Passive seismic data primary estimation and noise removal via focal‐denoising closed‐loop surface‐related multiple elimination based on 3D L1‐norm sparse inversion

Passive seismic has recently attracted a great deal of attention because non‐artificial source is used in subsurface imaging. The utilization of passive source is low cost compared with artificial‐source exploration. In general, constructing virtual shot gathers by using cross‐correlation is a preliminary step in passive seismic data processing, which provides the basis for applying conventional seismic processing methods. However, the subsurface structure is not uniformly illuminated by passive sources, which leads to that the ray path of passive seismic does not fit the hyperbolic hypothesis. Thereby, travel time is incorrect in the virtual shot gathers. Besides, the cross‐correlation results are contaminated by incoherent noise since the passive sources are always natural. Such noise is kinematically similar to seismic events and challenging to be attenuated, which will inevitably reduce the accuracy in the subsequent process. Although primary estimation for transient‐source seismic data has already been proposed, it is not feasible to noise‐source seismic data due to the incoherent noise. To overcome the above problems, we proposed to combine focal transform and local similarity into a highly integrated operator and then added it into the closed‐loop surface‐related multiple elimination based on the 3D L1‐norm sparse inversion framework. Results proved that the method was capable of reliably estimating noise‐free primaries and correcting travel time at far offsets for a foresaid virtual shot gathers in a simultaneous closed‐loop inversion manner.     

Wavelet‐based cepstrum decomposition of seismic data and its application in hydrocarbon detection

How to use cepstrum analysis for reservoir characterization and hydrocarbon detection is an initial question of great interest to exploration seismologists. In this paper, wavelet‐based cepstrum decomposition is proposed as a valid technology for enhancing geophysical responses in specific frequency bands, in the same way as traditional spectrum decomposition methods do. The calculation of wavelet‐based cepstrum decomposition, which decomposes the original seismic volume into a series of common quefrency volumes, employs a sliding window to move over each seismic trace sample by sample. The key factor in wavelet‐based cepstrum decomposition is the selection of the sliding‐window length as it limits the frequency ranges of the common quefrency section. Comparison of the wavelet‐based cepstrum decomposition with traditional spectrum decomposition methods, such as short‐time Fourier transform and wavelet transform, is conducted to demonstrate the effectiveness of the wavelet‐based cepstrum decomposition and the relation between these two technologies. In hydrocarbon detection, seismic amplitude anomalies are detected using wavelet‐based cepstrum decomposition by utilizing the first and second common quefrency sections. This reduces the burden of needing dozens of seismic volumes to represent the response to different mono‐frequency sections in the interpretation of spectrum decomposition in conventional spectrum decomposition methods. The model test and the application of real data acquired from the Sulige gas field in the Ordos Basin, China, confirm the effectiveness of the seismic amplitude anomaly section using wavelet‐based cepstrum decomposition for discerning the strong amplitude anomalies at a particular quefrency buried in the broadband seismic response. Wavelet‐based cepstrum decomposition provides a new method for measuring the instantaneous cepstrum properties of a reservoir and offers a new field of processing and interpretation of seismic reflection data.     

基于时频稀疏性分析法的低信噪比微震事件识别与恢复

微震监测是直观评价压裂过程和压裂效果的有效手段.微震事件识别是微震监测的首要步骤.然而对于低信噪比微震监测数据,常规识别方法很难取得满意效果.基于微震事件在时频域中的稀疏性,本文提出利用Renyi熵值表示微震监测数据的时频稀疏程度,并以时频距离为约束条件,建立以低熵值的道数为判别阈值的目标函数.本文方法能在识别出微震事件的同时,恢复出较为清晰的微震事件.通过数值计算和对实际监测数据的测试,表明该方法对低信噪比的微震监测数据有较好的处理效果.     

Microseismic events enhancement and detection in sensor arrays using autocorrelation‐based filtering

Passive microseismic data are commonly buried in noise, which presents a significant challenge for signal detection and recovery. For recordings from a surface sensor array where each trace contains a time‐delayed arrival from the event, we propose an autocorrelation‐based stacking method that designs a denoising filter from all the traces, as well as a multi‐channel detection scheme. This approach circumvents the issue of time aligning the traces prior to stacking because every trace's autocorrelation is centred at zero in the lag domain. The effect of white noise is concentrated near zero lag; thus, the filter design requires a predictable adjustment of the zero‐lag value. Truncation of the autocorrelation is employed to smooth the impulse response of the denoising filter. In order to extend the applicability of the algorithm, we also propose a noise prewhitening scheme that addresses cases with coloured noise. The simplicity and robustness of this method are validated with synthetic and real seismic traces.     

Full‐waveform based microseismic event detection and signal enhancement: An application of the subspace approach

Microseismic monitoring has proven invaluable for optimizing hydraulic fracturing stimulations and monitoring reservoir changes. The signal to noise ratio of the recorded microseismic data varies enormously from one dataset to another, and it can often be very low, especially for surface monitoring scenarios. Moreover, the data are often contaminated by correlated noises such as borehole waves in the downhole monitoring case. These issues pose a significant challenge for microseismic event detection. In addition, for downhole monitoring, the location of microseismic events relies on the accurate polarization analysis of the often weak P‐wave to determine the event azimuth. Therefore, enhancing the microseismic signal, especially the low signal to noise ratio P‐wave data, has become an important task. In this study, a statistical approach based on the binary hypothesis test is developed to detect the weak events embedded in high noise. The method constructs a vector space, known as the signal subspace, from previously detected events to represent similar, yet significantly variable microseismic signals from specific source regions. Empirical procedures are presented for building the signal subspace from clusters of events. The distribution of the detection statistics is analysed to determine the parameters of the subspace detector including the signal subspace dimension and detection threshold. The effect of correlated noise is corrected in the statistical analysis. The subspace design and detection approach is illustrated on a dual‐array hydrofracture monitoring dataset. The comparison between the subspace approach, array correlation method, and array short‐time average/long‐time average detector is performed on the data from the far monitoring well. It is shown that, at the same expected false alarm rate, the subspace detector gives fewer false alarms than the array short‐time average/long‐time average detector and more event detections than the array correlation detector. The additionally detected events from the subspace detector are further validated using the data from the nearby monitoring well. The comparison demonstrates the potential benefit of using the subspace approach to improve the microseismic viewing distance. Following event detection, a novel method based on subspace projection is proposed to enhance weak microseismic signals. Examples on field data are presented, indicating the effectiveness of this subspace‐projection‐based signal enhancement procedure.     

单一地震事件与多个地震事件的定位方法及应用

主要介绍各种地震定位方法,概述各种地震定位方法的基本原理,重点介绍Geiger的经典方法以及在此基础上建立的各种线性方法:单一地震事件定位法与多个地震事件定位法以及对每一种地震定位方法的应用情况,尤其是国内的应用情况做了总结;同时指出各种方法的特点,并进行相应的比较.     

Evaluation of a passive gap damper to control displacements in a shaking test of a seismically isolated three‐story frame

Recent studies have indicated uncertainty about the performance limit states of seismically isolated buildings in very large earthquakes, especially if the isolator displacement demands exceed the seismic gap and induce pounding. Previous research has shown the benefit of providing phased supplemental damping that does not affect the isolation system response in a design event. A phased passive control device, or gap damper, was designed, fabricated, and experimentally evaluated during shake table testing of a quarter scale base‐isolated three‐story steel frame building. Identical input motions were applied to system configurations without a gap damper and with a gap damper, to directly assess the influence of the gap damper on displacement and acceleration demands. The gap damper was observed to reduce displacement demands by up to 15% relative to the isolated system without the gap damper. Superstructure floor accelerations increased substantially because of damper activation, but were limited to a peak of about 1.18 g. The gap damper reduces displacement most effectively if the ground motion contains one or more of the following characteristics: the spectral displacement increases with increasing period near the effective period of the isolation system, the motion is dominated by a single large pulse rather than multiple cycles at a consistent intensity, and the motion has a dominant component aligned with a major axis of the structure. Copyright © 2016 John Wiley & Sons, Ltd.     

Earthquake detection probability within a seismically quiet area: application to the Bruchsal geothermal field

In applications such as oil and gas production, deep geothermal energy production, underground storage, and mining, it is common practice to implement local seismic networks to monitor and to mitigate induced seismicity. For this purpose, it is crucial to determine the capability of the network to detect a seismic event of predefined magnitude in the target area. The determination of the magnitude of completeness of a network is particularly required to properly interpret seismic monitoring results. We propose a method to compute the detection probability for existing local seismic networks, which (i) strictly follows the applied detection sequence; (ii) estimates the detection capability where seismicity has not yet occurred; and (iii) delivers the results in terms of probabilities. The procedure includes a calibration of a local magnitude scale using regional earthquakes recorded by the network and located outside the monitored area. It involves pre‐processing of the seismograms recorded at each station as performed during the triggering sequence, which is assumed based on amplitude thresholds. Then, the calibrated magnitude–distance–amplitude relations are extrapolated at short distances and combined to reproduce the network detection sequence. This generates a probability to detect a seismic event of a given magnitude at a specified location. This observation‐based approach is an alternative to a fully theoretical detection capability modelling and includes field conditions. Seismic wave attenuation by geometrical spreading and intrinsic attenuation, site effect, and instrumental responses are partly accounted for by the calibration. We apply this procedure on the seismic network deployed in the Bruchsal geothermal field (Germany). Although the system was in good working order, no induced seismicity was identified in the area between June 2010, when monitoring started, and November 2012. The recording of distant seismicity during this time period, however, allowed the application of the proposed procedure. According to the applied network detection parameters, the results indicate that the absence of seismicity can be interpreted as a 95% probability that no seismic event with M_L ≥ 0.7 occurred below the network at 2.4‐km depth, i.e., in the geothermal reservoir.     

时频峰值滤波去噪技术及其应用

本文将时频峰值滤波(TFPF)去噪技术应用于共炮点地震资料的随机噪声压制.时频峰值滤波技术是通过频率调制将信号调制成解析信号的瞬时频率,利用解析信号的Wigner-Ville分布的峰值进行瞬时频率估计,恢复有效信号,与其它去噪方法相比,TFPF具有在较少的约束条件下压制强随机噪声的优点.本文针对实际地震资料的非线性特性,利用加窗的Wigner-Ville分布实现TFPF,使得地震信号在一个窗长内近似满足线性瞬时频率条件,减小由地震信号非线性引起的偏差.本文对共炮点地震记录做时频峰值滤波处理,滤波结果表明在地震勘探资料中存在强随机噪声的情况下,利用局部线性化处理的时频峰值滤波技术可以有效地压制地震资料中的随机噪声,恢复出湮没在随机噪声中的地震反射信号.信噪比提高3～6 dB.     

图像边缘检测方法在地震剖面同相轴自动检测中的应用研究

为了提高地震剖面的信噪比和分辨率,使同相轴容易识别和追踪,便于地震资料解释,应用图像边缘检测方法检测地震剖面的同相轴.通过对比各种边缘检测方法对地震剖面的边缘检测效果,确定使用Canny算子对地震剖面进行边缘检测.但边缘检测的结果是灰度突变区域的包络线,并不能直接作为同相轴检测结果.根据地层反射同相轴灰度值较大这一特性,提取强灰度包络线的中轴作为同相轴的检测追踪结果,得到了正确的同相轴检测结果.并经过消除检测结果中的斑点边缘后,使同相轴显示更加清晰.     

The identification of an appropriate Minimum Inter‐event Time (MIT) based on multifractal characterization of rainfall data series

Different hydrological models of sediment entrainment, infiltration, overland flow production, soil loss, landslide occurrence, among others, need rainfall events data. The Minimum Inter‐event Time (MIT) used to separate rainfall events affects their properties. Therefore, it is highly important their correct definition. Various event definitions are commonly used in hydrology, and a high variety of MIT is applied. In this work, an easy method is proposed for deciding the proper MIT in a certain place when dealing with hourly rainfall data series. This new methodology is based on the scale invariance properties of rainfall, analysed with both multifractal and Self‐Organized Criticality theories. The similarity between some parameters from both analyses allows picking out the more appropriate MIT for the hourly rainfall data sets analysed, in Malaga (Southern Spain) and Bullileo (Central Chile). The method can be applied for different rainfall time resolutions according to the purpose of the model that needs the rain event information. Copyright © 2016 John Wiley & Sons, Ltd.     

An automated cross‐validation method to assess seismic time‐to‐depth conversion accuracy: a case study on the Cooper and Eromanga basins,Australia

Selecting a seismic time‐to‐depth conversion method can be a subjective choice that is made by geophysicists, and is particularly difficult if the accuracy of these methods is unknown. This study presents an automated statistical approach for assessing seismic time‐to‐depth conversion accuracy by integrating the cross‐validation method with four commonly used seismic time‐to‐depth conversion methods. To showcase this automated approach, we use a regional dataset from the Cooper and Eromanga basins, Australia, consisting of 13 three‐dimensional (3D) seismic surveys, 73 two‐way‐time surface grids and 729 wells. Approximately 10,000 error values (predicted depth vs. measured well depth) and associated variables were calculated. The average velocity method was the most accurate overall (7.6 m mean error); however, the most accurate method and the expected error changed by several metres depending on the combination and value of the most significant variables. Cluster analysis tested the significance of the associated variables to find that the seismic survey location (potentially related to local geology (i.e. sedimentology, structural geology, cementation, pore pressure, etc.), processing workflow, or seismic vintage), formation (potentially associated with reduced signal‐to‐noise with increasing depth or the changes in lithology), distance to the nearest well control, and the spatial location of the predicted well relative to the existing well data envelope had the largest impact on accuracy. Importantly, the effect of these significant variables on accuracy were found to be more important than choosing between the four methods, highlighting the importance of better understanding seismic time‐to‐depth conversions, which can be achieved by applying this automated cross‐validation method.     

Low signal-to-noise event detection based on waveform stacking and cross-correlation: application to a stimulation experiment

We study the microseismicity (M _L ?<?2) in the region of Landau, SW Germany. Here, due to thick sediments (~3?km) and high cultural seismic noise, the signal-to-noise ratio is in general very low for microearthquakes. To gain new insights into the occurrence of very small seismic events, we apply a three-step detection approach and are able to identify 207 microseismic events (?1?<?M _L ?<?~1) with signal-to-noise ratios smaller than 3. Recordings from a temporary broadband network are used with station distances of approximately 10?km. First, we apply a short-term to long-term average detection algorithm for data reduction. The detection algorithm is affected severely by transient noise signals. Therefore, the most promising detections, selected by coinciding triggers and high-amplitude measures, are reviewed manually. Thirteen seismic events are identified in this way. Finally, we conduct a cross-correlation analysis. As master template, we use the stacked waveforms of five manually detected seismic events with a repeating waveform. This search reveals additional 194 events with a cross-correlation coefficient exceeding 0.65 which ensures a stable identification. Our analysis shows that the repeating events occurred during the stimulation of a geothermal reservoir within a source region of only about 0.5?km³. Natural background seismicity exceeding our detection level of M _L ?~?0.7 is not found in the region of Landau by our analysis.     

基于S变换的软阈值滤波在深地震反射数据处理中的应用

深地震反射原始单炮数据是非平稳的弱能量反射信号, 信噪比较低. 如何提高信噪比一直是深地震反射数据前处理中的一大难题. S变换是一种适用于分析非平稳信号的时频变换方法. 同其他分析时变信号的方法相比, S变换的基本小波不必满足小波在时间域均值为零的容许性条件, 它的时频分辨率与分析信号的频率有关, 且其在时间域的积分可以得到傅里叶频谱,其反变换也简单. 因此, S变换容易表示深地震反射信号复杂的时频特性. 本文在S变换的基础上, 利用软阈值滤波方法对深地震反射数据进行处理, 实验结果表明, 该方法有效地提高了信噪比, 压制了有效频带范围内的混频干扰, 突出了弱反射信号, 使得波组信息更加丰富, 有利于连续追踪有效反射波组和识别薄地层, 特别是提高了深部Moho界面反射层位的分辨率, 为深地震反射剖面后续处理和准确解释奠定了基础.     

Severe soil erosion during a 3‐day exceptional rainfall event: combining modelling and field data for a fallow cereal field

Exceptional rainfall events cause significant losses of soil, although few studies have addressed the validation of model predictions at field scale during severe erosive episodes. In this study, we evaluate the predictive ability of the enhanced Soil Erosion and Redistribution Tool (SERT‐2014) model for mapping and quantifying soil erosion during the exceptional rainfall event (~235 mm) that affected the Central Spanish Pyrenees in October 2012. The capacity of the simulation model is evaluated in a fallow cereal field (1.9 ha) at a high spatial scale (1 × 1 m). Validation was performed with field‐quantified rates of soil loss in the rills and ephemeral gullies and also with a detailed map of soil redistribution. The SERT‐2014 model was run for the six rainfall sub‐events that made up the exceptional event, simulating the different hydrological responses of soils with maximum runoff depths ranging between 40 and 1017 mm. Predicted average and maximum soil erosion was 11 and 117 Mg ha^?1 event^?1, respectively. Total soil loss and sediment yield to the La Reina gully amounted to 16.3 and 9.0 Mg event^?1. These rates are in agreement with field estimations of soil loss of 20.0 Mg event^?1. Most soil loss (86%) occurred during the first sub‐event. Although soil accumulation was overestimated in the first sub‐event because of the large amount of detached soil, the enhanced SERT‐2014 model successfully predicted the different spatial patterns and values of soil redistribution for each sub‐event. Further research should focus on stream transport capacity. Copyright © 2014 John Wiley & Sons, Ltd.     

Application of diffracted wave analysis to time‐lapse seismic data for CO2 leakage detection

Time‐lapse seismic analysis is utilized in CO₂ geosequestration to verify the CO₂ containment within a reservoir. A major risk associated with geosequestration is a possible leakage of CO₂ from the storage formation into overlaying formations. To mitigate this risk, the deployment of carbon capture and storage projects requires fast and reliable detection of relatively small volumes of CO₂ outside the storage formation. To do this, it is necessary to predict typical seepage scenarios and improve subsurface seepage detection methods. In this work we present a technique for CO₂ monitoring based on the detection of diffracted waves in time‐lapse seismic data. In the case of CO₂ seepage, the migrating plume might form small secondary accumulations that would produce diffracted, rather than reflected waves. From time‐lapse data analysis, we are able to separate the diffracted waves from the predominant reflections in order to image the small CO₂ plumes. To explore possibilities to detect relatively small amounts of CO₂, we performed synthetic time‐lapse seismic modelling based on the Cooperative Research Centre for Greenhouse Gas Technologies (CO2CRC) Otway project data. The detection method is based on defining the CO₂ location by measuring the coherency of the signal along diffraction offset‐traveltime curves. The technique is applied to a time‐lapse stacked section using a stacking velocity to construct offset‐traveltime curves. Given the amount of noise found in the surface seismic data, the predicted minimum detectable amount of CO₂ is 1000–2000 tonnes. This method was also applied to real data obtained from a time‐lapse seismic physical model. The use of diffractions rather than reflections for monitoring small amounts of CO₂ can enhance the capability of subsurface monitoring in CO₂ geosequestration projects.     

A new passive rolling‐pendulum vibration absorber using a non‐axial‐symmetrical guide to achieve bidirectional tuning

A new, passive, vibroprotective device of the rolling‐pendulum tuned mass damper type is presented that, relying on a proper three‐dimensional guiding surface, can simultaneously control the response of the supporting structure in two mutually orthogonal horizontal directions. Unlike existing examples of ball vibration absorbers, mounted on spherical recesses and effective for axial‐symmetrical structures, the new device is bidirectionally tuneable, by virtue of the optimum shape of the rolling cavity, to both fundamental structural modes, even when the corresponding natural frequencies are different, in such a case recurring to an innovative non‐axial‐symmetrical rolling guide. Based on Appell's non‐holonomic mechanics, a non‐linear dynamic model is first derived for the bidirectional absorber mounted on a 1‐storey 3‐degrees‐of‐freedom linear structure translating under the effect of both imparted base motion and applied dynamic forces. A laboratory‐scaled prototype of the device is then tested to experimentally demonstrate the bidirectional tuning capability and to validate the mathematical model. The design procedure and the seismic performance of the absorber are finally exemplified through numerical simulation. Copyright © 2009 John Wiley & Sons, Ltd.     

Development and experimental evaluation of a passive gap damper device to prevent pounding in base‐isolated structures

Studies have shown the effectiveness of providing supplemental energy dissipation in base‐isolated structures to reduce displacements at the isolation level. A previous analytical study demonstrated the benefits of providing this energy dissipation at a specified gap larger than the design displacement. The gap before engagement allows the base isolation system to meet performance criteria in varying levels of ground excitation. Use of this ‘gap damper’ device eliminates undesirable effects often exhibited with large amounts of supplemental damping at lower intensity motions. Using results from an analytical study, the primary purpose of this research was to develop devices for practical implementation. Development of the devices demanded simplicity, feasibility, economy, and reliability to be an effective option in building design and construction. Multiple designs were proposed, and a final design was chosen based on selection criteria and finite element analyses. The device was designed and tested in Auburn University's Structural Research Lab. Experimental results were compared with theoretical models to verify behavior and make necessary adjustments for a shake table experiment. The design parameters were selected to accommodate re‐use of the device for the shake table test. Copyright © 2015 John Wiley & Sons, Ltd.     

F检测算法及其在识别地震地表反射波震相中的初步应用

地震P波波列中地表反射波pP或sP震相的准确识别,对地震震源深度的精确测定具有重要作用.基于新疆和田地震台阵部分地震记录数据,利用F检测算法对震中距分别为22.1°,6.44°和39.62°的3次地震事件进行了地表反射波pP或sP震相检测.结果表明,应用F检测分析新疆和田小孔径地震台阵数据,可以帮助分析人员识别地震的地...