Toward Creating a Subsurface Camera

Song, Wen-Zhan; Li, Fangyu; Valero, Maria; Zhao, Liang

doi:10.3390/s19020301

Cited by 20 publications

(11 citation statements)

References 103 publications

(163 reference statements)

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“…Xue et al [51] incorporated shaping regularization imposing structure constraints on the estimated model into a reverse-time migration approach to attenuate migration artifacts and crosstalk noise, which has the potential of further improving the source location resolution. Song et al [52] underlined the importance of reverse-time migration location in their subsurface camera (SAMERA) network idea, pointing out that interdisciplinary collaboration is the future direction for efficiently obtaining the in situ and real-time seismic inversion results based on advanced wireless sensor networks with distributed imaging algorithms.…”

Section: Reverse-time Migration Location Methodsmentioning

confidence: 99%

Locating Mine Microseismic Events in a 3D Velocity Model through the Gaussian Beam Reverse-Time Migration Technique

Wang

Shang

Peng

2020

Sensors

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Microseismic (MS) source location is a fundamental and critical task in mine MS monitoring. The traditional ray tracing-based location method can be easily affected by many factors, such as multi-ray path effects, waveform focusing and defocusing of wavefield propagation, and low picking precision of seismic phase arrival. By contrast, the Gaussian beam reverse-time migration (GBRTM) location method can effectively and correctly model the influences of multi-path effects and wavefield focusing and defocusing in complex 3D media, and it takes advantages of the maximum energy focusing point as the source location with the autocorrelation imaging condition, which drastically reduces the requirements of signal-to-noise ratio (SNR) and picking accuracy of P-wave arrival. The Gaussian beam technique has been successfully applied in locating natural earthquake events and hydraulic fracturing-induced MS events in one-dimensional (1D) or simple two-dimensional (2D) velocity models. The novelty of this study is that we attempted to introduce the GBRTM technique into a mine MS event location application and considered utilizing a high-resolution tomographic 3D velocity model for wavefield back propagation. Firstly, in the synthetic test, the GBRTM location results using the correct 2D velocity model and different homogeneous velocity models are compared to show the importance of velocity model accuracy. Then, it was applied and verified by eight location premeasured blasting events. The synthetic results show that the spectrum characteristics of the recorded blasting waveforms are more complicated than those generated by the ideal Ricker wavelet, which provides a pragmatic way to evaluate the effectiveness and robustness of the MS event location method. The GBRTM location method does not need a highly accurate picking of phase arrival, just a simple detection criterion that the first arrival waveform can meet the windowing requirements of wavefield back propagation, which is beneficial for highly accurate and automatic MS event location. The GBRTM location accuracy using an appropriate 3D velocity model is much higher than that of using a homogeneous or 1D velocity model, emphasizing that a high-resolution velocity model is very critical to the GBRTM location method. The average location error of the GBRTM location method for the eight blasting events is just 17.0 m, which is better than that of the ray tracing method using the same 3D velocity model (26.2 m).

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Section: Reverse-time Migration Location Methodsmentioning

confidence: 99%

Locating Mine Microseismic Events in a 3D Velocity Model through the Gaussian Beam Reverse-Time Migration Technique

Wang

Shang

Peng

2020

Sensors

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“…Since water saturation may affect the underground velocity, we believe our method may be suitable for this application. Similarly, near surface seismic imaging helps monitor shallow buried objects [9,34,35], for example, very shallow seismic reflection and refraction experiments can be conducted to investigate groundwater level changes in beach sand in situ [36]. These are other potential applications that we aim to explore with our methodology.…”

Section: Future Workmentioning

confidence: 99%

“…For example, wirelessly connected sensors are deployed using an air-dropped way to monitor live volcano activities, where communication and computation become bottlenecks [7]. Recently, seismic tomography has been implemented using advanced wireless sensor networks with distributed computing algorithms [8,9,10]. The distributed style has advantages in reducing the data loss risk in the case of node and cable failures, because the sensing, computing, and data storage tasks can be operated in the sensor nodes.…”

Section: Introductionmentioning

confidence: 99%

“…We have been pioneers in developing such kind of systems [9,10,11]. Sensors are deployed in the field (Figure 1a is a illustrative example of deployment at meter scale, and Figure 1b at kilometers scale (the based method used in this paper (SPAC) has been tested in deployments in the range of few meters to several kilometers [12,13,14])) in a mesh network to work cooperatively and image the subsurface.…”

Section: Introductionmentioning

confidence: 99%

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Distributed and Communication-Efficient Spatial Auto-Correlation Subsurface Imaging in Sensor Networks

Valero

Clemente

et al. 2019

Sensors

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A wireless seismic network can be effectively used as a tool for subsurface monitoring and imaging. By recording and analyzing ambient noise, a seismic network can image underground infrastructures and provide velocity variation information of the subsurface that can help to detect anomalies. By studying the variation in the noise cross-correlation function of the noise, it is possible to determine the subsurface seismic velocity and image underground infrastructures. Ambient noise imaging can be done in a decentralized fashion using Distributed Spatial Auto-Correlation (dSPAC). In dSPAC over sensor networks, the cross-correlation is the most intensive communication process since nodes need to communicate their data with neighbor nodes. In this paper, a new communication-reduced method for cross-correlation is presented to meet bandwidth and cost of communication constraints in networks while ambient noise imaging is performed using dSPAC method. By applying the proposed communication-reduced method, we show that energy and computational cost of the nodes is also preserved.

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“…Crice et al in [3] covered the approaches and designs for near-surface seismic acquisition and highlighted the transition in the industry from cabled to cable-less seismic acquisition systems. More recently, Song et al in [15] discussed the big picture of distributed sensor networks for subsurface imaging, describing a framework and an architecture towards the realization of an envisioned subsurface camera.…”

Section: Introductionmentioning

confidence: 99%

Wireless Geophone Sensing System for Real-Time Seismic Data Acquisition

et al. 2020

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Active seismic surveys, for the exploration of oil and gas reservoirs, are conducted using a huge network of geophone sensors (>10,000) covering a very large area and interconnected using seismic cables. Such cables enable reliable operation and fast data transfer, but account for a major percentage of the survey cost and limit its flexibility. In this paper, a wireless seismic data acquisition system that provides real-time data transmission for active seismic surveys is designed and implemented. A system that comprises a smart wireless sensor node and a gateway unit is demonstrated as a proof-of-concept. The smart wireless node comprises a geophone sensor, a high-resolution data acquisition system and a smart reconfigurable wireless communication module. The data acquisition system includes an electronic circuit for amplification and filtering, a single-board computer and a 24-bit analog-to-digital converter (ADC). The wireless communication module comprises a 2.4 GHz radio frequency (RF) transceiver connected to a pattern reconfigurable antenna. A microcontroller is employed to reconfigure the Yagi-Uda antenna to scan its radiation pattern in different directions and focus the radiated power in the direction of the nearest gateway. This high-gain directional antenna would allow communication between the sensor node and the gateway over a longer distance as compared with the monopole antenna conventionally employed in commercial wireless seismic systems. The proposed system, employing a reconfigurable antenna in the sensor node, has been implemented and tested and was able to successfully capture seismic data from the geophone sensor and transmit it wirelessly in real-time to the gateway unit, achieving a notable 25% enhancement in the communication range between the sensor node and the gateway. This communication range enhancement results in a significant 56% enhancement in the gateway's communication area coverage, when compared to similar systems that use conventional monopole antennas in their sensor nodes.

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Toward Creating a Subsurface Camera

Cited by 20 publications

References 103 publications

Locating Mine Microseismic Events in a 3D Velocity Model through the Gaussian Beam Reverse-Time Migration Technique

Locating Mine Microseismic Events in a 3D Velocity Model through the Gaussian Beam Reverse-Time Migration Technique

Distributed and Communication-Efficient Spatial Auto-Correlation Subsurface Imaging in Sensor Networks

Wireless Geophone Sensing System for Real-Time Seismic Data Acquisition

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