时间推移地震反演的连续模型与算法

针对时间推移地震反演问题建立了依赖勘探时间的数学模型,并在此基础上设计了全局收敛的连续型及逐次递归算法.将同伦方法与Tikhonov正则化方法相结合,设计了初次勘探反演的同伦-正则化方法.以三维时间推移地震为例,在连续型及逐次递归算法的基础上构造了快速的局域化反演算法.数值模拟结果说明了上述方法都是有效的.     

Uncertainties in quantitative time-lapse seismic analysis

Most seismic time-lapse studies so far have been of a qualitative nature. Identification of areas with minor or no seismic changes has been used to plan new infill drilling targets. Increased accuracy in seismic acquisition methods, in both conventional streamer surveys and newer methods such as multicomponent sea-bed seismic and permanent sensors, opens possibilities for the next step: quantitative time-lapse analysis. Quantitative methods here mean the estimation of, for instance, a change in fluid saturation from 20% water to 90% water or the estimation of a pore pressure change of 5 MPa. Explicit expressions for the uncertainties associated with estimated changes in, for instance, reservoir pressure and fluid saturation are derived. These formulae can be used to compare relative uncertainties between estimated parameters as well as to identify the critical factors in various estimation techniques. The importance of accurate rock physics input, as well as that of highly repeatable time-lapse seismic data, is emphasized. Furthermore, uncertainty analysis can be used to find optimal weight factors when the same parameter (e.g. saturation change) is estimated by two or three different techniques.     

Iterated extended Kalman filter method for time-lapse seismic full-waveform inversion

Time-lapse seismic data is useful for identifying fluid movement and pressure and saturation changes in a petroleum reservoir and for monitoring of CO₂ injection. The focus of this paper is estimation of time-lapse changes with uncertainty quantification using full-waveform inversion. The purpose of also estimating the uncertainty in the inverted parameters is to be able to use the inverted seismic data quantitatively for updating reservoir models with ensemble-based methods. We perform Bayesian inversion of seismic waveform data in the frequency domain by combining an iterated extended Kalman filter with an explicit representation of the sensitivity matrix in terms of Green functions (acoustic approximation). Using this method, we test different strategies for inversion of the time-lapse seismic data with uncertainty. We compare the results from a sequential strategy (making a prior from the monitor survey using the inverted baseline survey) with a double difference strategy (inverting the difference between the monitor and baseline data). We apply the methods to a subset of the Marmousi2 P-velocity model. Both strategies performed well and relatively good estimates of the monitor velocities and the time-lapse differences were obtained. For the estimated time-lapse differences, the double difference strategy gave the lowest errors.     

可分裂的三维陡倾角深度偏移算法

对于构造复杂和存在明显速度横向变化地区的地震资料，三维深度偏移方法能同时消除波的衍射和折射效应，且对侧面波的收敛也很显著，故其成像结果能准确地反映地质构造在地下的空间分布．文中通过对深度偏移方程进行陡倾角近似，并利用二阶中心差分网格将三维方程离散分裂，极大地提高了运算效率和节约存贮量，同时在波场外推计算中采用了一种与差分相似的时移算法，较好地解决了差分频散现象和数值稳定性问题．理论模型和实际资料的试验结果进一步验证了算法的可行性和实用性．     

基于动态图像变形的PP与PS波层位直接匹配

多分量地震资料的矢量偏移、多波地震资料的联合解释与反演均需要估算纵横波的速度比,实现纵波与转换横波在时间或深度域的匹配.基于DTW,本文实现了一种适用于PP与PS波直接匹配的动态图像变形算法.该算法分为三个部分:首先,使用二阶对称动态规划算法逐样点递归计算PP与PS波走时或深度的误差累积和;其次,在以误差累积和为目标函数的回溯阶段设定变形窗,并在纵横波速比约束的变形窗内递归回溯搜索匹配路径;最后,根据最大相关系数判定准则在匹配路径中确定最佳匹配路径,获得使PP与PS波匹配的拉伸或压缩时移量.利用所获得的拉伸压缩时移量计算纵横波速度比就可以实现PP与PS波之间的匹配.模型与实际陆上多分量地震资料测试结果表明:该方法具有较高的匹配精度,且对于信噪比、相似度较低的多分量地震资料,该方法也能产生较好的匹配效果.     

复数子波匹配追踪算法识别薄层砂体

针对东营凹陷滩坝砂岩薄砂体的预测识别问题,研究了复小波匹配追踪方法.从地震信号morlet小波分解及重构分析入手,讨论了重构地震信号时关于频率、振幅、相位及时移参数的选取方法及其具体的选取变量.并就关键的振幅参数,研究了改善的计算方法.常规的匹配追踪算法扫描地震信号的所有时间点和频率.在本文中,为了改善时频分辨率,采用局部扫描主频和子波的时间延迟.在具体实现过程中,采用计算地震信号的平均瞬时频率和地震信号的瞬时包络处的时间,做为采样频率和时间采样点,得到与地震信号最佳相关的子波.对研究的方法从理论模型和实际资料进行了论证分析,证明理论上正确合理,实际应用效果显著.     

Review Paper: Post-stack 4D seismic time-shifts: Interpretation and evaluation

A review and analysis of post-stack time-lapse time-shifts has been carried out that covers published literature supplemented by in-house datasets available to the authors. Time-shift data are classified into those originating from geomechanical effects and those due to fluid saturation changes. From these data, conclusions are drawn regarding the effectiveness of post-stack time-shifts for overburden and reservoir monitoring purposes. A variety of field examples are shown that display the range and magnitude of variation for each class of application. The underlying physical mechanisms creating these time-shifts are then described, and linked to a series of generic and field-specific rock physics calculations that predict their magnitudes. These calculations serve as a guide for practitioners wishing to utilize this information on their own datasets. Conclusions are drawn regarding the reliability of this attribute for monitoring purposes, and the extent to which further development is required and how it should be reported by authors.     

Direct correlation of 4D seismic with well activity for a clarified dynamic reservoir interpretation

A method to provide an improved time‐lapse seismic attribute for dynamic interpretation is presented. This is based on the causal link between the time‐lapse seismic response and well production activity taken over time. The resultant image is obtained by computing correlation coefficients between sequences of time‐lapse seismic changes extracted over different time intervals from multiply repeated seismic and identical time sequences of cumulative fluid volumes produced or injected from the wells. Maps of these cross‐correlations show localized, spatially contiguous signals surrounding individual wells or a specific well group. These may be associated with connected regions around the selected well or well group. Application firstly to a synthetic data set reveals that hydraulic compartments may be delineated using this method. A second application to a field data set provides empirical evidence that a connected well‐centric fault block and active geobody can be detected. It is concluded that uniting well data and time‐lapse seismic using our proposed method delivers a new attribute for dynamic interpretation and potential updating of the model for the producing reservoir.     

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.     

在X模式单道成像与观测系统重复性关系下的多道观测系统重复性

时移地震中新提出的多道观测系统重复性,逐一应用于面元,可以给出每个面元单一的观测系统重复性,形成对应叠后成像的地震道重复性的面分布,对于评估时移地震重复性具有重要意义.前人研究抽象了多道间观测系统重复性与单道间观测系统重复性的关系,给出了多道观测系统重复性的衡量方法及其理论依据.其理论中依赖了地震数据重复性与单道观测系统重复性的线性关系模型,而这一关系在单道观测系统重复性的有限范围内较为准确.针对这一问题,本文提出了X模式拟合的关系模型,与全范围的单道地震数据重复性随观测系统重复性的变化趋势更好地吻合,并采用对大单道观测系统重复性的向X节点的收缩,使原多道观测系统重复性的相应关系在整个数据范围内基本成立.基于实际数据的研究表现了该方法的数据分析结果的新特性和应用价值.     

基于相关参数的时移地震互均化质量监控方法研究

在时移地震技术的实际应用过程中,限于观测条件及处理流程等因素的影响,不同时期所获得的地震数据的一致性往往是较差的.这些不一致通常表现为地震资料在振幅、时间延迟、频率、相位等方面的差异.为了消除这些差异带来的影响,通常使用的方法就是进行时移地震的互均化处理,本文讨论了一种有效的时移地震互均化质量监控方法,用来评定时移资料的优劣,互均化结果的好坏,能够为时移地震可行性分析及互均化处理流程带来一定的帮助,同时可以起到很好的指导意义.     

反卷积在人工震源数据处理中的应用

震源到接收台站之间的地层响应函数能够反映地下介质信息。对地震波传播过程中的卷积模型进行推导:记录信号是众多震源子波经过时移加权叠加的结果;通过反卷积方法可去除震源子波信息,提取震源到接收台站之间的地层响应函数;地层响应函数中第一个突跳值对应的时间即为P波走时。在河北赤城—张北地区进行人工震源实验,通过反卷积计算得到该地区地层响应函数剖面图,得出P波波速约6 km/s。利用人工震源系统还可以对地下介质波速变化进行长期动态监测,对地震预测具有一定意义。     

多尺度全变分法及其在时移地震中的应用

本文针对时间推移地震本身包含不同时期的两次或者两次以上的勘探反问题,构造了一种快速有效的反演方法--多尺度全变分法.通过引入全变分正则化来代替传统的Tikhonov正则化,针对待反演参数不连续的情况,提高了算法精度.为了提高计算效率,引入了多尺度方法,从而构造了多尺度全变分方法.在数值模拟中,针对一个时间推移地震反演问题对多尺度-Tikhonov正则化法、单一尺度全变分法、以及本文所构造的多尺度全变分法进行了比较.结果表明,本文所提出的多尺度全变分法是一种稳定、快速和精确的反演方法.     

Statistical facies classification from multiple seismic attributes: comparison between Bayesian classification and expectation–maximization method and application in petrophysical inversion

We present here a comparison between two statistical methods for facies classifications: Bayesian classification and expectation–maximization method. The classification can be performed using multiple seismic attributes and can be extended from well logs to three‐dimensional volumes. In this work, we propose, for both methods, a sensitivity study to investigate the impact of the choice of seismic attributes used to condition the classification. In the second part, we integrate the facies classification in a Bayesian inversion setting for the estimation of continuous rock properties, such as porosity and lithological fractions, from the same set of seismic attributes. The advantage of the expectation–maximization method is that this algorithm does not require a training dataset, which is instead required in a traditional Bayesian classifier and still provides similar results. We show the application, comparison, and analysis of these methods in a real case study in the North Sea, where eight sedimentological facies have been defined. The facies classification is computed at the well location and compared with the sedimentological profile and then extended to the 3D reservoir model using up to 14 seismic attributes.     

Deriving effects of pressure depletion on elastic framework moduli from sonic logs

We have developed a method to determine the effect of pore pressure depletion on elastic framework moduli, by utilizing sonic logs from wells drilled at different locations through a reservoir at varying depletion stages. This is done by first inverting the sonic logs for elastic framework bulk and shear moduli, thus carefully removing pressure dependent fluid effects. By crossplotting these elastic framework moduli against an increase in net stress (which is directly related to depletion), we derive the stress sensitivity of the elastic framework moduli. We found that the observed stress sensitivity was consistent with time-lapse seismic results and that the sensitivity derived from the sonic logs was much smaller than predicted by hydrostatic measurements on core samples. This method is applicable to depletion scenarios in mature fields and can be used both for modelling and inverting time-lapse seismic data for effects of pore pressure depletion on seismic data.     

4-D inversion of DC resistivity monitoring data acquired over a dynamically changing earth model

Geophysical monitoring is used principally to interpret the locations and amounts of ground condition changes. To achieve these objectives, differences are computed and examined using time-lapse images calculated under the time-invariant static assumption, that any material property changes during the data measurement can be practically ignored. These monitored data, however, can be contaminated with noise and frequently generate false anomalies of ground condition changes. Furthermore, the assumption of the static model can be invalid if the material property changes significantly during data acquisition. To alleviate these problems, we developed a new least-squares inversion algorithm that allows for the subsurface properties to continuously change in time. We define the subsurface structure and the entire monitoring data in the space–time domain, allowing us to obtain a four-dimensional space–time model using just one inversion process. We introduce the regularizations not only in the space domain but also in time, resulting in reduced inversion artifacts and improved stability of the inverse problem. We demonstrated the performance of the proposed algorithm through numerical experiments that assumed several scenarios of ground condition changes and data acquisition sequences. Finally, the applicability to field data was proven by applying the developed algorithm to the monitoring data of crosshole resistivity tomography jointly performed with a dye tracer flooding experiment. This experiment had a small enough scale that we could not ignore the change of material properties during the data measurement.     

四维地震资料处理及其关键

四维地震利用时延三维地震资料的差异来解释地下储层流体的变化，时延地震资料的差异除了受地下储层流体因素的影响外，还受采集和处理因素的影响。为了尽可能的减少或消除由非储层因素所引起的差异，四维地震资料处理总的要求是相对振幅保持处理，高信噪比处理和一致性处理，一致性处理是四维地震资料特有的处理，其一般处理原则是：（１）调查影响四维地震资料非穗生的原因；（２）保持处理流程的一致性；（３）尽量保持相同的偏移     

4D active time constrained resistivity inversion

Techniques that incorporate regularization in space and time have been proposed to reduce inversion artifacts that may lead a misinterpretation of geophysical monitoring data. Applying this time regularization, however, may result in a model too smoothly carrying in the time domain. To alleviate this problem, we propose an algorithm for inverting time-lapse resistivity monitoring data.Here the time regularization is not considered to be constant between different time steps but is now allowed to vary depending on the degree of spatial resistivity changes occurring between different monitoring stages. Two methods are proposed to assign different time Lagrangian values, one based on a pre-estimation during execution time, and one using a-priori information. Both methods require a threshold to characterize the significance of the observed resistivity changes with time. We performed numerous numerical experiments using synthetic data to provide reasonable threshold values. Synthetic data tests illustrate that the new algorithm, named 4D Active Time Constrained (4D-ATC), produces in most cases improved time-lapse images when compared with existing techniques. Further the applicability of the new scheme is demonstrated with real data. Overall, the new algorithm is shown to be a useful tool for processing time-lapse resistivity data, which can be used with minor modifications to other types of time-lapse geophysical data.     

高频GNSS实时地震学与地震预警研究现状

为实现从注重灾后救助向注重灾前预防转变,如何提高地震灾害监测预警和风险防范能力成为我们关注的重点.本文给出了国际上GNSS位移记录、强震动加速度记录、测震速度记录在地震预警中的应用现状,并总结了各自的特点,归纳出围绕高频GNSS地震学在震级与破裂过程实时反演中的几个需要进一步研究的关键问题：（1）引入北斗系统,基于高频GNSS（GPS/BDS）双系统的实时位移解算方法来提高实时单站位移解算精度,使实时解算精度达到厘米级;（2）开展强震仪加速度记录基线偏移校正研究,弥补地震近场GNSS站密度不足问题;（3）强震仪加速度记录与GNSS位移记录特点不同,开展强震仪加速度数据与GNSS位移数据实时融合处理研究,快速获得包含丰富地震形变和速率的波形数据;（4）测震学方法可快速估算震级,但是在强震发生时会出现震级饱和现象,造成震级估算偏低.需要开展基于GNSS位移时间序列的多种方法相结合的实时震级估算方法研究,通过与地震学方法比较和结合,来得到精度高、计算快的震级估值算法;（5）基于高频GNSS、断层初始模型快速选取、断层尺度、参数自适应调整是快速判断断层破裂方向的基础,在断层破裂过程自适应准实时反演算法方面需要进一步加强.通过国内外研究现状调研、分析,表明基于高频GNSS地震学的震级快速确定、震源破裂过程准实时反演算法的发展将对我国地震预警系统从"二网融合"到"三网融合"提供坚实的技术支撑.     

Simultaneous time-lapse electrical resistivity inversion

Time-lapse monitoring is a powerful tool for observing dynamic changes in the subsurface. In particular it offers the potential for achieving inversion results with increased fidelity through the inclusion of complementary information from multiple time-steps. This inclusion of complementary information can reduce the need for spatial smoothing, without adding inversion artifacts to the resulting images. Commonly used time-lapse inversion methods include the ratio method, cascaded time-lapse inversion, difference inversion and differencing independent inversions. We introduce two additional methods in which both time-lapse data sets are inverted simultaneously. In the first, called temporally constrained time-lapse inversion, inversion of both datasets is done under a single optimization procedure and constraints are added to the regularization to ensure that the changes from one time to another are smooth. In the second method, called simultaneous time-lapse inversion, the inversions at time 1 and time 2 are performed simultaneously and constraints of smoothness and closeness to a reference model are applied to the difference image produced at each iteration, and subsequently, the constraints are updated at each iteration. Through both a numerical and a field example we compare the results of common time-lapse inversion methods as well as the introduced approaches. We found that of the commonly used time-lapse inversion methods the difference inversion method produced the best resolution of time-lapse changes and was the most robust in the presence of noise. However, we found that the alternative approach of simultaneous time-lapse inversion produced the best reconstruction of modeled EC changes in the numerical example and easily interpretable high resolution difference images in the field example. Moreover, there was less tailoring of regularization parameters with our simultaneous time-lapse approach, suggesting that it will lend itself well to an automated inversion code.