Fracture-generated frequency-dependent seismic Q measured from a VSP in granite

Author(s):  
Victoria R. Bourne ◽  
C. Dario Cantu Bendeck ◽  
Mark W. Hildyard ◽  
Roger A. Clark ◽  
William Wills

<div> <div> <div> <p>We integrate two topics – seismic characterisation of fractures, and seismic attenuation quantified as the frequency-dependent Seismic Quality Factor Q, Q(f). The former is vital for predicting and monitoring fluid movement and containment in energy-related settings (hydrocarbons; geothermal; CO<sub>2</sub>, hydrogen or compressed air storage; radwaste). Fractures control the fluid flow and structural behaviour of a rock mass, yet their expression in Q is poorly studied and not well understood despite it typically being more sensitive than wavespeeds as a rock physics parameter. The latter is long-recognised, little-studied, and a paradigm shift from frequency-independent Q (‘constant-Q’, a routine signal-processing and image enhancement tool in hydrocarbon exploration), despite theory, laboratory, and field data showing that Q must be frequency dependent due to varying scale-lengths of the physical-mechanical phenomena causing attenuation.</p> <p>We therefore measure Q(f) from the downgoing direct P-wave arrival in a near-offset vertical seismic profile in granite at a former geothermal test site in Cornwall, SW England, where vertical and horizontal fracturing is seen at surface: horizontal fractures are confirmed at depth by well-log data. Sensors were 3-component 15Hz geophones at 15m depth spacing: the source was a single vibrator, linear 8-100Hz up-sweep, 30m offset from the wellhead in the azimuth of well deviation: record length was 1000ms at 1ms sample interval. We analyse only the deeper cased interval, from 700m to 1735m. Pre-processing was geometric spreading correction, hodogram-based component rotation toward the source, and wavefield separation using a 7-point median filter to suppress interference from upgoing energy. Measured attenuation Q<sub>eff</sub> is the harmonic sum of intrinsic Q, Q<sub>int</sub>, and apparent attenuation, Q<sub>app</sub>. Q<sub>int</sub> in massive granite is typically 500-1000, yet we find Q<sub>eff</sub>(f) is 50-70 at >60Hz and only ≈30 at <30-35Hz, features masked in the constant-Q result of 55±11 over our working bandwidth of 25-90Hz.</p> <p>One contribution to Q<sub>app</sub> is ‘stratigraphic attenuation’, forward-scattering interference of short-path internal multiple reflections superimposed on direct arrivals, and quantifiable from sonic and density well-logs using O’Doherty-Anstey-Shapiro methodology. We find it is indeed frequency-dependent (peaking at ≈50-60Hz, 10-40% lower at our bandwidth limits) but its absolute magnitude is insignificant (Q≈20,000-30,000) and unable to explain the measured Q<sub>eff</sub>(f). We therefore investigate the effect of fracturing directly using finite difference models in which fractures are defined explicitly as displacement discontinuities with opposing surfaces connected by a normal and shear stiffness. An individual fracture acts somewhat like a low pass filter: more complex frequency behaviour emerges from multiple fractures, particularly when fracture stiffness, spacing and size can vary. We concentrate first on large horizontal fractures perpendicular to the borehole receiver array, and find that these can indeed influence effective attenuation within the 25-90Hz bandwidth. We then discuss the range of fracture spacings and stiffnesses capable of explaining the data and whether they are sufficiently physically credible as an explanation of the observed Q(f).</p> </div> </div> </div>

Geophysics ◽  
2018 ◽  
Vol 83 (3) ◽  
pp. S249-S259 ◽  
Author(s):  
Tong Zhou ◽  
Wenyi Hu ◽  
Jieyuan Ning

Most existing [Formula: see text]-compensated reverse time migration ([Formula: see text]-RTM) algorithms are based on pseudospectral methods. Because of the global nature of pseudospectral operators, these methods are not ideal for efficient parallelization, implying that they may suffer from high computational cost and inefficient memory usage for large-scale industrial problems. In this work, we reported a novel [Formula: see text]-RTM algorithm — the multistage optimized [Formula: see text]-RTM method. This [Formula: see text]-RTM algorithm uses a finite-difference method to compensate the amplitude and the phase simultaneously by uniquely combining two techniques: (1) a negative [Formula: see text] method for amplitude compensation and (2) a multistage dispersion optimization technique for phase correction. To prevent high-frequency noise from growing exponentially and ruining the imaging results, we apply a finite impulse response low-pass filter using the Kaiser window. The theoretical analyses and numerical experiments demonstrate that this [Formula: see text]-RTM algorithm precisely recovers the decayed amplitude and corrects the distorted phase caused by seismic attenuation effects, and hence produces higher resolution subsurface images with the correct structural depth information. This new method performs best in the frequency range of 10–70 Hz. Compared with pseudospectral [Formula: see text]-RTM methods, this [Formula: see text]-RTM approach offers nearly identical imaging quality. Based on local numerical differential operators, this [Formula: see text]-RTM method is very suitable for parallel computing and graphic processing unit implementation, an important feature for large 3D seismic surveys.


2013 ◽  
Vol 37 (3) ◽  
pp. 459-465
Author(s):  
Chih-Ta Yen ◽  
Ing-Jr Ding ◽  
Zong-Wei Lai

Digital watermarking is an encryption technology commonly used to protect intellectual property and copyright. In this study, we restored watermarks that had already been affected by noise interference, used the Walsh–Hadamard codes as the watermark identification codes, and applied salt-and-pepper noise and Gaussian noise to destroy watermarks. First method, we used a low-pass filter and median filter to remove noise interferences. The second one, we used a back-propagation neural network algorithm to suppress noises. We removed nearly all noise and recovered the originally embedded watermarks of Walsh–Hadmard codes.


2021 ◽  
Vol 11 (2) ◽  
pp. 256
Author(s):  
Mohtar Yunianto ◽  
Soeparmi Soeparmi ◽  
Cari Cari ◽  
Fuad Anwar ◽  
Delta Nur Septianingsih ◽  
...  

<p class="AbstractText">Telah berhasil dilakukan klasifikasi kanker paru-paru dari 120 data citra CT Scan. Pada penelitian, proses preposisi dimulai dengan variasi filtering yaitu low pass filter, median filter, dan high pass filter. Segmentasi yang digunakan yaitu Otsu Thresholding yang kemudian teksturnya akan diekstraksi menggunakan fitur Gray Level Co-occurrence Matrix (GLCM) dengan variasi arah sudut. Hasil dari ekstraksi GLCM dijadikan database yang akan menjadi dataset untuk pengklasifikasian citra menggunakan klasifikasi naïve bayes. Hasil dari penelitian dengan 12 buah variasi diperoleh hasil variasi terbaik adalah median filter dengan arah sudut GLCM 0° menunjukkan tingkat akurasi yang paling tinggi sebesar 88,33 %.</p>


2013 ◽  
Vol 284-287 ◽  
pp. 2961-2964
Author(s):  
Chih Ta Yen ◽  
Ing Jr Ding ◽  
Zong Wei Lai

Digital watermarking is an encryption technology commonly used to protect intellectual property and copyright. Although watermarks possess advantageous secrecy and robustness, environmental interference in the image propagation through the Internet is inevitable and, certainly, human-based image modification can also destroy the watermark. In this study, we restored watermarks that had already been affected by noise interference, used the Walsh-Hadamard codes as the watermark identification codes, and applied salt-and-pepper noise and Gaussian noise to destroy watermarks. First, we used a low-pass filter and median filter to remove noise interferences. Although these filters can suppress noises, watermarked images remain unidentifiable when the noise interferences strongly. Finally, we used a back-propagation neural network algorithm to filter noises, obtaining results that exceeded our expectations. We removed nearly all noise and recovered the originally embedded watermarks of Walsh-Hadmard codes.


2010 ◽  
Vol 139-141 ◽  
pp. 1736-1739
Author(s):  
Hui Huang Zhao ◽  
De Jian Zhou ◽  
Zhao Hua Wu

We present an approach to recognizing characters in surface mount technology (SMT) product. An improved SMT product character recognition method is proposed which can obtain a good recognition rate. Some appropriate image processing algorithms, such as Gray processing, Low-pass Filter, Median Filter, and so on, are used to eliminate the noise. Then, Character image is obtained after character segmentation and character normalization. Finally, a three-layer back propagation (BP) neural network module is constructed. In order to improve the convergence rate of the network and avoid oscillation and divergence, the BP algorithm with momentum item is used. As a result, the SMT product character recognition system is developed. Experimental results indicate that the proposed character recognition can obtain satisfactory character-recognition rate and the recognition rate reached over by 98.6% when the hidden layer of BP neural network module has 20 nodes.


2019 ◽  
Vol 11 (22) ◽  
pp. 82-92
Author(s):  
Raaid N. Hassan

This paper includes a comparison between denoising techniques by using statistical approach, principal component analysis with local pixel grouping (PCA-LPG), this procedure is iterated second time to further improve the denoising performance, and other enhancement filters were used. Like adaptive Wiener low pass-filter to a grayscale image that has been degraded by constant power additive noise, based on statistics estimated from a local neighborhood of each pixel. Performs Median filter of the input noisy image, each output pixel contains the Median value in the M-by-N neighborhood around the corresponding pixel in the input image, Gaussian low pass-filter and Order-statistic filter also be used. Experimental results shows LPG-PCA method gives better performance, especially in image fine structure preservation, compared with other general denoising algorithms.


2004 ◽  
Vol 92 (1) ◽  
pp. 408-415 ◽  
Author(s):  
Susanne Schreiber ◽  
Irina Erchova ◽  
Uwe Heinemann ◽  
Andreas V. M. Herz

Neurons integrate subthreshold inputs in a frequency-dependent manner. For sinusoidal stimuli, response amplitudes thus vary with stimulus frequency. Neurons in entorhinal cortex show two types of such resonance behavior: stellate cells in layer II exhibit a prominent peak in the resonance profile at stimulus frequencies of 5–16 Hz. Pyramidal cells in layer III show only a small impedance peak at low frequencies (1–5 Hz) or a maximum at 0 Hz followed by a monotonic decrease of the impedance. Whether the specific frequency selectivity for periodic stimuli also governs the integration of non-periodic stimuli has been questioned recently. Using frozen-noise stimuli with different distributions of power over frequencies, we provide experimental evidence that the integration of non-periodic subthreshold stimuli is determined by the same subthreshold frequency selectivity as that of periodic stimuli. Differences between the integration of noise stimuli in stellate and pyramidal cells can be fully explained by the resonance properties of each cell type. Response power thus reflects stimulus power in a frequency-selective way. Theoretical predictions based on linear system's theory as well as on conductance-based model neurons support this finding. We also show that the frequency selectivity in the subthreshold range extends to suprathreshold responses in terms of firing rate. Cells in entorhinal cortex are representative examples of cells with resonant or low-pass filter impedance profiles. It is therefore likely that neurons with similar frequency selectivity will process input signals according to the same simple principles.


2012 ◽  
Vol 256-259 ◽  
pp. 2193-2199
Author(s):  
Jin Dong Song ◽  
Shan You Li

Currently, there are two magnitude estimation approaches using predominant period for earthquake early warning, Tpmax method and Tc method. We compared Tpmax method with Tc method from the NSMP strong motion records of 22 earthquakes in United States with moment magnitude ranging from 4.1 to 7.9, to explore which method was with higher precision and could be suitable for the earthquake early warning system. Our results show that scaling relations between the two predominant period parameters, Tpmax and Tc, calculated from P-wave arrivals and earthquake magnitude are consistent with previous research. It was found that Tc method had higher precision than Tpmax method with the same filter band, and had best result in magnitude estimation resulting in a correlation coefficient of 0.78 and a standard deviation of 0.16 using 3 seconds signal after the P-wave arrival. We also found that Tc method without low-pass filter had higher accuracy than Tpmax method without low-pass filter. We recommended Tc method using 3 seconds signal after the P-wave arrival as the priority magnitude estimation method for earthquake early warning.


2017 ◽  
Vol E100.C (10) ◽  
pp. 858-865 ◽  
Author(s):  
Yohei MORISHITA ◽  
Koichi MIZUNO ◽  
Junji SATO ◽  
Koji TAKINAMI ◽  
Kazuaki TAKAHASHI

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