Seismic Nodes Research Articles

Benefits of integrating seismic and gravity data in a subsalt environment: A case study at block BM-C-33, deepwater Campos Basin, offshore Brazil

Imaging subsalt layers is challenging in the BM-C-33 block in the Campos Basin’s ultradeep waters. This block is important because it has three significant gas and condensate discoveries in the presalt carbonate and volcanic reservoirs—Seat, Gávea, and Pão de Açucar. Understanding basement morphology is essential to better define the petroleum system in the area. To that end, we performed a 2D gravity modeling exercise along a northwest–southeast section using seismic interpretation as input to reduce the ambiguity of the modeling exercise. To achieve this, we fixed the main sedimentary horizons and their densities (calculated via well-log information) to better estimate the top of the basement morphology. This interpretation strategy better delineated the presalt sedimentary section and the complex structural framework with two asymmetric grabens bounded by a prominent horst, interpreted as a migration focusing high in the BM-C-33 area. In addition, our findings show that obtaining clear images remains challenging even after extensive processing of the seismic data set. We suggest that seismic node acquisition with ultralong offsets and multiazimuthal illumination and then carefully processing the data is required to accurately reveal the area’s prerift section and basement morphology under study.

Firn seismic anisotropy in the Northeast Greenland Ice Stream from ambient-noise surface waves

Abstract. We analyse ambient-noise seismic data from 23 three-component seismic nodes to study firn velocity structure and seismic anisotropy near the EastGRIP camp along the Northeast Greenland Ice Stream (NEGIS). Using nine-component correlation tensors, we derive dispersion curves of Rayleigh and Love wave group velocities from 3 to 40 Hz. These velocity distributions exhibit anisotropy along and across the flow. To assess these variations, we invert dispersion curves for shear wave velocities (Vsh and Vsv) in the top 150 m of the NEGIS using a Markov chain Monte Carlo approach. The reconstructed 1-D shear velocity model reveals radial anisotropy in the firn, with Vsh 12 %–15 % greater than Vsv, peaking at the critical density (550 kg m−3). We combine density data from firn cores drilled in 2016 and 2018 to create a new density parameterisation for the NEGIS, serving as a reference for our results. We link seismic anisotropy in the NEGIS to effective and intrinsic causes. Seasonal densification, wind crusts, and melt layers induce effective anisotropy, leading to faster Vsh waves. Changes in firn recrystallisation cause intrinsic anisotropy, altering the Vsv / Vsh ratio. We observe a shallower firn–ice transition across the flow (≈ 50 m) compared with along the flow (≈ 60 m), suggesting increased firn compaction due to the predominant wind direction and increased deformation towards the shear margin. We demonstrate that short-duration (9 d minimum), passive, seismic deployments and noise-based analysis can determine seismic anisotropy in firn, and we reveal 2-D firn structure and variability.

BROADBAND SEISMIC NODE BASED ON LOW-NOISE HIGH-SENSITIVITY MOLECULAR-ELECTRONIC SENSORS

The developed wideband compact digital seismic module designed for use in ground nodal seismic systems with deployment assistance from unmanned aerial vehicle (UAV) is discussed. The operation frequency band is 1–300 Hz, which is by far wider than that of the seismic nodes based on using standard (10Hz) electrodynamic geophones. Such improvement was achieved through the use of highly sensitive seismic sensors with molecular electronic transfer (MET) that allow for covering a low-frequency part of the spectrum that is needed for broadband processing and receiving information on deep subsurface formation. Low self-noise of the MET seismic sensors used for this seismic station has been proven in special tests. According to the test results, measurements of the self-noise of the developed sensor turned out to be 27-30 dB lower than the self-noise of similar sensors with additional mass. Besides of the 3 mutually orthogonal wideband MET sensors the developed module consists of a digital electronics block enabling autonomous registration and featuring wireless data transmission capability; a battery compartment providing autonomous operation of the seismic module; a device for attaching the seismic module to UAVs and lowering it to the ground. The developed device ensures data time synchronization with satellites, records data at frequencies up to 1000 samples per second with 24 bits resolution and stores the recorded information on the internal 32 Gb storage. A distinctive feature of the presented seismic node is the implementation of quality control of seismic data using a drone. This function is implemented on a Raspberry Pi single-board computer installed on board of the UAV, which has the ability to retrieve portion of information from the node for data quality control and initiate calibration procedure.

Quantifying spatial peat depth with seismic micronodes and the implications for carbon stock estimates

Peatlands are a major store of soil carbon, due to their high concentration of carbon-rich decayed plant material. Consequently, accurate assessment of peat volumes is important for determining land-use carbon budgets, especially in the Northern hemisphere. Determination of carbon stocks at the scale of individual peat sites has principally relied on either mechanical probing or electromagnetic geophysical methods. In this study, we investigated the use of seismic nodal instrumentation for quantifying peat depth. We used Stryde™ nodes for a deployment at the Whixall moss in Shropshire, England. We measured seismic arrival times from peat-bottom reflections, as well as dispersive surface waves to invert for a model of variable peat depth along a linear cross-section. The use of very small seismic nodes (micronodes) allows for particularly rapid deployment on challenging terrain.

Seismic Node Arrays for Enhanced Understanding and Monitoring of Geothermal Systems

Abstract Harnessing geothermal energy will likely play a critical role in reducing global CO2 emissions. However, exploration, development, and monitoring of geothermal systems remain challenging. Here, we explore how recent low-cost seismic node instrumentation advances might enhance geothermal exploration and monitoring. We show the results from 450 nodes deployed at a geothermal prospect in Cornwall, United Kingdom. First, we demonstrate how the nodes can be used to monitor the spatiotemporal and size distribution of induced seismicity. Second, we use focal mechanisms, shear-wave source polarities, and anisotropy to indicate how the dense passive seismic observations might provide enhanced insight into the stress state of the geothermal systems. All the methods are fully automated, essential for processing the data from many receivers. In our example case study, we find that the injection-site fracture orientations significantly differ from that of the crust above and the regional stress state. These observations agree well with fracture orientations inferred from independent well-log data, exemplifying how the nodes can provide new insight for understanding the geothermal systems. Finally, we discuss the limitations of nodes and the role they might play in hybrid seismic monitoring going forward. Overall, our results emphasize the important role that low-cost, easy-to-deploy dense nodal arrays can play in geothermal exploration and operation.

Basin Structure for Earthquake Ground Motion Estimates in Urban Los Angeles Mapped with Nodal Receiver Functions

We constrained sedimentary basin structure using a nodal seismic array consisting of ten dense lines that overlie multiple basins in the northern Los Angeles area. The dense array consists of 758 seismic nodes, spaced ~250–300 m apart along linear transects, that recorded ground motions for 30–35 days. We applied the receiver function (RF) technique to 16 teleseismic events to investigate basin structure. Primary basin-converted phases were identified in the RFs. A shear wave velocity model produced in a separate study using the same dataset was incorporated to convert the basin time arrivals to depth. The deepest part of the San Bernardino basin was identified near the Loma Linda fault at a depth of 2.4 km. Basin depths identified at pierce points for separate events reveal lateral changes in basin depth across distances of ~2–3 km near individual stations. A significant change in basin depth was identified within a small distance of ~4 km near the San Jacinto fault. The San Gabriel basin exhibited the largest basin depths of all three basins, with a maximum depth of 4.2 km. The high lateral resolution from the dense array helped to reveal more continuous structures and reduce uncertainties in the RFs interpretation. We discovered a more complex basin structure than previously identified. Our findings show that the basins’ core areas are not the deepest, and significant changes in basin depth were observed near some faults, including the San Jacinto fault, Fontana fault, Red Hill fault and Indian Hill fault.

The Pecos Array: A Temporary Nodal Seismic Experiment in the Pecos, Texas, Region of the Delaware Basin

Abstract With increasing earthquakes in the Delaware basin since 2009, earthquake studies, including accurate hypocenters, are critically needed in the Delaware basin to identify the structures producing earthquakes, and to determine if they are related to unconventional petroleum development and production. In 2018, with funding from the Texas Seismological Network, we deployed and maintained a nodal network of 25 Magseis Fairfield Z-Land Generation 2 5-Hz seismic nodes in the Pecos, Texas, region of the Delaware basin, known as, The Pecos Array. The network was deployed from November 2018 to the beginning of January 2020, with an additional two months of data recorded in September and October 2020. The network collected continuous three-component data with a 1000-Hz sampling rate. The spacing of the nodes varied from ∼2 km in town to ∼10 km farther away from the city center. The primary goal of this network was to improve estimation of event hypocenters, which will help to determine why there has been an increase in earthquakes over the past several years. In this article, we summarize the scientific motivation, deployment details, and data quality of this network. Data quality statistics show that we successfully collected continuous data with signal-to-noise ratios that allow us to detect and locate events, hundreds of them being estimated at ML<0.50. This unique dataset is contributing to new seismotectonic studies in the Delaware basin.

Joint elastic reverse time migration of towed streamer and sparse ocean-bottom seismic node hybrid data

Compared to 1C towed-streamer (TS) seismic exploration, 4C ocean-bottom seismic (OBS) node exploration has great advantages in complex structure imaging, lithology, and fluid identification using elastic waves. However, sparse spatial sampling of OBS node surveys highlights the problems of the imaging acquisition footprint, poor phase continuity, and low signal-to-noise ratio (S/N) with conventional elastic reverse time migration (ERTM) methods. Therefore, a solution of joint ERTM (J-ERTM) is proposed by combining sparse OBS node data with dense TS data. In the J-ERTM of the hybrid data, a novel weighted boundary condition combined with acoustic-elastic coupling equations and a vector-based crosscorrelation imaging condition are presented to perform PP and PS imaging by receiver-side tensorial extrapolation of TS and OBS node hybrid data. A synthetic example demonstrates that our method can effectively process TS and OBS node hybrid data and improve elastic imaging problems caused by OBS node sparse acquisition. J-ERTM techniques also are applied to an active-source OBS data set from the South China Sea. To improve the imaging quality with limited data, some preprocessing procedures for field TS and OBS node hybrid data sets are necessary, such as denoising, OBS node relocation, OBS node orientation correction, OBS node calibration, and others. After preprocessing, the pressure component and velocity components have a more physical energy relationship, more consistent frequency range and wavelet, and a higher S/N. Finally, the preprocessed hybrid data can be used for J-ERTM. The imaging results demonstrate that our method works well with field data.

Integrating controlled-source and ambient noise seismic measures for archaeological prospection: the Scrovegni Chapel case

SUMMARY In this paper, we present the results of an analysis of passive seismic noise recorded around the Scrovegni Chapel in Padua (Italy), using a dense 2-D network with nearly 1500 autonomous seismic nodes. Surface wave tomography using the active records allowed the imaging of several structures located at a depth of few metres, while this study focuses on the processing of about 22 hr of continuous passive records. First, the ambient noise is characterized in terms of amplitude, frequency content and azimuthal distribution, in order to ensure the applicability of the interferometric method. Second, a cross-correlation analysis is performed to retrieve virtual source gathers. Third, traveltimes are extracted from virtual source gathers using the same processing sequence applied to active gathers. Fourth, Eikonal tomography is run to retrieve isotropic phase velocity maps and azimuthal anisotropy. We compare and discuss the results obtained from the active and the passive methods, and finally propose a strategy for the integration of passive and active information. The new quasi-3-D shear wave velocity model obtained from the joint active and passive analysis is more accurate at depth, due to the addition of the passive low-frequency information.

Fleet's Geode: A Breakthrough Sensor for Real-Time Ambient Seismic Noise Tomography over DtS-IoT.

As most of the outcropping and shallow mineral deposits have been found, new technology is imperative to finding the hidden critical mineral deposits required to transition to renewable energy. One such new technique, called ambient seismic noise tomography, has shown promise in recent years as a low-cost, low environmental impact method that can image under cover and at depth. Wireless and compact nodal seismic technology has been instrumental to enable industry applications of ambient noise tomography, but these devices are designed for the active seismic reflection method and do not have the required sensitivity at low frequencies for ambient noise tomography, and real-time data transmission in remote locations requires significant infrastructure to be installed. In this paper, we show the development and testing of the Geode-a real-time seismic node purpose-built by Fleet Space Technologies for ambient seismic noise tomography on exploration scales. We discuss the key differences between current nodal technology and the Geode and show results of a field trial where the performance of the Geode is compared with a commercially popular nodal geophone. The use of a 2 Hz high sensitivity geophone and low noise digitiser results in an instrument noise floor that is more than 30 dB lower below 5 Hz than nodes that are commonly used in the industry. The increased sensitivity results in signal-to-noise ratios in the cross-correlation functions in the field trial that are more than double that of commercially available nodal geophone at low frequencies. When considering the full bandwidth of retrievable correlations in our study, using the Geode would reduce the required recording time from 75 h to 32 h to achieve an average signal-to-noise ratio in the cross-correlation functions of 10. We also discuss the integration of a real-time direct-to-satellite Internet of Things (DtS-IoT) modem in the Geode, which, together with edge processing of seismic data directly on the Geode, enables us to image the subsurface in real-time. During the field trial, the Geodes successfully transmitted more than 90% of the available preprocessed data packets. The Geode is compact enough so that several devices can be carried and installed by one field technician, whilst the array of stations do not require a base station to transmit data to the cloud for further processing. We believe this is the future of passive seismic surveys and will result in faster and more dynamic seismic imaging capabilities analogous to the medical imaging community, increasing the pace at which new mineral deposits are discovered.

Cover Mapping with Passive Seismics at the Boulia Prospect, Mount Isa Province, Queensland, Australia

To determine the thickness of sedimentary cover overlying Proterozoic basement, an ambient-noise surface-wave tomo-graphic (ANSWT) survey was conducted in the Boulia region of the Mt Isa Province in Queensland, Australia. An array of 100 three-component seismic nodes was deployed along a 30 km section and ambient seismic noise was recorded for 19 days. In the resultant seismic model, the top-basement contact is resolved as a sharp, subhorizontal interface at a depth of about 700 m, where seismic velocity (Vs) increases downward from about 2500 to 3500 m/s. The accuracy of the retrieved top-basement contact was confirmed by comparison with drill hole intersections and with results from active seismic and magnetotelluric surveys. This study demonstrates that the ANSWT method can accurately and inexpensively map the thickness of sedimentary cover that obscures potentially mineralised regions globally.

The extended range phase shift method for broadband surface wave dispersion measurement from ambient noise and its application in ore deposit characterization

Surface wave tomography using seismic ambient noise has been applied widely in subsurface characterization, the depth of which ranges from a few meters in urban underground engineering to tens of kilometers in delineation of crustal heterogeneities. Currently, multichannel analysis of surface waves with active and passive sources together with some similar techniques has been widely applied to obtain fine near-surface structures. However, it is still difficult to retrieve accurate dispersion curves at low frequencies with those methods to constrain structures at greater depths. To better retrieve surface wave dispersion data at lower frequencies using ambient noise data acquired by dense linear arrays, we use the extended range phase shift (ERPS) method, which can extract broadband dispersions from the ambient noise crosscorrelation functions (CFs). A broadband dispersion curve is obtained by merging a dispersion curve of medium-to-high frequencies with a dispersion curve of low-to-medium frequencies measured using receivers with different combinations, whereas both curves reflect the local property of the subsurface structure under a subarray with a relatively small aperture. Thus, the horizontal resolution of the inverted models is not compromised, whereas the inverted depth is improved considerably. We first perform a synthetic test to validate the ERPS method, and then apply the method in characterizing the Woxi polymetallic deposit in Hunan, China, where eight 10 km linear arrays using 467 seismic nodes were deployed to record ambient noise. The dispersion data within 0.5–10 Hz are extracted from the CFs using ERPS and then used to invert for the [Formula: see text] models down to at least 2 km. The inverted structures are found to be consistent with the previous geologic studies and known structures from underground mining, and the proposed passive-source imaging method is considered to be economical and practical for ore deposit explorations.

Postseismic Survey of a Historic Masonry Tower and Monitoring of Its Dynamic Behavior in the Aftermath of Le Teil Earthquake (Ardèche, France)

ABSTRACTOn 11 November 2019, an Mw 4.9 earthquake struck the middle Rhône valley (South-East France) producing moderate to severe damage in the town of Le Teil and its surroundings. This unexpected event stressed the vulnerability of the French cultural built heritage to a moderate seismic hazard. Commonly applied to modern civil engineering structures, passive seismic methods are still lacking on historic constructions to understand properly the different factors driving their dynamic behavior. In this article, the results of a two-month seismic monitoring survey carried out shortly after the Le Teil mainshock in a historic masonry tower are presented and discussed. Located only 5 km south of the epicenter, the Gate Tower of Viviers (eleventh century) was instrumented with four highly sensitive seismic nodes. Ambient vibrations, as well as aftershocks and quarry blasts from the nearby Le Teil quarry, were recorded and used in the analysis. Through vibration-based analysis, the article addresses three relevant aspects of the dynamic response of ancient masonry structures. We discuss first the differences in the building’s response induced by the three reported types of vibrations, focusing on the particular signal characteristics of shallow aftershocks and quarry blasts. Then, we apply the Random Decrement Technique (RDT) to track the dynamic behavior variations over two months and to discuss the role of the environmental conditions in the slight fluctuations of the structural modal parameters (natural frequencies, damping coefficients) of unreinforced masonry structures. We also show evidence of the nonlinear elastic behavior under both weak seismic and atmospheric loadings. The correlation between the presence of heterogeneities in the construction materials and the nonlinear threshold supports the relevance of such types of monitoring surveys as a valuable tool for future modeling works and conservation efforts.

A Link and Energy Aware Gradient Routing Method for Seismic Node Networks

Seismic node is an important geological exploration equipment. The seismic node has a complex near-ground application environment. The near-ground seriously interferes with the wireless signal of the seismic node and affects its data transmission capability. This article proposes a link and energy-aware gradient routing (LEGR) method, which can effectively reduce the interference of the near-ground on the seismic node. LEGR introduces the concept of link potential energy (LPE) to represent the gradient and establishes the LPE loss model using the link quality and the remaining power. The LPE is generated by the data acquisition center (DAC) and spreads to each node with some loss which is depending on the LPE loss model during the propagation process, and finally, a gradient field about the LPE is formed. Data are transmitted along the steepest direction of the gradient to the DAC. The simulation results show that LEGR significantly reduces the impact of wireless signal strength fluctuations on the seismic node compared with other traditional routing methods. The experimental results show that LEGR is superior to the commonly used routing method for seismic nodes network in term of packets latency and packet delivery rate, improves the anti-interference ability, and enhances the wireless communication reliability for the seismic node networks.

Optimal Power Management for Seismic Nodes

Estimating the state-of-charge of a lead-acid battery at remote seismic nodes is a key factor in managing the available power. Optimal management enables the continuous acquisition of seismic data of an area. This paper presents the management of lead-acid batteries at remote seismic nodes, using the Neural Network model's historical data to estimate the battery's state-of-charge. Powersim (PSIM) simulation tool was used to implement photovoltaic energy harvesting system with a buck mode converter and maximum power point tracking algorithm to acquire historical data. A backpropagation neural network technique for training the historical dataset of hourly points in 500 days on the Matlab platform is adopted, and a feedforward neural network is employed due to the irregularities of the input data. The neural network model's hidden layer contains the transfer function of the Tansig Function to produce the model output of state-of-charge estimations. Besides, this paper is based on the management of estimating the state-of-charge of the lead-acid battery near-realtime instead of relying on the vendor's lifecycle information. The simulated results show the simplicity and optimal estimations of state-of-charge of the lead-acid battery with RMSE of 0.023%.

A Greedy Flee in the Direction Routing Algorithm for Data Quality Control System of 3D Seismic Sensors Array

A rectangular array of seismic nodes is called a 3D seismic sensors array which is suitable for geographic routing. However, when certain seismic nodes have no location information, using detours or other methods to detect the path will increase latency and power consumption of geographic routing. It is challenging to maintain the high performance of geographic routing in practical 3D exploration networks. This letter proposes a greedy flee in the direction routing algorithm (GFDR). According to the feature that the intersection of the connection set of nodes is not empty, GFDR can drive the packet continuously forward in a specified direction without location information when the packet records the node ID of the path. Simulation results show that as the size of the area without location information (AWLI) increases, GFDR can keep the delivery ratio above 98%, while maintaining an approximately constant packet delay without increasing the number of packet-forwarding hops. A real seismic system experiment running GFDR algorithm confirms the simulation results and demonstrates the effectiveness of GFDR.

A Multi‐Hydrogeophysical Study of a Watershed at Kaiwi Coast (Oʻahu, Hawaiʻi), using Seismic Ambient Noise Surface Wave Tomography and Self‐Potential Data

AbstractWe study a watershed containing an old stream valley at the Kaiwi Coast on Oʻahu, Hawaiʻi. The study site has undergone significant hydrogeological changes throughout its history, and at present displays complex interactions of a variety of geological formations. We highlight an innovative and efficient combination of two hydrogeophysical methodologies for studying groundwater systems: ambient noise surface wave tomography (ANSWT), and self‐potential (SP) measurements. We collected (1) 5 days of continuous seismic data, using a total of 54 autonomous seismic nodes, exploiting both ocean wave and traffic noise sources and (2) 386 SP measurements with an average 20 m spacing, in the same area. We showcase how these two data sets complement each other in a joint‐interpretation framework. The SP data display the distribution of groundwater in the region, as well as zones of higher infiltration and/or flow rates. Using ANSWT, we identify the structural contact between the older Koʻolau basalt formation and the younger post‐erosional Honolulu volcanics, as well as the distribution of sedimentary valley fill and coastal deposits. The joint interpretation of the SP and seismic data clearly illustrates that groundwater flow occurs in the identified paleo‐channels at the erosional surface of the basaltic bedrock. Furthermore, it highlights that the basaltic bedrock of the ridges likely forms an important groundwater flow unit. Some flow may occur in the shallower valley fill material. Complementing SP data with seismic data enables us to place groundwater flow inferences, as made from SP data, at depth.

Determination of the local magnitudes of small earthquakes using a dense seismic array in the Changning−Zhaotong Shale Gas Field, Southern Sichuan Basin

With the development of unconventional shale gas in the southern Sichuan Basin, seismicity in the region has increased significantly in recent years. Though the existing sparse regional seismic stations can capture most earthquakes with <inline-formula><tex-math id="M1">\begin{document}$ {M}_{\mathrm{L}}\ge 2.5 $\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="lijunlun-F_M1.jpg"></graphic><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="lijunlun-F_M1.png"></graphic></alternatives></inline-formula>, a great number of smaller earthquakes are often omitted due to limited detection capacity. With the advent of portable seismic nodes, many dense arrays for monitoring seismicity in the unconventional oil and gas fields have been deployed, and the magnitudes of those earthquakes are key to understand the local fault reactivation and seismic potentials. However, the current national standard for determining the local magnitudes was not specifically designed for monitoring stations in close proximity, utilizing a calibration function with a minimal resolution of 5 km in the epicentral distance. That is, the current national standard tends to overestimate the local magnitudes for stations within short epicentral distances, and can result in discrepancies for dense arrays. In this study, we propose a new local magnitude formula which corrects the overestimated magnitudes for shorter distances, yielding accurate event magnitudes for small earthquakes in the Changning−Zhaotong shale gas field in the southern Sichuan Basin, monitored by dense seismic arrays in close proximity. The formula is used to determine the local magnitudes of 7,500 events monitored by a two-phased dense array with several hundred 5 Hz 3C nodes deployed from the end of February 2019 to early May 2019 in the Changning−Zhaotong shale gas field. The magnitude of completeness (<inline-formula><tex-math id="M2">\begin{document}$ {M}_{\mathrm{C}} $\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="lijunlun-F_M2.jpg"></graphic><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="lijunlun-F_M2.png"></graphic></alternatives></inline-formula>) using the dense array is −0.1, compared to <inline-formula><tex-math id="M3">\begin{document}$ {M}_{\mathrm{C}} $\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="lijunlun-F_M3.jpg"></graphic><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="lijunlun-F_M3.png"></graphic></alternatives></inline-formula> 1.1 by the sparser Chinese Seismic Network (CSN). In addition, using a machine learning detection and picking procedure, we successfully identify and process some 14,000 earthquakes from the continuous waveforms, a ten-fold increase over the catalog recorded by CSN for the same period, and the <inline-formula><tex-math id="M4">\begin{document}$ {M}_{\mathrm{C}} $\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="lijunlun-F_M4.jpg"></graphic><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="lijunlun-F_M4.png"></graphic></alternatives></inline-formula> is further reduced to −0.3 from −0.1 compared to the catalog obtained via manual processing using the same dense array. The proposed local magnitude formula can be adopted for calculating accurate local magnitudes of future earthquakes using dense arrays in the shale gas fields of the Sichuan Basin. This will help to better characterize the local seismic risks and potentials.

Power-Efficient Hybrid Energy Storage System for Seismic Nodes

Recent surveys in the energy harvesting system for seismic nodes show that, most often, a single energy source energizes the seismic system and fails most frequently. The major concern is the limited lifecycle of battery and high routine cost. Simplicity and inexperience have caused intermittent undersizing or oversizing of the system. Optimizing solar cell constraints is required. The hybridization of the lead-acid battery and supercapacitor enables the stress on the battery to lessen and increases the lifetime. An artificial neural network model is implemented to resolve the rapid input variations across the photovoltaic module. The best performance was attained at the epoch of 117 and the mean square error of 1.1176e-6 with regression values of training, test, and validation at 0.99647, 0.99724, and 0.99534, respectively. The paper presents simulations of Nsukka seismic node as a case study and to deepen the understanding of the system. The significant contributions of the study are (1) identification of the considerations of the PV system at a typical remote seismic node through energy transducer and storage modelling, (2) optimal sizing of PV module and lead-acid battery, and, lastly, (3) hybridization of the energy storage systems (the battery and supercapacitor) to enable the energy harvesting system to maximize the available ambient irradiance. The results show the neural network model delivered efficient power with duty cycles across the converter and relatively less complexities, while the supercapacitor complemented the lead-acid battery and delivered an overall efficiency of about 75 % .

Optimizing Energy Harvesting System at Seismic Node: A Case of NNNSS Nodes

Optimizing Energy Harvesting System at Seismic Node: A Case of NNNSS Nodes