Wave Seismic Data Research Articles

Prediction of shale bedding-parallel crack density based on the SH-SH wave inversion of the VTI media

Bedding-parallel cracks relate to hydrocarbon accumulation and can be beneficial for hydraulic fracturing. The prediction of bedding-parallel crack density (BCD) from seismic data is difficult because the development of bedding-parallel cracks has limited effects on the velocities and density of subsurface formation. Well logs of the Qingshankou (K2qn) shales in the Songliao Basin, northeast China, reveal that the target formations represent extremely strong seismic anisotropy (> 40%), and the magnitude of S-wave anisotropy highly relates to the density of bedding-parallel cracks (up to 2500 m−1). We present a novel BCD prediction method using the reflected seismic shear wave. The S-wave anisotropy parameter γ is first inverted from the SH-SH wave by using a stepwise inversion method based on a new shear wave reflection coefficient approximation. Furthermore, the highly correlated rock-physics relationship between BCD and the anisotropy parameter γ facilitates accurate BCD estimation. Field data application on a real seismic shear wave data set acquired from the study area demonstrates the viability of the proposed method. The investigation provides a useful tool for the characterization of ‘sweet-spots’ of shale-oil reservoir formation.

Seismic shear wave noise suppression and application to well tie

Abstract Seismic shear waves have been employed in oil and gas exploration for decades. A 2D seismic shear wave inline was acquired in Sanhu area, located in the Qaidam Basin in western China. Although the acquired shear wave data exhibits high resolution and comparable bandwidth to the compressional wave, it is contaminated by various types of noise, including linear noise, single-frequency noise, and especially internal multiples. Internal multiples seriously compromise the primary reflections at both near-offset and far-offset and are difficult to be suppressed. This paper presents a case study of noise attenuation for the seismic shear wave. Firstly, single-frequency noise and linear noise are attenuated through filtering methods. Then, two methods (the Radon transform and the frequency-wavenumber (F-K) filtering) are evaluated for their effectiveness in multiple suppression and amplitude preservation. The results indicate that both methods successfully reduce long-period multiples at far-offset, enhancing the signal-to-noise ratio. We show that F-K filtering retains the characteristic ‘strong-weak-strong’ amplitude variation in the SV-SV wave data gather, making it preferable for subsequent AVO (amplitude variation with offset) analysis and inversion. Finally, a wave-equation-based MSI (multiple suppression inversion) method is used to suppress near-offset internal multiples. This involves iteratively predicting internal multiples and adaptively subtracting them from the original data. Stacked sections of different offsets are compared to demonstrate de-multiple result, and the result is also validated by the improvement of well calibration with the seismic shear wave data.

Analyzing the seismic response characteristics of P, SV, and SH waves to reservoir parameters using physical modeling

Changes in reservoir parameters cause differences in seismic response characteristics, which can reflect the formation lithology and fluids. We conduct seismic physical modeling and seismic response characteristic analysis of P, SV, and SH wavefields. A seismic physical model is developed in the laboratory, which included several groups of sandstone blocks for simulating reservoir parameters, such as different fluid and clay content. Two-dimensional wavefield data of P-P, SV-SV, and SH-SH waves are acquired and processed in the laboratory. Compared with P waves, SV and SH waves are insensitive to pore fluids, and the SH stack profile is superior to the SV stack profile. The reflection events at the interface are slightly better for the SH-wave section than for the SV-wave section. The reflection coefficient of P waves varies greatly on amplitude variation with angle (AVA) gathers and is significantly influenced by factors such as fluids. The variation in the SV-wave reflection coefficient on AVA gathers is not as significant as that of P waves, and SV and SH waves are more conducive in identifying whether the block contained clay. The SH wave is more reliable for seismic imaging. Overall, this study can assist in combining different seismic wave data for better hydrocarbon identification and reservoir description.

Improvement and Application of Hale’s Dynamic Time Warping Algorithm

Due to the different generation and propagation mechanisms of P- and S-waves, there may be significant differences in the seismic data collected by the two, which poses a great obstacle to the time domain matching of P- and S-waves in multiwave exploration. Furthermore, the quality and accuracy of the matching effect will directly affect the subsequent multiwave joint inversion and interpretation effect. Therefore, the study of P and S-wave-matching methods plays a crucial role in seismic exploration. In 2013, Hale improved the classical Dynamic Time Warping (DTW) algorithm applied to solve the problem of speech recognition, and obtained the DTW algorithm suitable for solving the matching of P-waves and S-waves. The seismic wave-matching results generated by this algorithm are horizontal discontinuous (different trajectories) and need further processing. This study analyses the algorithm based on simulations of seismic waves using Ricker wavelets. In response to existing problems, this paper proposes strategies to improve the DTW algorithm. The algorithm in this study significantly improved the continuity of the registration results of the actual seismic wave data in the horizontal direction (different traces).

Application of seismic refraction and MASW methods for investigating the Spillway Fault trace along the western side of the Aswan High Dam, Egypt

AbstractAn earthquake of local magnitude ML = 4.6 occurred on November 7, 2010, 4.5 km northwest of the Aswan High Dam on the Spillway Fault. In the Aswan metropolitan region this earthquake was felt intensely. As no surface rupture was found, the focal mechanism and the distribution of seismic activity was one of the tools used for finding fault dimensions. The composite fault-plane solutions for the observed events on the Spillway Fault showed a left lateral strike-slip faulting with normal-fault component striking NNW-SSE. Also, remote sensing techniques were applied for the detection and identification of the geomorphology and geometry of the Spillway Fault. In this research, sub-surface layers and structures are delineated utilizing near-surface seismic techniques. Furthermore, the area’s supposed path and position of the Spillway Fault are also investigated. Two active seismic techniques, Seismic Refraction and Multi-Channel Analysis of Surface Waves (MASW), are utilized for recording near-surface seismic wave data at 9 sites. The seismic refraction profiles are conducted as a 2D cross-section on the trace of the detected Spillway Fault in the study area to evaluate the maximum depth of penetration of the P-wave for fault investigation. The constructed 2D seismic and structural sections from P-wave results show that the obtained average depth of about 30 m. In addition, the estimated P-wave velocities extend from 600 m/s to over 6500 m/s. Some lateral variation in the seismic wave velocities in all layers may represent fault zones. Moreover, the 1D MASW technique is conducted to estimate the velocities of the shear wave for the upper 30 m (Vs30) to provide the site classes and soil characteristics along both sides of the detected Spillway Fault trace in the study area. The calculated Vs30 values emphasized the idea of the existence of a normal dip-slip fault trace which divides the study area into two different lithological parts. The first part is located on the eastern side and characterized by almost class B (hard rock, according to NEHRP classification), while the other part is located to the west, and shows almost class type C (denoted as dense soil and soft rock soil).

Influence of water on the thermoelastic properties of Fe bearing ringwoodite: A first-principles study

Using first-principles density functional theory (DFT), we model the thermoelastic properties of hydrated ringwoodite (γ-(Fe, Mg)2SiO4), a potential water reservoir in the Earth's mantle transition zone (MTZ). Our calculations indicate that hydration, in general, leads to a reduction in the sound wave velocity of ringwoodite. However, increased pressure tends to suppress this reduction. For our 1.56 wt% H2O containing ringwoodite model, we find that the suppression is so large that at pressure and temperature (P-T) conditions relevant to the lower part of the MTZ the sound wave velocities for the hydrous (1.56 wt% H2O) ringwoodite become very similar to that of the anhydrous ringwoodite. However, when the water concentration is increased to 3.3 wt%, the pressure-induced suppression of the velocity reduction due to hydration is not so significant. We have given a plausible explanation for the same on the basis of the electronic structure of the hydrous ringwoodite models. We conclude that in the lower part of the MTZ, seismic wave data is sufficiently robust to detect regions of very high-water content (∼3.3 wt%). However, if the water concentration is less than 1.56 wt%, sound wave velocities may not be able to precisely detect the state of hydration of the MTZ.

Applying the BeiDou Navigation Satellite System in the acquisition of the coseismic deformation and the high-frequency dynamic displacement of the 2021 MW 7.4 Maduo earthquake

SUMMARY This study acquires the coseismic deformation field and the high-frequency dynamic displacement of the MW 7.4 earthquake that occurred in Maduo, China, on 2021 May 22, based on the BeiDou Navigation Satellite System (BDS), and the comparison with the results obtained by the Global Positioning System (GPS) reveals that the two systems are certain differences in their ability to acquire the coseismic deformation field. The maximum difference in the horizontal coseismic deformation is <5 mm, and the maximum difference in the vertical coseismic deformation is 8.7 mm. The dynamic displacement waveforms of the 2021 MW 7.4 Maduo earthquake acquired by BDS and GPS are very similar, which confirms that BDS can acquire ground-shaking images with an accuracy comparable to that of GPS. Based on the empirical relationship equation of the peak ground displacement (PGD) and moment magnitude (MW), this study verifies and calculates both the MW of the 2021 MW 7.4 Maduo earthquake and the error and finds that the MW can be quickly and accurately obtained by using the empirical PGD and MW equations, and this MW value can be used as a supplementary means of calibrating the MW of the large earthquake early warning systems, which can be quickly determined by seismic wave data. Finally, by comparing the slip distributions inverted from the BDS and GPS coseismic deformation fields, this study finds that BDS is equally effective as GPS.

Waveform Imaging Based on Linear Forward Representations for Scalar Wave Seismic Data

The current reverse-time migration, which is based on wave equations for imaging wavefields, employs an imaging formula derived from Claerbout’s imaging principle. This imaging formula is only valid for plane waves with small incident angles on the perfectly flat reflecting surface. However, the complexity of seismic wave propagation may lead to situations that do not meet this requirement. Therefore, this paper divides the subsurface into local scattering and reflecting bodies. It proposes linear forward representations for scattering and reflection data based on perturbations in the physical parameters and wave impedance, respectively. To further describe the effect on the reflecting body boundary, the local reflection coefficient is defined and the linear forward representation for the reflection data based on it is obtained. After that, the proposed linear forward representations are used as the forward equations for the linear inverse of the seismic data, and the seismic data waveform imaging method is developed based on linear inversion theory. At the same time, the specific waveform imaging calculation formulas for scalar wave scattering data and scalar wave reflection data are provided and validated via numerical experiments. Compared with the current reverse-time migration, waveform migration not only has the correct phase and higher resolution in theory but also does not increase the computational complexity. To some extent, it improves the deficiencies of the current structural imaging and provides a basis for subsurface lithological imaging.

A Novel Approach for Earthquake Prediction Using Random Forest and Neural Networks

INTRODUCTION: This research paper presents an innovative method that merges neural networks and random forest algorithms to enhance earthquake prediction.
 OBJECTIVES: The primary objective of the study is to improve the precision of earthquake prediction by developing a hybrid model that integrates seismic wave data and various extracted features as inputs.
 METHODS: By training a neural network to learn the intricate relationships between the input features and earthquake magnitudes and employing a random forest algorithm to enhance the model's generalization and robustness, the researchers aim to achieve more accurate predictions. To evaluate the effectiveness of the proposed approach, an extensive dataset of earthquake records from diverse regions worldwide was employed.
 RESULTS: The results revealed that the hybrid model surpassed individual models, demonstrating superior prediction accuracy. This advancement holds profound implications for earthquake monitoring and disaster management, as the prompt and accurate detection of earthquake magnitudes is vital for effective mitigation and response strategies.
 CONCLUSION: The significance of this detection technique extends beyond theoretical research, as it can directly benefit organizations like the National Disaster Response Force (NDRF) in their relief efforts. By accurately predicting earthquake magnitudes, the model can facilitate the efficient allocation of resources and the timely delivery of relief materials to areas affected by natural disasters. Ultimately, this research contributes to the growing field of earthquake prediction and reinforces the critical role of data-driven approaches in enhancing our understanding of seismic events, bolstering disaster preparedness, and safeguarding vulnerable communities.

Temporal evolution of entropy and chaos in low amplitude seismic wave prior to an earthquake

This study investigates the temporal changes of entropy and chaos in low-amplitude continuous seismic wave data prior to two moderate-level earthquakes. Specifically, we examine seismic signals before and during the Istanbul-Turkey earthquake of September 26, 2019 (M = 5.7), and the Duzce-Turkey earthquake of November 17, 2021 (M = 5.2), which occurred near the Marmara Sea region on the north-Anatolian fault line. We aim to identify changes in complexity and chaotic characteristics in the pre-earthquake seismic waves and explore the possibility of earthquake forecasting minutes before an earthquake. To accomplish this, we utilize windowed scalogram entropy and sample entropy methods and compared the results with Lyapunov exponents and windowed scale index. Our findings indicate that measuring the temporal change of entropy using windowed scalogram entropy is sensitive to the change in complexity due to the frequency shifts during the weak ground motion approaching an earthquake.On the other hand, Lyapunov exponents and sample entropy appear more effective in their response to the change in complexity and chaotic characteristics due to the change in the signal amplitude. Additionally, the windowed scale index can detect temporal fluctuations in the aperiodicity of the signal. Overall, our results suggest that all four methods can be valuable in characterizing complexity and chaos in short-time pre-earthquake seismic signals, differentiating earthquakes, and contributing to the development of earthquake forecasting techniques.

Coseismic Gravity Changes and Crustal Deformation Induced by the 2018 Fiji Deep-Focus Earthquake Observed by GRACE and GRACE-FO Satellites

Earthquakes at depths of ≥300 km are generally called deep-focus earthquakes. Only two deep-focus earthquakes with Mw 8.0 or more have occurred in this century—the 2013 Okhotsk earthquake (Mw 8.3) and the 2018 Fiji earthquake (Mw 8.2) on 19 August 2018. However, the 2018 Fiji earthquake was only reported on seismographs, and the related crustal deformations were not observed by the Global Navigation Satellite System because the observation network did not exist around the epicenter. This study analyzed the time series of gravity data observed by the Gravity Recovery And Climate Experiment (GRACE) and its successor, GRACE Follow-On, and detected the spatial distribution of coseismic gravity changes mainly due to crustal deformation by the 2018 Fiji earthquake. The results in this study were not consistent with the numerical calculation of gravity changes when using the fault parameters estimated by the data of seismic waves. Thus, numerical calculations were used to construct a uniform slip rectangle fault model to explain coseismic gravity changes and provide a spatial distribution map of crustal deformation. However, this fault model is only based on gravity changes; thus, new research combining satellite gravimetry and seismic wave data will be necessary in the future.

EPM–DCNN: Earthquake Prediction Models Using Deep Convolutional Neural Networks

ABSTRACT Earthquakes usually cause severe injuries and loss of life, so researchers have developed various methods to predict them. However, the prediction accuracies of these methods are not satisfactory. Unlike most artificial intelligence earthquake prediction methods using earthquake catalogs or seismic wave data, this article proposes three earthquake prediction models based on deep convolutional neural network-based (EPM-DCNN) using 11 continuous earthquake precursory observation item data, including fluid, geomagnetic, and deformation disciplines. To enhance the accuracy of the location prediction of earthquakes, we propose a method to divide the research area into six prediction blocks based on the K-means++ clustering algorithm using the epicenter of historical earthquakes. Using earthquake precursory observation time-series data from 1 January 2015 to 31 December 2018, we construct approximately 34,000 samples by sliding a fixed window size. Each sample is subdivided into 13 categories by combining the magnitude label and prediction block label. The experimental results show that EPM–DCNN B proposed in this article has an accuracy of 99.0% and a recall of 99.8%, which demonstrates the effectiveness of EPM–DCNN for seismic prediction compared to several state-of-the-art baselines.

Reverse Time Migration Imaging Using SH Shear Wave Data

In this paper, we discussed the reverse time migration imaging of compressional wave (P-wave) and horizontally polarized shear wave (SH shear wave) seismic data, together with P- and SH shear wave constrained velocity model building. In the Sanhu area in Qaidam Basin, there are large areas of gas clouds, which leads to poor P-wave seismic imaging. The P and SH shear wave seismic data of a co-located survey line with the same acquisition geometry were used to access their imaging capability using reverse time migration. We first estimated the change in P-wave and SH shear wave velocity ratio using pre-stack time migration (PSTM) for constraining the overall depth domain velocity model. Additionally, we then used an eighth-order finite difference scheme for P-wave reverse time migration on a variable grid and used the sixth-order combined compact difference (CCD) wave field simulation method for SH shear wave reverse time migration on a regular grid. The results show that the constrained velocity model produces a good match in the overall geological structure shown in the P-wave and SH shear wave reverse time migration results. However, in the gas cloud areas, SH shear wave reverse time migration has obvious imaging advantages, which can clearly image the structure inside the gas clouds.

Newly formed craters on Mars located using seismic and acoustic wave data from InSight

Meteoroid impacts shape planetary surfaces by forming new craters and alter atmospheric composition. During atmospheric entry and impact on the ground, meteoroids excite transient acoustic and seismic waves. However, new crater formation and the associated impact-induced mechanical waves have yet to be observed jointly beyond Earth. Here we report observations of seismic and acoustic waves from the NASA InSight lander’s seismometer that we link to four meteoroid impact events on Mars observed in spacecraft imagery. We analysed arrival times and polarization of seismic and acoustic waves to estimate impact locations, which were subsequently confirmed by orbital imaging of the associated craters. Crater dimensions and estimates of meteoroid trajectories are consistent with waveform modelling of the recorded seismograms. With identified seismic sources, the seismic waves can be used to constrain the structure of the Martian interior, corroborating previous crustal structure models, and constrain scaling relationships between the distance and amplitude of impact-generated seismic waves on Mars, supporting a link between the seismic moment of impacts and the vertical impactor momentum. Our findings demonstrate the capability of planetary seismology to identify impact-generated seismic sources and constrain both impact processes and planetary interiors. Impact-induced acoustic and seismic wave events on Mars recorded by the InSight lander’s seismometer have been traced to fresh craters observed in spacecraft imagery.

Full wave seismic exploration technology

Reflected wave seismology has the following defects: the acquisition design is based on the assumption of layered media, the signal processing suppresses weak signals such as diffracted wave and scattered wave, and the seismic wave band after the image processing is narrow. They limit the full utilization of broadband raw data. The concept of full wave seismic exploration is redefined based on the idea of balanced utilization of reflected wave, diffracted wave and scattered wave information, its characteristics and adaptive conditions are clarified. A set of key technologies suitable for full wave seismic exploration are put forward. During seismic acquisition period, it is necessary to adopt multi geometry, i.e. embed small bin, small offset and small channel interval data in conventional geometry. By discretizing of common midpoint (CMP) gathers, small offset with high coverage, the weak signals such as diffracted wave and scattered wave in the raw seismic data can be enhanced. During seismic processing, the signal and noise in the original seismic data need to be redefined at first. The effective signals of seismic data are enhanced through merging of multi-geometry data. By means of differential application of data with different bin sizes and different arrangement modes, different regimes of seismic waves can be effectively decomposed and imaged separately. During seismic interpretation stage, making the most of the full wave seismic data, and adopting well-seismic calibration on multi-scale and multi-dimension, the seismic attributes in multi-regimes and multi-domains are interpreted to reveal interior information of complex lithology bodies and improve the lateral resolution of non-layered reservoirs.

Adjoint Waveform Tomography of South America

AbstractWe used 3D spectral‐element seismic wave simulations and data from 112 earthquakes and 1,311 seismic stations, totalizing 20,884 unique ray paths, to construct an adjoint waveform tomographic model of South America. We performed 23 conjugate‐gradient iterations using exponentiated phase (EP) measurements. Our final model (SAAM23, South American Adjoint Model—iteration 23) shows a 50% decrease in the EP misfit relative to its 3D starting model. We further assessed the phase misfit reduction by using cross‐correlation travel‐time measurements of 53 earthquakes not included in the inversion. We estimated SAAM23 resolution using point‐spread function tests and density coverage analysis. The Nazca Slab is well imaged and is shown to be continuous in the 300–500 km depth range. Beneath northern South America, the slab traverses the mantle transition zone and continues into the lower mantle. In the central and southern part of South America, the slab appears to flatten near the 650 km discontinuity before continuing into the lower mantle. In the stable Precambrian platform, both cratons (Amazonian and São Francisco), as well as covered cratonic blocks beneath the intracratonic Paraná and Parnaíba basins (Paranapanema and Parnaíba, respectively), show high velocities at lithospheric depths. The seismic Lithosphere/Asthenosphere boundary (LAB) agrees well with published values obtained by S‐wave receiver functions. In the Amazonian craton, the positive lithospheric S‐wave velocity anomalies and LAB depth increase with the average age of the geochronological provinces. No lithospheric high‐velocity anomalies were found beneath the Río de la Plata Craton.

Assessment Tingkat Kerentanan Bangunan Bertingkat di Kampus Universitas Negeri Padang Menggunakan Gelombang Rayleigh

In 2009 the city of Padang experienced an earthquake with a magnitude of 7.9 SR which resulted in damage to many high-rise buildings in the city of Padang, including multi-storey buildings on the UNP campus. Over time the multi-storey building will experience a decrease in quality so it is necessary to check the quality of the building itself. In this study, the author chose one of the multi-storey buildings on the UNP campus to be the object of research, namely the Faculty of Economics building. The purpose of this study was to determine the level of vulnerability of the Faculty of Economics building by checking without damaging it using a microtremor device. The research method was carried out by recording the frequency of the soil and buildings under study using a microtremor device. The primary data of this research is in the form of seismic wave data which will be processed using Matlab and Bido 2.02 software to obtain the natural frequency value of the building itself. Based on the data processing that has been done, the resonance index of the Faculty of Economics UNP building ranges from 584.81%-1054.23% so it is in the low category. The vulnerability index of the UNP Faculty of Economics building ranges from 7.07–29.21 with the highest value on the 1st floor so that the 1st floor is the most vulnerable floor.

A high-resolution dispersion imaging method of seismic surface waves based on chirplet transform

Abstract The surface-wave analysis method is widely adopted to build a near-surface shear-wave velocity structure. Reliable dispersion imaging results form the basis for subsequent picking and inversion of dispersion curves. In this paper, we present a high-resolution dispersion imaging method (CSFK) of seismic surface waves based on chirplet transform (CT). CT introduces the concept of chirp rate, which could focus surface-wave dispersion energy well in time-frequency domain. First, each seismic trace in time-distance domain is transformed to time-frequency domain by CT. Thus, for each common frequency gather, we obtain a series of 2D complex-valued functions of time and distance, which are called pseudo-seismograms. Then, we scan a series of group velocities to obtain the slanting-phase function and perform a spatial Fourier transform on the slanting-phase function to get its amplitude. In addition, power operation is adopted to increase the amplitude difference between dispersion energy and noise. Finally, we generate the dispersion image by searching for the maximum amplitude of a slanting-phase function. Because the CSFK method considers the position of surface-wave energy in the time-frequency domain, this largely eliminates the noise interference from other time locations and improves the resolution and signal-to-noise ratio of the dispersion image. The results of synthetic test and field dataset processing demonstrate the effectiveness of the proposed method. In addition, we invert all 120 sets of dispersion curves extracted from reflected wave seismic data acquired for petroleum prospecting. The one-dimensional inversion shear-wave velocity models are interpolated into a two-dimensional profile of shear-wave velocity, which is in good agreement with the borehole data.

Differential Interferometric Synthetic Aperture Radar data for more accurate earthquake catalogs

The accuracy of earthquake catalogs limits the reliability of earthquake hazard assessment and the comprehensive understanding of earthquake mechanisms. Current seismic catalogs are based on the inversion of seismic wave data. The accuracy of their source parameters, which reflect the quantity and layout of seismic stations, and the crustal velocity model used, are often highly uncertain. The open source and popularization of Interferometric Synthetic Aperture Radar (InSAR) deformation data offer the potential to provide more accurate source parameters for earthquake catalogs. In this study, we used same-source InSAR data and a consistent processing approach (i.e., the same sampling, inversion algorithm, and processing flow) to obtain the fault slip models and source parameters of 56 earthquakes, covering most of earthquakes observed by the Sentinel-1 since 2014; these were then used to form a unified InSAR earthquake catalog (U-InSAR). We then compiled a second InSAR earthquake catalog (C-InSAR) based on the source parameters of an additional 164 earthquakes inverted using InSAR deformation data from various sources by previous studies, among which 45 earthquakes included additional Global Navigation Satellite System (GNSS) data. The C-InSAR catalog was used to evaluate the impact of data sources and processing approach on the consistency of InSAR catalogs; we found no significant differences between the U- and C-InSAR catalogs. Secondly, the combined U- and C-InSAR catalogs were compared with seismological catalogs, and showed significantly improved seismic source locations, depths, moment magnitudes, fault strikes, fault dips, and fault rakes. Our results confirm the rationality and feasibility of constructing earthquake catalogs using source parameters from a variety of InSAR data sources and inversion algorithms. We emphasize that InSAR catalogs can provide an important supplement, improvement, and/or correction to seismological catalogs, and can provide important basic data for more refined and reliable research on earthquake mechanisms and hazard assessments. Finally, we set up a preliminary sharing and distribution system for InSAR-based catalogs.

Application of the Bayesian Source Location Using Seismic and Acoustic Observations in Inversion of Surface Explosion Source Locations

The dropping point of a projectile is an important parameter for evaluating the range weapon performance. A Bayesian jointed source location method by using seismic and acoustic observations is developed. This jointed method is to take advantage of signals in the atmosphere and seismic wave signals in the ground and reduce the influence of atmospheric factors, geological factors, topographical factors, and seismic phase identification factors on the location accuracy. Therefore, it is a high-precision location method. Firstly, this paper combined the four-element cross acoustic array and the single seismic measurement points to measure the acoustic signals/seismic waves of the surface explosion. Then, the paper obtained the azimuth information through sound arrays and signal arrival information through the seismic measurement points and performed an inversion of the explosive source location based on the Bayesian theory. The results show that the Bayesian location method has a high precision due to the full consideration of the error model and a-priori information. In addition, the Bayesian jointed source location method can provide more constraints on the location of the explosive source by integrating seismic wave data and acoustic data, which makes the probability density distribution of the explosive source more concentrated and the location result more robust.