Seismic Applications Research Articles

Temperature-dependent modal analysis of the InSight lander on Mars

The first high-performance seismometer on Mars, deployed by InSight, has been working for nearly two Martian years. However, the recorded seismic data are substantially affected by the natural frequencies of the lander. To analyze the effect of the natural frequencies of the lander on specific components of the seismic data, we have built a simplified finite-element model of the lander to conduct modal analyses. Three natural frequencies are modeled by comparing them with those identified from the observed data. These natural frequencies are nonconstant and temperature dependent, which can be explained as an elastic modulus reduction of the solar panels (35% at most) and/or the property changes of the ground media beneath the lander due to a daily air temperature variation of approximately 100 K on Mars. Compared with the previous studies based on the empirical models before the launch, our results can quantitatively evaluate natural modes and their temperature dependency. Thus, these analyses are helpful in avoiding the potential interference of natural frequencies and improving the reliability of seismic data applications.

All-in-one proxy to replace 4D seismic forward modeling with machine learning algorithms

Time-lapse seismic data provides valuable information to assist reservoir monitoring, model-based reservoir management, and development activities. 4D seismic information can be used quantitatively to estimate saturation-pressure changes or update reservoir simulation models through a data assimilation process, which traditionally requires a 4D seismic forward model that includes two steps: (1) petro-elastic model to relate rock and fluid properties to elastic attributes and (2) seismic model to depict wave propagation in the reservoir. The traditional forward model brings some complications in quantitative applications, such as time-lapse seismic history matching. Its multidisciplinary nature is a significant bottleneck to update simulation models, once observed 4D seismic data is used with production data in the assimilation process. Furthermore, it is time-consuming, especially in three-dimensional simulation models within data assimilation with several iterations. Here, the traditional forward model needs to be run hundreds or even thousands of times. Aside from being time-consuming, it requires substantial computer memory for complex geology, where more sophisticated seismic models are needed. In 4D seismic quantitative applications, the timely use of the information and its full benefits fade away due to the computational cost and time of the 4D seismic forward model. This research proposes a proxy (we call it, S4D-Proxy) to replace the traditional approach. The S4D-Proxy leverages machine learning models to detect hidden patterns and learn relations between input features (e.g., porosity and saturation-pressure changes) and the target (time-lapse difference of seismic amplitude). Training data are prepared and fed to the machine learning algorithms to relate the inputs and the desired output. The performances of the machine learning models are evaluated based on a numerical measure (coefficient of determination) and visual comparison of the results with the traditional forward model. Our results show that the average coefficient of determination for the test dataset is in an acceptable range. Moreover, the visual comparison of the proxy predictions with those from the traditional approach shows high similarity. Most hardening and softening 4D signals are reproduced with the proxy models. The main advantage of our approach is that it lowers the computational cost and time. The application of the proxy in data assimilation process could offer a significant speed advantage with faster 4D seismic forward modeling for data assimilation iterations. Unlike the traditional forward model, which is one step (petro-elastic model) then another (seismic model), our approach performs the forward modeling at once (all-in-one proxy model). It also offers an alternative 4D seismic forward model for time-lapse seismic feasibility study. All these advantages make the S4D-Proxy valuable and practical in permanent reservoir monitoring (PRM), where the reduced turnaround time in the forward model indicates the timely use of the 4D seismic information.

Design of MEMS capacitive comb accelerometer with perforated proof mass for seismic applications

Micro Electro Mechanical System (MEMS) sensors are characterized by their small size, but their performances exceed that of their macro-scale counterparts. The small size of MEMS devices and their integration with microelectronics proves a major advantage. In this paper, a design of MEMS capacitive comb accelerometer for seismology application using COMSOL Multiphysics platform is presented. A seismometer (also known as a seismograph) is a device that is used to measure and record the behavior of seismic waves. With this data, the location and measure of earthquakes can be detected. This seismic device has a large frequency band, compared to traditional geophones and seismographs. In this paper, a study to measure amplitudes and frequencies of vibrations is presented, and the results are analyzed and compared for perforated mass and solid proof mass. The effect of the size of etch hole for perforation is also studied.The displacement sensitivity and capacitive sensitivity of accelerometer are found to be 1.188 × 10-9m/g and 1.093 × 10-21F, respectively.

Southwest Australia Seismic Network (SWAN): Recording Earthquakes in Australia’s Most Active Seismic Zone

AbstractThe geological structure of southwest Australia comprises a rich, complex record of Precambrian cratonization and Phanerozoic continental breakup. Despite the stable continental cratonic geologic history, over the past five decades the southwest of Western Australia has been the most seismically active region in continental Australia, though the reason for this activity is not yet well understood. The Southwest Australia Seismic Network (SWAN) is a temporary broadband network of 27 stations that was designed to both record local earthquakes for seismic hazard applications and provide the opportunity to dramatically improve the rendering of 3D seismic structure in the crust and mantle lithosphere. Such seismic data are essential for better characterization of the location, depth, and attenuation of the regional earthquakes, and hence understanding of earthquake hazard. During the deployment of these 27 broadband instruments, a significant earthquake swarm occurred that included three earthquakes of local magnitude 4.0 and larger, and the network was supplemented by an additional six short-term nodal seismometers at 10 separate sites in early 2022, as a rapid deployment to monitor this swarm activity. The SWAN experiment has been continuously recording since late 2020 and will continue into 2023. These data are archived at the International Federation of Digital Seismograph Networks (FDSN) - recognized Australian Passive Seismic (AusPass) Data center under network code 2P and will be publicly available in 2025.

Emerging superelastic SMA core damping elements for seismic application

Structural and non-structural damage reported after recent strong earthquakes promotes a fundamental shift in structural design target from “collapse resistance” to “fast structural function recovery”. A unique class of metal called superelastic shape memory alloy (SMA) has been emerging as a promising solution to enhance the seismic resilience of structures. SMA core damping elements are the basic constituents of many newly-proposed seismic resistant members or devices, and they are directly responsible for the safety, integrity, and economical efficiency of the structures using them. This mini-review paper offers a comprehensive summary of the emerging SMA core damping elements recently developed, covering SMA monofilament wires, fibers, bars, flat plates, U-shaped plates, angles, cables, rings, helical springs, disc springs, and friction springs. These SMA core elements are suitable for various seismic application scenarios, and their efficiency have been verified through either full-scale or proof-of-concept experimental studies. The basic working principles, advantages, and potential shortcomings of these elements are discussed, and future research needs are outlined.

Soil-structure interaction in a base and mid-story seismically isolated building

The main goal of this study is to analyze the performance of seismic isolation systems by implementing isolation to the base and inter-story of the buildings together, in order to reduce the earthquake impact in multi-story buildings. In addition the soil-structure interaction for these cases are taken into consideration. An example building model was composed to observe the effect of base isolation and mid-story isolation numerically. Analyses were performed by using SAP2000 software. A five story building was used as an example structure. Investigations were carried out for six different combinations that are: fixed base buildings, buildings with soil-structure interaction, buildings incorporating single base isolation system with and without consideration of soil-structure interaction, buildings with base and mid story isolation system with and without consideration of soil-structure interaction. Two different earthquake motions were selected for time-history analysis. The results obtained from time-history analysis were discussed comparatively, for all the base-isolation cases including and excluding soil-structure interaction. It has been concluded that the seismic isolation application of the base and mid-story improves the seismic performance of the building. In addition, it has been observed that the soil-structure interaction affects the building seismic performances according to the reference ground type.

Weak Seismic Signal Enhancement Using Curvelet Transform and Compressive Sampling

Conventional curvelet-domain denoising methods suppress random noise by thresholding the amplitude of curvelet coefficients, which makes it hard to distinguish weak seismic signals from random noise because they share the same characteristic of weak amplitude in the curvelet domain. Here we put forward an innovative weak seismic signal enhancement method taht can distinguish weak seismic signals from random noise. After compressive sampling, the curvelet coefficients of weak seismic signals show significant amplitude reduction, whereas random noise does not. We take advantage of this characteristic and design a sensitivity coefficient, the absolute ratio of curvelet coefficients before and after compressive sampling. The sensitivity coefficient can distinguish weak seismic signals from random noise in the curvelet domain better than thresholding the amplitude of curvelet coefficients. The results of synthetic and field seismic data applications both indicate that our method outperforms the conventional curvelet-domain denoising method on weak seismic signal enhancement.

Reinforcement Learning-Based Denoising Model for Seismic Random Noise Attenuation

The random noise attenuation is an essential step in seismic data processing. Due to complex geological conditions and acquisition environment, the intensity of effective signal and random noise varies in time and space. Additionally, the morphology of seismic event is complex and diverse, such as large dips and fast changes. These complex conditions necessitate that the denoiser adjust filtering policy dynamically. In this paper, we propose a reinforcement learning-based seismic denoising (RLSD) model with the framework of asynchronous advantage actor-critic (A3C). In A3C framework, the RLSD agent utilizes a policy network to learn a denoising policy for the state that is the sample of seismic data and selects a suitable filter from the preset action space composed of multiple simple and effective seismic filters with different parameters. Moreover, the RLSD agent utilizes a value network and a region-adaptive weighted reward function to accurately evaluate the denoising effect of nonstationary seismic signals. A curriculum learning approach is adopted to achieve convergence of the proposed RLSD model under complex seismic data by training from the stationary training data to nonstationary training data, and make the model more suitable to the data to be processed by using a local similarity-based reward function to fine-tune the model. The synthetic and field seismic data applications confirm that the proposed RLSD model achieves a significant performance in preserving nonstationary signals and suppressing noise by adaptively adjusting the denoising policy according to the complex structural features and noise levels. The source code is available on https://github.com/liangc-code/RLSD.

Evaluation of waste in seismic metamaterial applications

Within the scope of this study, a simulation study was carried out in order to prove the usability of waste in seismic metamaterial studies. In the study, a square array field application was preferred, and a 3-layer cylindrical pile design was used. In addition, direct contact of waste with soil and direct air is prevented. Within the scope of the study, polypropylene, which is frequently contained in medical products, concrete as a containment layer, and lime materials to prevent leakage of hazardous waste were used as materials. In addition, a design has been made within the soil structure as the ground structure. As a result of the study, it was determined that transmission losses occur in low frequency regions such as 3-10 Hz values due to obtaining partial band gaps. In addition, when looking at the propagation of the vibration waves in the field plane depending on the time, it is seen that the waves are significantly reduced, and the results are promising.

Adaptive knowledge-based seismic risk assessment of existing reinforced concrete buildings using the SLaMA method

This paper presents and discusses the ongoing developments towards the definition of a multi-knowledge level seismic assessment procedure for large-scale seismic risk applications. The procedure involves the analytical-mechanical SLaMA (Simple Lateral Mechanism Analysis) method and allows for an adaptive and updatable assessment of the seismic performance of buildings accounting for different data acquisition (knowledge) levels. By coupling this approach with vulnerability assessment survey forms, a range/domain of expected capacity curves of a structure can be obtained and used to evaluate the seismic safety and the expected economic losses according to the state-of-the-art procedures in literature. Moreover, the results of the analytical assessment method can be used to develop fragility curves through simplified spectrum-based procedures. Combining the results of the fragility analysis with the hazard analysis, the seismic risk of a structure can be assessed in terms of Mean Annual Frequency (MAF) of collapse, as well as in terms of Expected Annual Losses (EAL). The proposed SLaMA-based approach is illustrated for an existing reinforced concrete building. Results confirm the effectiveness of the methodology for seismic-risk assessment studies at large scale, thus overcoming the issue related to limited building information, yet allowing for a continuous update of the “digital twin” model as further data/information becomes available.

Frequency-Dependent AVO Inversion Using a Modified Window-Parameter-Optimized S-Transform for High Gas-Saturation Reservoir Delineation

The dispersion induced by fluid flow is a useful characteristic of hydrocarbon reservoirs and can be deduced from frequency-dependent amplitude versus offset (FAVO) inversion. However, FAVO inversion strongly depends on the spectral decomposition method, which directly affects the resolution of inversion results. In this letter, we propose a new time-frequency analysis method, named modified window-parameter optimized S-transform (MWPOST), for improving the resolution of FAVO inversion. In MWPOST, the optimized scale parameter of the window function can be adaptively obtained according to the amplitude spectra of actual signals. Synthetic signal analysis indicates that the method has excellent performance with higher time-frequency resolution. Then, we present a high-precision FAVO inversion method using MWPOST for high gas-saturation reservoir delineation. The field seismic data application illustrates that the dispersion factor inverted by the proposed method has a higher time resolution and exhibits better performance for delineating the reservoir boundary with high gas saturation. The proposed method can improve the precision of FAVO and it is feasible to detect the location and spatial distribution of high gas-saturation reservoirs.

Time-lapse seismic imaging using shot gathers with nonrepeatable source wavelets

In time-lapse seismic applications, the signal produced by changes in the properties of subsurface rocks is generally obscured by noise associated with imperfect repeatability between surveys. A particularly important obstacle in the formation of time-lapse difference images is variation in the effective source wavelet between baseline and monitoring data sets. However, the partially separable influence of the wavelet within Green’s function model of seismic data permits two frequency-domain matching filters to be designed, which act to reduce source wavelet nonrepeatability. One is based on the spectral ratio of the baseline and monitoring wavelets and can be applied when prior estimates of the wavelets are available; the other is the average spectral ratio of the baseline and monitoring traces and can be applied when prior estimates are unavailable. After balancing the data sets with either of these filters, we further prepare for the imaging step with time-shift corrections, using a published fast local crosscorrelations algorithm, preparing the difference data for use in an imaging algorithm. Reverse time migration is engaged for the imaging task, but we observe that residual repeatability errors tend to be magnified at this stage when source-normalized crosscorrelation imaging conditions are used. Testing indicates that replacing this with a Poynting vector imaging condition strongly suppresses remaining errors in a robust manner. This includes stability within simulated data environments to noise-free data and data with random noise, up to signal-to-noise ratios of roughly one. Furthermore, our method illustrates better performance when compared with the conventional least-squares matching filter and common-depth-point-domain warping. At present, there is no common workflow for seismic imaging directly using time-lapse shot gathers. Our research contribution lies not only in the two matching filters but also in a novel workflow for time-lapse seismic imaging.

Wide-Azimuth, Broadband, and High-Density Seismic Technology and Its Application for Prediction of Residual Oil Distribution

Abstract —The paper focuses on the wide-azimuth, broadband, and high-density (WBH) seismic data application methodology, which was used to complete a more detailed structural interpretation of the K oilfield, to identify a number of low-relief structures in its periclinal parts, and to detect the potential residual oil zones (ROZ) in the oilfield. The obtained wide-azimuth, high-density field data and the results of broadband inversion are the main factors that increase the degree of ROZ prediction. A comprehensive analysis has shown that potential ROZ are arched faulted-nose structures in the periclinal parts of the oilfield, low-relief anticlines in the periclinal parts of the oilfield, and lithologic pinchout zones. Technical support has been provided for identifying ROZ in the given oilfield, and the basis has been laid for predicting the residual oil distribution in analogous oilfields with high productivity and high water cut that are at the middle and late stages of development.

Tribological investigation on metal mating surfaces to explore real use conditions of a novel friction damper for seismic applications

The seismic rehabilitation of existing buildings is a strategic goal for many countries located in high seismic risk areas of the globe. Retrofit techniques based on energy dissipation by implementing additional mechanical dampers into the structure have proved to be very efficient. Among the others, friction-based dampers have revealed to be particularly simple and cheap; nonetheless, for this kind of device, the selection of mating surfaces set a crucial point. This paper shows the experimental investigation performed for the development of a novel Friction Damper (FD) using Pin-on-Disk (PoD) tests and highlights the main tribological aspects useful for the full-scale tests. PoD tests have been set to simulate the real use condition of the device in development under the action of subsequent earthquakes. Sliding surface’s material and machining processes have been selected taking into account the S355JR steel main body of the device in development, and the need of reducing the friction’s abrasive component and the particle formation during sliding. The experimental campaign has been addressed to highlight the influence of surface roughness, machining processes, additional treatment, and different coupling materials on Coefficient of Friction (COF) mean value and its statistical dispersion.

The “Glass Beads” Coupling Solution for Borehole and Posthole Accelerometers: Shaking Table Tests and Field Retrievability

AbstractBorehole accelerometers are designed to record strong ground movements at depth. They have become an important complement to surface accelerometers for seismic and earthquake engineering applications. Borehole accelerometers present several implementation challenges, including their coupling with the geological environment. One possible coupling solution is the use of small glass beads, which are placed inside the borehole casing with the purpose of filling in any empty space between the sensor and the casing walls. We carried out a test on a shaking table, over a wide range of peak ground accelerations (PGA from 0.17 to 1.64g), allowing the comparison of the signals between a surface accelerometer and a borehole accelerometer coupled through the glass beads. These tests show that there is almost no difference between the surface and borehole accelerometer signals between 0.5 and 25 Hz, and only very small differences outside this band (0.2–0.5 Hz and 25–80 Hz). Furthermore, experience from multiple vertical accelerometric arrays show that an installation using glass beads is “reversible”, that is, 30 yr after the initial installation it can still be possible to easily extract the accelerometers for repair or replacement, without any problems or damage to the sensors.

Complementary Dense Datasets Acquired in a Low-to-Moderate Seismicity Area for Characterizing Site Effects: Application in the French Rhône Valley

Abstract Superficial geological layers can strongly modify the surface ground motion induced by an earthquake. These so-called site effects are highly variable from one site to another and still difficult to quantify for complex geological configurations. That is why site-specific studies can greatly contribute to improve the hazard prediction at a specific site. However, site-specific studies have historically been considered difficult to carry out in low-to-moderate seismicity regions. We present here seismological datasets acquired in the framework of the French–German dense array for seismic site effect estimation project in the heavily industrialized area surrounding the French Tricastin Nuclear Site (TNS). TNS is located above an ancient canyon dug by the Rhône River during the Messinian period. The strong lithological contrast between the sedimentary fill of the canyon and the substratum, as well as its expected confined geometry make this canyon a good candidate for generating site effects that are variable on short spatial scales. To investigate the impact of this geological structure on the seismic motion, we conducted complementary seismic campaigns in the area. The first main campaign consisted of deploying 400 nodes over a 10 × 10 km area for one month and aimed at recording the seismic ambient noise. A second seismic campaign involved the deployment of 49 broadband stations over the same area for more than eight months. This complementary campaign aimed at recording the seismicity (including local, regional, and teleseismic events). These different designs allowed us to target a variety of seismic data at different spatial and temporal scales. Beyond the interest for local operational seismic hazard applications, these datasets may be valuable for studying seismic wave propagation within complex kilometer-scale sedimentary structures. In this article, we present the deployment designs as well as initial analyses to provide information on the characteristics and the overall quality of the data acquired to future users.

Structural and modal analysis of gas insulated switchgear structure made up of glass-epoxy and carbon-epoxy composite materials for seismic application

Earthquakes cause significant loss of life and infrastructure damage. As a result, there has been a huge increase in the development of technologies and materials to mitigate the effects of earthquakes in the infrastructure sector. Along with the infrastructure industry, the electrical sector is working to design structures that can withstand the effect of an earthquake. The purpose of this study is to develop lightweight frame structure for Gas Insulated Switchgear (GIS) for seismic applications. In the proposed study, GIS frame structure incorporates composite materials such as carbon fibre reinforced polymer (CFRP) and glass fibre reinforced polymer (GFRP) in addition to traditional materials such as steel. These composite materials are subjected to experimental testing in order to determine their mechanical properties. To select optimal material for the frame structure, the structural and modal performance of these materials is evaluated using finite element simulations for the GIS frame structure under seismic loading as per California Building Code (CBC) and International Building Code (IBC) code.

Seismic design and parametric study of steel modular frames with distributed seismic resistance

Structures in modular buildings typically have some unique characteristics as compared with conventional structures, e.g., discrete connection of modules through inter-module connections, discontinuous floor diaphragms. The behavior of steel modular structures under earthquake excitations has not been fully understood, and no seismic design method specifically tailored for modular building structures is available. Moreover, although various inter-module connections with different rotational connectivity have been proposed, their suitability for seismic application is questionable. In this paper, the distributed seismic design method, which makes use of the lateral resistance inherent in all modules, was proposed for modular buildings with steel frames. A numerical parametric study was conducted on a 9-story prototype building. The effect of three parameters, i.e., the rotational stiffness of inter-module connections, the seismic design force level, and the height-wise distribution of the design base shear, were studied. The results show that the rotational stiffness of inter-module connections has limited impact on the elastic lateral stiffness and the fundamental period of modular steel frames. However, in the inelastic range, the increase in the rotational stiffness will lead to less plastic drift concentration and better collapse prevention performance. Increasing the seismic design force may not result in enhanced collapse prevention performance, as it is also dependent on the height-wise distribution of the design base shear and if significant higher-mode response is involved in the total response of the structure.

Finite element modelling (FEM) of the asymmetric friction connection (AFC)

Earthquakes occur frequently in New Zealand as the country is situated in the collision zone between the Indo-Australian and Pacific tectonic plates, where many earthquakes and volcanic activities occur. The consequences of severe earthquakes are injury and loss of life of people, the costs of repair for the damage of the structures and contents, and the costs of disruption of business and other activities. In average, 10 000 people are killed in earthquakes every year. Moreover, the damage and disruption caused by earthquakes throughout the world can be considerable. To avoid these undesirable economic effects of earthquakes, the global tendency has been moving towards the development and implementation of low-damage seismic resisting systems. The low damage design philosophy aims to satisfy the well-accepted “life safety” mandate, and minimize the economic losses due to post-earthquake damage repair as well as the downtime. The Sliding Hinge Joint (SHJ) is a low-damage beam-column connection used in steel moment-resisting frames. It allows large beam-column rotation with minimal damage through sliding in asymmetric friction components (AFCs) that are located at the web bottom bolt and bottom flange levels. AFC is friction seismic energy dissipating component of the SHJ. Following a set of experiments and different analytical research carried out on the AFC, there are proposed modifications to improve the performance of the AFC, and in general the SHJ (Clifton et. al., 2007 & Ramhormozian, 2017). One of the key objectives of this project is to provide a complete literature review and background of the friction energy dissipators for seismic applications including the SHJ developments, and to create numerical models to be validated by the previous and ongoing experimental results of the AFC as well as the SHJ. This includes creating finite element model (FEM) of different sizes, capacities, and configurations of the AFC and those of the SHJ, using ABAQUS software.

Improvement of superelasticity conditions in Cu-based shape memory alloys for seismic control applications

Shape memory alloys (SMAs) are smart materials with self-centering characteristics that can be used to reduce the earthquake damage to structures. In this paper, the optimal thermal treatment to obtain the ideal mechanical properties of a CuAlBe SMA wires for seismic protection applications is discussed. For this purpose, the uniaxial cyclic and monotonic stress-strain response of a 1.4 mm-diameter wire subjected to heat treatments applied for different durations is evaluated. Wire specimens are tested in multiple environments at several strain amplitudes and loading protocols. The variation of mechanical properties over time is also addressed. Test results show that a minimum treatment time of 25 min at 750 °C (∼200 μm) is necessary for obtaining superelasticity at all ambient temperatures tested. Also, as the heat treatment time increases, the residual strain, functional fatigue, strength, energy dissipation and hysteresis degradation decrease, but the superelasticity limit and low cycle fatigue life are increased. However, a 35 min treatment (∼400 μm) causes the loops to become unstable at high temperatures and the training process is not efficient. The best conditions for seismic protection purposes are achieved with a 30 min treatment (∼300 μm), due to its maximum recoverable strain of 6.5 %, 3.6 % equivalent viscous damping, negligible residual strain and stable hysteresis under all temperatures evaluated and over time. A low-cycle fatigue model based on the Coffin - Manson relationship is also proposed.