FIRST ARRIVAL PICKING ON COMMON-OFFSET TRACE COLLECTIONS FOR AUTOMATIC ESTIMATION OF STATIC CORRECTIONS*

The increase in the number of geophone groups in production records during recent years and the requirement for accurate basic static corrections for high resolution records have made it necessary to develop sufficiently accurate automatic techniques for the determination of static corrections. A fully automatic method is presented which makes use of the delay-time method in order to compute static corrections at each shot position. Delay times, weathering and subweathering velocities are determined from automatic picks of the first arrivals on common-offset trace collections. It is assumed that the weathering is a single layer and that the dip of the subweathering layer under the geophone groups is small. The picking routine is fully automatic and successful in most cases, provided the signal-to-noise ratio is sufficiently high. The subsequent filtering of erroneous values for picked times is performed by means of statistical techniques, using curves of picked times on common-offset trace collections. If the distance between receivers and shot-points on the profile is sufficiently short, one can expect only little change in the picked times of two contiguous traces. The method is well adapted to end-on spreads with a great number of traces, where distances between geophone groups are short. Examples are presented showing the possibilities of the method for the determination of long wavelength as well as short wavelength components of static corrections.     

ADAPTIVE PICKING OF REFRACTED FIRST ARRIVALS1

Static correction computations require knowledge of the refracted traveltimes. Zero-phase wavelet sources cannot be picked reliably when incoherent picking techniques are used. Assuming a complex convolutional model for Vibroseis, a coherent picking technique based on the matched filter is described. In order to match the filter to the first arrival wavelet an adaptive algorithm is used. This allows the filter to change both with shot and offset so that all the properties of matched filtering such as improvement of S/N and resolution can be exploited. Incoherent picking is used before coherent picking to improve the convergence of adaptive picking.     

人工神经网络方法在地震预报中的初步应用

以陕西地区的地震为例，探讨了人工神经网络方法在地震预报中的应用。预报因子采用Ｋｅｉｌｉｓ－Ｂｏｒｏｋ提出的地震流函数。结果表明，人工神经网络方法能够较好地学习复杂的预报因子和预报对象的关系，模拟地震预报问题，预报效果也较好，有广阔的应用前景。     

用人工神经网络实现地震记录中的废道自动切除

切除废道（即道编辑）的工作是地震信号处理中重要而又工作量巨大的一步.本文提出了一种用人工神经网络实现的自动切除方法,所用的神经网络模型为新奇滤波器模型,方法简单实用,切除效果令人满意.文中介绍了方法的原理并给出了几个实验结果.     

用人工神经网络实现地震记录中的废道自动切除

切除废道（即道编辑）的工作是地震信号处理中重要而又工作量巨大的一步.本文提出了一种用人工神经网络实现的自动切除方法,所用的神经网络模型为新奇滤波器模型,方法简单实用,切除效果令人满意.文中介绍了方法的原理并给出了几个实验结果.     

多级BP神经网络石油测井信号分类器

本文提出了一种利用多级ＢＰ神经网络进行石油测井信号分类的新方法．介绍了用多级ＢＰ网络处理测井信号的分类器算法和网络结构，并给出了针对理论模拟信号的分类结果及针对实际模型井信号的分类结果，其正确率可达９０％以上．     

时间延迟神经网络地震油气预测方法

本文绘出基于时间延迟神经网络模型的地震油气预测方法及其初步应用结果，不同于通常的孤立模式识别方法．在特征提取阶段，不仅提取地震道中相应目的层单时窗的特征，同时也提取时窗滑动时的特征，这些多时窗的特征信息反映出地层层序的变化．时间延迟神经网络模型通过井旁道特征串的训练，用于表达特征信息与地层含油气情况的复杂关系和特征信息的变化与地层油气聚集的联系．初步应用表明，这种基于时间延迟网络模型的油气预测方法的结果要好于BP网络方法的结果．     

时间延迟神经网络地震油气预测方法

本文绘出基于时间延迟神经网络模型的地震油气预测方法及其初步应用结果,不同于通常的孤立模式识别方法．在特征提取阶段,不仅提取地震道中相应目的层单时窗的特征,同时也提取时窗滑动时的特征,这些多时窗的特征信息反映出地层层序的变化．时间延迟神经网络模型通过井旁道特征串的训练,用于表达特征信息与地层含油气情况的复杂关系和特征信息的变化与地层油气聚集的联系．初步应用表明,这种基于时间延迟网络模型的油气预测方法的结果要好于BP网络方法的结果．     

基于人工神经网络的边坡抗震抗滑稳定性评判方法

从人工神经网络的基本原理出发，建立了边坡抗震抗滑稳定性评判的人工神经网络模型。选择四川和云南地区的70个边坡实例作为学习样本,对BP算法进行了学习和检验。实例计算表明,BP网络性能良好，所建立的模型预测精度高，具有一定的工程实用价值。神经网络法是一种有效可行的新方法。     

INVERSION OF MAGNETOTELLURIC DATA: A NON-LINEAR LEAST-SQUARES APPROACH1

The inverse problem of magnetotellurics over a horizontally stratified earth is described, with emphasis on practical application. The inversion is divided into basically two steps. The construction of some best solution, and the analysis of that solution with regard to uncertainty and complexity. For the construction of best solutions a robust non-linear solver was developed, and for the estimation of parameter errors a modified eigenvalue-eigenvector analysis is performed to better describe non-linear effects. The choice of the number of layers is shown to be intimately connected with the structure of data errors and the misfit between model and data. An example from the Siljan impact structure in Sweden illustrates the power of the technique.     

MULTIPARAMETER GEOPHYSICAL LOGGING AT THE YAVA LEAD DEPOSIT: A STATISTICAL APPROACH1

The present study describes multiparameter geophysical logging carried out at the Yava sandstone lead deposit, Nova Scotia, Canada. Statistical analysis of the multiparameter data set shows that the spectral gamma-gamma ratio log (SGG ratio) is the most useful technique for characterizing the disseminated sulphide mineralization. Principal component analysis (PCA) indicates that the apparent chargeability (IP parameter) responds to the presence of clay minerals in the sandstone in addition to disseminated sulphides, so that the induced polarization method (IP) does not accurately delineate the disseminated galena content as was originally assumed in the preliminary log interpretation. PCA has also confirmed that the SGG ratio and density are related to lead content and that lithological variations can be delineated with natural radioactivity and resistivity. The zinc content of the deposit was poorly characterized by geophysical logs. Sphalerite occurrences seem to be localized as narrow bands (< 1 cm) which were not geophysically detectable.     

基于热异常信息与BP神经网络的中强地震预测试验

地震预测是地震科学研究的主要领域之一。震前热异常现象(地表温度异常升高)普遍存在并且与地震三要素有复杂的非线性关系。文中结合神经网络的优点,提出将热异常信息作为地震预测的信息源,通过构建神经网络,进行地震预测的思路,并进行了试验。基于8d合成的1km分辨率的MODIS数据,利用RST算法提取震前热异常信息,在分析震前热异常信息时空变化的基础上,确定出BP神经网络的结构,利用该网络对中国及周边100个5级以上震例,以及70个随机无震样本进行训练和仿真。试验结果表明,通过RST算法提取的震前热异常指数值,用于BP神经网络地震预测是可行的,其预测的试验结果刻画出了地震要素与热异常值间的非线性相关性。未来预测区域范围的选取以及神经网络中隐层神经元的数量将对地震预测效果产生较大的影响。     

A NEW APPROACH FOR DERIVING PSEUDOVELOCITY LOGS FROM RESISTIVITY LOGS1

This paper describes a method of generating pseudovelocity logs using measurements of electrical resistivity. A theoretical relation between electrical resistivity and transit time, which is applicable to a wide range of lithologies, has been developed. The application of this relation using a method which defines lithoresistivity zones as lithological intervals related to the same formation and showing small resistivity variations, has been tested in the Recôncavo sedimentary basin in Bahia, Brazil. A comparison of derived pseudovelocity logs with actual sonic logs for five wells whows the validity of the present approach.     

DEBUBBLING: A GENERALIZED LINEAR INVERSE APPROACH*

On seismograms recorded at sea bubble pulse oscillations can present a serious problem to an interpreter. We propose a new approach, based on generalized linear inverse theory, to the solution of the debubbling problem. Under the usual assumption that a seismogram can be modelled as the convolution of the earth's impulse response and a source wavelet we show that estimation of either the wavelet or the impulse response can be formulated as a generalized linear inverse problem. This parametric approach involves solution of a system of equations by minimizing the error vector (ΔX = X^obs– X^cal) in a least squares sense. One of the most significant results is that the method enables us to control the accuracy of the solution so that it is consistent with the observational errors and/or known noise levels. The complete debubbling procedure can be described in four steps: (1) apply minimum entropy deconvolution to the observed data to obtain a deconvolved spike trace, a first approximation to the earth's response function; (2) use this trace and the observed data as input for the generalized linear inverse procedure to compute an estimated basic bubble pulse wavelet; (3) use the results of steps 1 and 2 to construct the compound source signature consisting of the primary pulse plus appropriate bubble oscillations; and (4) use the compound source signature and the observed data as input for the generalized linear inverse method to determine the estimated earth impulse response—a debubbled, deconvolved seismogram. We illustrate the applicability of the new approach with a set of synthetic seismic traces and with a set of field seismograms. A disadvantage of the procedure is that it is computationally expensive. Thus it may be more appropriate to apply the technique in cases where standard analysis techniques do not give acceptable results. In such cases the inherent advantages of the method may be exploited to provide better quality seismograms.     

A STABLE AND FLEXIBLE PROCEDURE FOR THE INVERSE MODELLING OF SEISMIC FIRST ARRIVALS1

Multiple coverage reflection seismic data provide an important source of information concerning the subsurface. However, due to the stacking and migration techniques used in the processing, the first arrivals are muted and details about the upper part of the sections are generally lost. This paper describes a computerized method for the inverse modelling of laterally varying velocities and shallow depths which are not sufficiently resolved in the reflection seismic processing. The method minimizes, in a least-squares manner, the difference between the observed first arrivals, picked from the reflection traces, and a set of synthetic traveltimes, calculated by ray tracing in a cell model. An initial model, e.g. from a priori knowledge or the application of a conventional interpretation method, is refined iteratively until no further essential improvement can be achieved. Traditional first-arrival inversion methods cannot, in general, provide such flexible modelling. The technique is successfully tested on synthetic data as well as on first arrivals picked automatically from the records of a reflection seismic survey in North Jutland, Denmark.     

A SIMULATED ANNEALING APPROACH TO SEISMIC MODEL OPTIMIZATION WITH SPARSE PRIOR INFORMATION1

It is well known that seismic inversion based on local model optimization methods, such as iterative use of linear optimization, may fail when prior information is sparse. Where the seismic events corresponding to reflectors of interest remain to be identified, a global optimization technique is required. We investigate the use of a global, stochastic optimization method, that of simulated annealing, to solve the seismic trace inversion problem, in which the two-way traveltimes and reflection coefficients are to be determined. The simulated annealing method is based on an analogy between the model-algorithm system and a statistical mechanical system. We exploit this analogy to produce improved annealing schedules. It is shown that even in cases of virtually no prior information about two-way traveltimes and reflection coefficients, the method is capable of producing reliable results.     

BED SHEAR IN EVOLVING SCOUR AT A CYLINDER:A THEORETICAL APPROACH

ＢＥＤＳＨＥＡＲＩＮＥＶＯＬＶＩＮＧＳＣＯＵＲＡＴＡＣＹＬＩＮＤＥＲ：ＡＴＨＥＯＲＥＴＩＣＡＬＡＰＰＲＯＡＣＨＳｕｂｈａｓｉｓｈＤＥＹ１ａｎｄＳｒｉｊｉｂＫ．ＫＡＲ２Ａｂｓｔｒａｃｔ：Ｔｈｅｔｅｍｐｏｒａｌｖａｒｉａｔｉｏｎｏｆｓｈｅａｒｓｔｒｅｓｓ...     

加卸载响应比──一种新的地震预报方法

引入一个能够定量反映非线性系统不稳定程度的新参数──加卸载响应比Ｙ,这一参数可以用于地震及其它地质灾害的预测．对里氏震级４—８级地震进行后验性震例检验的结果表明,８０％以上的震例,在地震前Ｙ值均显著大于１．这一方法已预测出几次发生在中国大陆的中强地震及１９９４年１月１７日的美国洛杉矶６．６级地震．     

加卸载响应比──一种新的地震预报方法

引入一个能够定量反映非线性系统不稳定程度的新参数──加卸载响应比Ｙ，这一参数可以用于地震及其它地质灾害的预测．对里氏震级４-８级地震进行后验性震例检验的结果表明，８０％以上的震例，在地震前Ｙ值均显著大于１．这一方法已预测出几次发生在中国大陆的中强地震及１９９４年１月１７日的美国洛杉矶６．６级地震．