Publications

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This paper will describe an algorithm for detecting and classifying seismic and acoustic signals for unattended ground sensors. The algorithm must be computationally efficient and continuously process a data stream in order to establish whether or not a desired signal has changed state (turned-on or off). The paper will focus on describing a Fourier-based technique that compares the running power spectral density estimate of the data to a predetermined signature in order to determine if the desired signal has changed state. How to establish the signature and the detection thresholds will be discussed as well as the theoretical statistics of the algorithm for the Gaussian noise case with results from simulated data. Actual seismic data results will also be discussed along with techniques used to reduce false alarms due to the inherent nonstationary noise environments found with actual data.

In this paper, we have presented the relative advantages and complementary aspects of acoustic and seismic ground sensors. A detailed description of both acoustic and seismic ground sensing methods has been provided. Acoustic and seismic phenomenology including source mechanisms, propagation paths, attenuation, and sensing have been discussed in detail. The effects of seismo-acoustic and acousto-seismic interactions as well as recommendations for minimizing seismic/acoustic cross talk have been highlighted. We have shown representative acoustic and seismic ground sensor data to illustrate the advantages and complementary aspects of the two modalities. The data illustrate that seismic transducers often respond to acoustic excitation through acousto-seismic coupling. Based on these results, we discussed the implications of this phenomenology on the detection, identification, and localization objectives of unattended ground sensors. We have concluded with a methodology for selecting the preferred modality (acoustic and/or seismic) for a particular application.

This paper describes a novel digital signal processing algorithm for adaptively detecting and identifying signals buried in noise. The algorithm continually computes and updates the long-term statistics and spectral characteristics of the background noise. Using this noise model, a set of adaptive thresholds and matched digital filters are implemented to enhance and detect signals that are buried in the noise. The algorithm furthermore automatically suppresses coherent noise sources and adapts to time-varying signal conditions. Signal detection is performed in both the time-domain and the frequency-domain, thereby permitting the detection of both broad-band transients and narrow-band signals. The detection algorithm also provides for the computation of important signal features such as amplitude, timing, and phase information. Signal identification is achieved through a combination of frequency-domain template matching and spectral peak picking. The algorithm described herein is well suited for real-time implementation on digital signal processing hardware. This paper presents the theory of the adaptive algorithm, provides an algorithmic block diagram, and demonstrate its implementation and performance with real-world data. The computational efficiency of the algorithm is demonstrated through benchmarks on specific DSP hardware. The applications for this algorithm, which range from vibration analysis to real-time image processing, are also discussed.

During hydrocarbon reservoir stimulations, such as hydraulic fracturing, the cracking and slippage of the formation results in the emission of seismic energy. The objective of this study was to determine the properties of these induced micro-seisms. A hydraulic fracture experiment was performed in the Piceance Basin of Western Colorado to induce and record micro-seismic events. The formation was subjected to four processes; breakdown/ballout, step-rate test, KCL mini-fracture, and linear-gel mini-fracture. Micro-seisms were acquired with an advanced three-component wall-locked seismic accelerometer package, placed in an observation well 211 ft offset from the fracture well. During the two hours of formation treatment, more than 1200 micro-seisms with signal-to-noise ratios in excess of 20 dB were observed. The observed micro- seisms had a nominally flat frequency spectrum from 100 Hz to 1500 Hz and lack the spurious tool-resonance effects evident in previous attempts to measure micro-seisms. Both p-wave and s-wave arrivals are clearly evident in the data set, and hodogram analysis yielded coherent estimates of the event locations. This paper describes the characteristics of the observed micro- seismic events (event occurrence, signal-to-noise ratios, and bandwidth) and illustrates that the new acquisition approach results in enhanced detectability and event location resolution.

An essential requirement for both Vertical Seismic Profiling (VSP) and Cross-Hole Seismic Profiling (CHSP) is the rapid acquisition of high resolution borehole seismic data. Additionally, full wave-field recording using three-component receivers enables the use of both transmitted and reflected elastic wave events in the resulting seismic images of the subsurface. To this end, an advanced three-component multi-station borehole seismic receiver system has been designed and developed by Sandia National Labs (SNL) and OYO Geospace. The system acquires data from multiple three-component wall-locking accelerometer packages and telemeters digital data to the surface in real-time. Due to the multiplicity of measurement stations and the real-time data link, acquisition time for the borehole seismic survey is significantly reduced. The system was tested at the Chevron La Habra Test Site using Chevron's clamped axial borehole vibrator as the seismic source. Several source and receiver fans were acquired using a four-station version of the advanced receiver system. For comparison purposes, an equivalent data set was acquired using a standard analog wall-locking geophone receiver. The test data indicate several enhancements provided by the multi-station receiver relative to the standard receiver; drastically improved signal-to-noise ratio, increased signal bandwidth, the detection of multiple reflectors, and a true 4: 1 reduction in survey time.