity of media is poor,this strategy is difficult to meet the requirements of accurate wavefield calculation.This paper uses the multiple-relaxation-time lattice Boltzmann method(MRT-LBM)to conduct the seismic acoustic wavefield simulation and verify its computational accuracy.To cope with the problem of severe reflections at the truncated boundaries,we analogize the viscous absorbing boundary and perfectly matched layer(PML)absorbing boundary based on the single-relaxation-time lattice Boltzmann(SRT-LB)equation to the MRT-LB equation,and further,propose a joint absorbing boundary through comparative analysis.We give the specific forms of the modified MRT-LB equation loaded with the joint absorbing boundary in the two-dimensional(2D)and three-dimensional(3D)cases,respectively.Then,we verify the effects of this absorbing boundary scheme on a 2D homogeneous model,2D modified British Petroleum(BP)gas-cloud model,and 3D homogeneous model,respectively.The results reveal that by comparing with the viscous absorbing boundary and PML absorbing boundary,the joint absorbing boundary has the best absorption performance,although it is a little bit complicated.Therefore,this joint absorbing boundary better solves the problem of truncated boundary reflections of MRT-LBM in simulating seismic acoustic wavefields,which is pivotal to its wide application in the field of exploration seismology.

Imaging shallow structure with active-source surface wave signal recorded by distributed acoustic sensing arrays

Distributed acoustic sensing(DAS) is one recently developed seismic acquisition technique that is based on fiber-optic sensing. DAS provides dense spatial spacing that is useful to image shallow structure with surface waves.To test the feasibility of DAS in shallow structure imaging,the PoroTomo team conducted a DAS experiment with the vibroseis truck T-Rex in Brady’s Hot Springs, Nevada, USA.The Rayleigh waves excited by the vertical mode of the vibroseis truck were analyzed with the Multichannel Analysis of Surface Waves(MASW) method. Phase velocities between5 and 20 Hz were successfully extracted for one segment of cable and were employed to build a shear-wave velocity model for the top 50 meters. The dispersion curves obtained with DAS agree well with the ones extracted from co-located geophones data and from the passive source Noise Correlation Functions(NCF). Comparing to the co-located geophone array, the higher sensor density that DAS arrays provides help reducing aliasing in dispersion analysis, and separating different surface wave modes. This study demonstrates the feasibility and advantage of DAS in imaging shallow structure with surface waves.

Compressed Sensing： Optimized Overcomplete Dictionary for Underwater Acoustic Channel Estimation

Compressed Sensing （CS） offers a method to solve the channel estimation problems for an underwater acoustic system, based on the existence of a sparse representation of the treated signal and an overcomplete dictionary with a set of non-orthogonal bases. In this paper, we proposed a new approach to optimize dictionaries by decreasing the average measure of the mutual coherence of the effective dictionary. A fixed link between the average mutual coherence and the CS perforrmnce is indicated by designing three factors： operating bandwidth, the number of pilot subcarriers, and coherence bandwidth. Both the Orthogonal Matching Pursuit （OMP） and the Basis Pursuit De-Noising （BPDN） are compared to the Dantzig Selector （DS） for different Signal Noise Ratio （SNR） and shown to benefit from the newly designed dictionary. Nurnerical sinmlations and experimental data of an OFDM receiver are used to evaluate the proposed method in comparison with the conventional LeastSquare （LS） estirmtor. The results show that the dictionary with a better condition considerably improves the perforrmnce of the channel estimation.

An underwater acoustic data compression method based on compressed sensing

The use of underwater acoustic data has rapidly expanded with the application of multichannel, large-aperture underwater detection arrays. This study presents an underwater acoustic data compression method that is based on compressed sensing. Underwater acoustic signals are transformed into the sparse domain for data storage at a receiving terminal, and the improved orthogonal matching pursuit(IOMP) algorithm is used to reconstruct the original underwater acoustic signals at a data processing terminal. When an increase in sidelobe level occasionally causes a direction of arrival estimation error, the proposed compression method can achieve a 10 times stronger compression for narrowband signals and a 5 times stronger compression for wideband signals than the orthogonal matching pursuit(OMP) algorithm. The IOMP algorithm also reduces the computing time by about 20% more than the original OMP algorithm. The simulation and experimental results are discussed.

Cooperative Compressive Spectrum Sensing in Cognitive Underw ater Acoustic Communication Networks

Because of the specific of underwater acoustic channel,spectrum sensing entails many difficulties in cognitive underwater acoustic communication( CUAC) networks, such as severe frequency-dependent attenuation and low signal-to-noise ratios. To overcome these problems, two cooperative compressive spectrum sensing( CCSS) schemes are proposed for different scenarios( with and without channel state information). To strengthen collaboration among secondary users( SUs),cognitive central node( CCN) is provided to collect data from SUs. Thus,the proposed schemes can obtain spatial diversity gains and exploit joint sparse structure to improve the performance of spectrum sensing. Since the channel occupancy is sparse,we formulate the spectrum sensing problems into sparse vector recovery problems,and then present two CCSS algorithms based on path-wise coordinate optimization( PCO) and multi-task Bayesian compressive sensing( MT-BCS),respectively.Simulation results corroborate the effectiveness of the proposed methods in detecting the spectrum holes in underwater acoustic environment.

A Robust and Efficient Compressed Sensing Algorithm for Wideband Acoustic Imaging

Wideband acoustic imaging,which combines compressed sensing(CS)and microphone arrays,is widely used for locating acoustic sources.However,the location results of this method are unstable,and the computational efficiency is low.In this work,in order to improve the robustness and reduce the computational cost,a DCS-SOMP-SVD compressed sensing method,which combines the distributed compressed sensing using simultaneously orthogonal matching pursuit(DCS-SOMP)and singular value decomposition(SVD)is proposed.The performance of the DCS-SOMP-SVD is studied through both simulation and experiment.In the simulation,the locating results of the DCS-SOMP-SVD method are compared with the wideband BP method and the DCS-SOMP method.In terms of computational efficiency,the proposed method is as efficient as the DCS-SOMP method and more efficient than the wideband BP method.In terms of locating accuracy,the proposed method can still locate all sources when the signal to noise ratio(SNR)is−20 dB,while the wideband BP method and the DCS-SOMP method can only locate all sources when the SNR is higher than 0 dB.The performance of the proposed method can be improved by expanding the frequency range.Moreover,there is no extra source in the maps of the proposed method,even though the target sparsity is overestimated.Finally,a gas leak experiment is conducted to verify the feasibility of the DCS-SOMP-SVD method in the practical engineering environment.The experimental results show that the proposed method can locate both two leak sources in different frequency ranges.This research proposes a DCS-SOMP-SVD method which has sufficient robustness and low computational cost for wideband acoustic imaging.

A Design of Acoustic Signal Wireless Acquisition System for Stored Grain Pests Based on Compressed Sensing

In order to achieve the acoustic signal distributed acquisition of stored grain pests, a novel acoustic signal acquisition system was presented based on the wireless sensor networks. And the system architecture, hardware configuration, and software were introduced in detail. Considering bandwidth limitation of wireless sensor networks, random sampling algorithm based on the compressed sensing theory was proposed. The developed acoustic signal acquisition system was applied in sampling the crawl acoustic signal of Tribolinm castaneum Herbst adults in granary. Preliminary experimentation indicated the rationality and practicability of the developed system and the proposed algorithm. They can implement the remote, real-time, and reliable wireless transmission for the acoustic signal sampled data of multiple points stored grain pests effectively.

Distributed analysis of forward stimulated Brillouin scattering for acoustic impedance sensing by extraction of a 2nd-order local spectrum

Distributed fiber sensors based on forward stimulated Brillouin scattering(F-SBS)have attracted special attention because of their capability to detect the acoustic impedance of liquid material outside fiber.However,the reported results were based on the extraction of a 1st-order local spectrum,causing the sensing distance to be restricted by pump depletion.Here,a novel post-processing technique was proposed for distributed acoustic impedance sensing by extracting the 2nd-order local spectrum,which is beneficial for improving the sensing signal-to-noise ratio(SNR)significantly,since its pulse energy penetrates into the fiber more deeply.As a proof-of-concept,distributed acoustic impedance sensing along~1630 m fiber under moderate spatial resolution of~20 m was demonstrated.

Three-dimensional analytical solution of acoustic emission or microseismic source location under cube monitoring network

To find the analytical solution of the acoustic emission/microseismic(AE/MS) source location coordinates, the sensor location coordinates were optimized and simplified. A cube monitoring network of sensor location was selected, and the AE/MS source localization equations were established. A location method with P-wave velocity by analytical solutions (P-VAS) was obtained with these equations. The virtual location tests show that the relocation results of analytical method are fully consistent with the actual coordinates for events both inside and outside the monitoring network; whereas the location error of traditional time difference method is between 0.01 and 0.03 m for events inside the sensor array, and the location errors are larger, which is up to 1080986 m for events outside the sensor array. The broken pencil location tests were carried out in the cross section of 100 mm×98 mm, 350 mm-length granite rock specimen using five AE sensors. Five AE sources were relocated with the conventional method and the P-VAS method. For the four events outside monitoring network, the positioning accuracy by P-VAS method is higher than that by the traditional method, and the location accuracy of the larger one can be increased by 17.61 mm. The results of both virtual and broken pencil location tests show that the proposed analytical solution is effective to improve the positioning accuracy. It can locate the coordinates of AE/MS source only using simple four arithmetic operations, without determining the fitting initial value and iterative calculation, which can be solved by a conventional calculator or Microsoft Excel.

Absorption Line Profile Recovery Based on TDLS and MEMS Micro-Mirror for Photoacoustic Gas Sensing

A novel and efficient absorption line recovery technique is presented.A micro-electromechanical systems(MEMS) mirror driven by an electrothermal actuator is used to generate laser intensity modulation through the mirror reflection.Tunable diode laser spectroscopy(TDLS) and photoacoustic spectroscopy(PAS) are used to recover the target absorption line profile which is compared with the theoretical Voigt profile.The target gas is 0.01% acetylene(C2H2) in a nitrogen host gas.The laser diode wavelength is swept across the P17 absorption line of acetylene at 1 535.4 nm by a current ramp,and an erbium-doped fibre amplifier(EDFA) is used to enhance the optical intensity and increase the signal-to-noise ratio(SNR).A SNR of about 35 is obtained with 100 mW laser power from the EDFA.Good agreement is achieved between the experimental results and the theoretical simulation for the P17 absorption line profile.

Remote structural health monitoring with serially multiplexed fiber optic acoustic emission sensors

Development and testing of a serially multiplexed fiber optic sensor system is described.The sensor differs from conventional fiber optic acoustic systems,as it is capable of sensing AE emissions at several points along the length of a single fiber.Multiplexing provides for single channel detection of cracks and their locations in large structural systems. An algorithm was developed for signal recognition and tagging of the AE waveforms for detection of' crack locations,Labora- tory experiments on plain concrete beams and post-tensioned FRP tendons were pcrlormed to evaluate the crack detection capability of the sensor system.The acoustic emission sensor was able to detect initiation,growth and location of the cracks in concrete as well as in the FRP tendons.The AE system is potentially suitable lot applications involving health monitoring of structures following an earthquake.

Analysis, Implementation, and Application of Acoustic and Seismic Arrays

In this paper, we consider the analysis, implementation, and application of wideband sources using both seismic and acoustic sensors. We use the approximate maximum likelihood (AML) algorithm to perform acoustic direction of arrival (DOA). For non-uniform noise spectra, whitening filtering was applied to the received acoustic signals before the AML operation. For short-range seismic DOA applications, one method was based on eigen-decomposition of the covariance matrix and a second method was based on surface wave analysis. Two well-known optimization schemes were used to estimate the source locations from the estimated DOAs at sensors of known locations. Experimental estimation of the DOAs and resulting localizations using the acoustic and seismic signals generated by striking a heavy metal plate by a hammer were reported.

Moment tensor and stress inversion solutions of acoustic emissions during compression and tensile fracturing in crystalline rocks

We investigate the accuracy and robustness of moment tensor(MT)and stress inversion solutions derived from acoustic emissions(AEs)during the laboratory fracturing of prismatic Barre granite specimens.Pre-cut flaws in the specimens introduce a complex stress field,resulting in a spatial and temporal variation of focal mechanisms.Specifically,we consider two experimental setups:(1)where the rock is loaded in compression to generate primarily shear-type fractures and(2)where the material is loaded in indirect tension to generate predominantly tensile-type fractures.In each test,we first decompose AE moment tensors into double-couple(DC)and non-DC terms and then derive unambiguous normal and slip vectors using k-means clustering and an unstructured damped stress inversion algorithm.We explore temporal and spatial distributions of DC and non-DC events at different loading levels.The majority of the DC and the tensile non-DC events cluster around the pre-cut flaws,where macro-cracks later develop.Results of stress inversion are verified against the stress field from finite element(FE)modeling.A good agreement is found between the experimentally derived and numerically simulated stress orientations.To the best of the authors’knowledge,this work presents the first case where stress inversion methodologies are validated by numerical simulations at laboratory scale and under highly heterogeneous stress distributions.

Chiral Seismic Attenuation with Acoustic Metamaterials

We study the analogy between the linear elasticity theory equations and classical Maxwell equation with chiral effects and we propose a new method of an earthquake-resistant design to support conventional aseismic designs using acoustic metamaterials. We suggest a simple and practical method to reduce the amplitude of a seismic wave exponentially. Our device is like an attenuator of a chiral seismic wave. Constructing a cylindrical shell-type waveguide that creates a stop-band for the chiral seismic wave, we can convert the wave into an evanescent wave for some frequency range without touching the building we want to protect.

Primary Quantitative Study on Earthquake Damage Extracted from Remote Sensing Imagery——A Case Study of Seismic Damage in the Urban Area of Dujiangyan due to the M_S8.0 Wenchuan Earthquake

The fast developing remote sensing techniques play an increasingly important role in earthquake emergency response, disaster survey and loss estimation. As there is a lack of quantitative studies on seismic damage based on remote sensing, its practicality in seismic disaster management has usually been questioned. The paper introduces the essential quantitative study idea, the concept of the remote sensing seismic damage index （D1RS） and analysis models, demonstrates the seismic damage indices （ D1G ） of buildings obtained from ground surveying and its quantitative relation to D1RS in Dujiangyan city, Sichuan Province, which was destroyed by the 2008 Wenchuan earthquake with Ms8.0. The primary results show that an obvious relationship exists between the D1RS of buildings obtained from the high resolution satellite or aerial remote sensing images and D1G or the building collapse ratio obtained through ground survey, which suggests that the quantitative study on seismic damage based on remote sensing will provide an effective method for seismic damage survey and loss estimation.

Seismic Data Recovery with Curvelet Bivariate Shrinkage Function Based on Compressed Sensing

Recovery of under-sampled seismic data is a critical problem,in oil and gas exploration,therefore recovery algorithms with iterative shrinkage based on compressed sensing have been recently proposed. However most of these algorithms usually adopt a soft shrinkage function,which assumes that all of the sparse coefficients are independent of each other in curvelet or other domains,little attention has so far been devoted to the inter-dependencies of coefficients. In this paper,the dependencies of parent-child curvelet coefficients of seismic data are exploited by Bayesian estimation,moreover the new seismic data recovery algorithm via curvelet-based bivariate shrinkage function is proposed. First the respective parent-child curvelet coefficients joint distribution models of fully-sampled seismic data and noise signal caused by missing traces are established,then the bivariate shrinkage function according to the Bayesian maximum posterior probability estimation is obtained,finally the Landweber iterative shrinkage algorithm is used in the recovery process.When compared with existing recovery algorithms,it is proved that the proposed algorithm can obtain higher PSNR performance,and maintains the texture details better in events of seismic data