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1.
Seismic facies analysis is a well‐established technique in the workflow followed by seismic interpreters. Typically, huge volumes of seismic data are scanned to derive maps of interesting features and find particular patterns, correlating them with the subsurface lithology and the lateral changes in the reservoir. In this paper, we show how seismic facies analysis can be accomplished in an effective and complementary way to the usual one. Our idea is to translate the seismic data in the musical domain through a process called sonification, mainly based on a very accurate time–frequency analysis of the original seismic signals. From these sonified seismic data, we extract several original musical attributes for seismic facies analysis, and we show that they can capture and explain underlying stratigraphic and structural features. Moreover, we introduce a complete workflow for seismic facies analysis starting exclusively from musical attributes, based on state‐of‐the‐art machine learning computational techniques applied to the classification of the aforementioned musical attributes. We apply this workflow to two case studies: a sub‐salt two‐dimensional seismic section and a three‐dimensional seismic cube. Seismic facies analysis through musical attributes proves to be very useful in enhancing the interpretation of complicated structural features and in anticipating the presence of hydrocarbon‐bearing layers.  相似文献   

2.
This paper presents some results from an investigation into the utility of pattern recognition methods in seismic interpretation. The seismic instantaneous attributes of amplitude, phase and frequency provide a way of quantifying the character of a simple reflection. Measures of character can be developed from cross-plots and cluster analysis of these attributes. It is demonstrated that such seismic character can produce better-defined maps than a single attribute. These procedures can be extended to attributes derived from seismic trace segments, such as trace energy and centre frequency, and to multitrace attributes, but more effort is then needed to analyse the attributes and search out useful ones. An introduction is given to projection pursuit which has proved a useful exploratory tool for the anlysis of attribute relationships. It is important to stress that pattern recognition techniques simply help bring relationships and patterns in the data to the attention of the interpreter and the most persistent problem in applying these techniques is the evaluation of potentially interesting patterns. The decision on what use can be made of them is highly interpretive and their calibration is difficult. Well control is vital but it normally allows only very limited supervision of a seismic classifier. An example is presented to illustrate these problems.  相似文献   

3.
通过对多种连续小波基的平稳序列时频分析,提出经验模态的非平稳序列的时频分析方法,并在地震资料处理解释应用中作探索性试验.试验结果表明:对地震记录道长为5 s和2 ms采样资料,经验模态分解后可获得6-7个固有模态函数单分量,分解的第一个分量C1(t)具有较宽的频率成分,可作为地震属性的主分量.  相似文献   

4.
Fault and fracture interpretation is a fundamental but essential tool for subsurface structure mapping and modelling from 3D seismic data. The existing methods for semi-automatic/automatic fault picking are primarily based on seismic discontinuity analysis that evaluates the lateral changes in seismic waveform and/or amplitude, which is limited by its low resolution on subtle faults and fractures without apparent vertical displacements in seismic images. This study presents an innovative workflow for computer-aided fault/fracture interpretation based on seismic geometry analysis. First, the seismic curvature and flexure attributes are estimated for highlighting both the major faults and the subtle fractures in a seismic volume. Then, fault probability is estimated from the curvature and flexure volumes for differentiation between the potential faults and non-faulting features in the geometric attributes. Finally, the seeded fault picking is implemented for interpreting the target faults and fractures guided by the knowledge of interpreters to avoid misinterpretation and artefacts in the presence of faulting complexities as well as coherent seismic noises. Applications to two 3D seismic volumes from the Netherlands North Sea and the offshore New Zealand demonstrate the added values of the proposed method in imaging and picking the subtle faults and fractures that are often overlooked in the conventional seismic discontinuity analysis and the following fault-interpretation procedures.  相似文献   

5.
介绍了人工智能领域最新的基于结构风险最小化原理的数据挖掘算法——支持向量机算法。根据支持向量机线性分类和可以具有不同核函数的非线性分类两种算法,建立了地震序列分类模型。通过试算和分析比较得到了地震序列最佳分类模型,最佳模型的分类结果与实际地震序列分类基本一致。综合分析认为支持向量机算法无论在学习或者预测精度方面都具有很大的优越性,其获得的地震序列分类知识库可以较为准确地实现地震序列类型的分类,因此基于支持向量机理论建立的地震序列分类模型应该是可行的。  相似文献   

6.
时移地震非线性反演压力与饱和度变化研究   总被引:2,自引:4,他引:2       下载免费PDF全文
在现有研究基础上提出基于岩石物理模型和混合优化算法的时移地震反演压力、饱和度变化方法.介绍了混合优化算法原理和适用于疏松砂岩的岩石物理模型,建立了非线性反演油藏参数变化的流程.将本方法用于某油田实际数据标定的疏松砂岩岩石物理模型,分析三组地震属性组合与油藏参数的敏感性并进行油藏参数非线性反演,结果表明敏感性不同的三组地震属性组合均能得到正确结果,表明了方法的稳定性与有效性.油藏参数反演结果整体误差小,证明非线性反演方法不受油藏参数变化范围的影响,优于线性化反演方法.  相似文献   

7.
A simple method to contour local inhomogeneities using seismic data is proposed. It formalizes an approximate inversion method which is based on the interpretation of local inhomogeneities as making the differences between an actual seismic data set and a previous reference model. It uses the optimal statistical criteria of parameter estimation and recognition and the ray representation of the waves spreading. Any combination of direct, reflected and/or other types of waves may be used as the database. Inhomogeneities, having a size two times above the wavelength of the seismic waves, can be resolved. Laboratory experiments, using ultrasonic waves and analysis of data from field experiments, confirmed the theoretical results. The method can be used to search for ore bodies, kimberlite cubes, oiltraps, etc.  相似文献   

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10.
基于线性预测倒谱系数的地震相分析   总被引:1,自引:0,他引:1       下载免费PDF全文
解滔  郑晓东  张&# 《地球物理学报》2016,59(11):4266-4277
本文借鉴语音识别技术中的线性预测倒谱系数(LPCC系数)特征参数提取方法对地震数据进行分解,这种方法的优点是:可以获得将子波和反射系数信息分离的地震语音特征参数,对地质现象边界具有较好的描述能力,使我们可以从不同维度更细致地观察隐藏在地震数据中的地质特征.理论模型分析表明,基于LPCC系数的地震分析具有较高的地震相划分能力.实际地震资料应用表明,LPCC系数对储层特征的描述比常规三瞬属性更为细致,不同阶次LPCC系数在描述储层不同特征时也保持了内在的联系.采用K均值聚类方法对提取的12阶和24阶LPCC系数进行聚类分析,聚类结果与目的层段古地形较为吻合,较好地反映了研究区的断裂、礁滩相带、深水扇和储层的分布特征,说明在地震相分析中采用LPCC系数作为特征参数是可行和有效的.  相似文献   

11.
遥感影像识别方法是破坏性地震震后地质灾害快速、准确获取的重要方法之一,传统的遥感影像识别方法主要以人工目视识别方法和半自动识别方法为主,需投入大量的人力和时间。针对破坏性地震震后地质灾害解译时间长、投入人力多等问题,以2017年8月8日四川九寨沟7.0级地震震后高分辨率无人机遥感影像为研究样本,提出基于深度学习网络的地震地质灾害识别方法。首先结合震后遥感影像解译资料和现场调查资料,提取九寨沟地震地质灾害无人机遥感影像特征,并构建研究区地震地质灾害解译指标和分类数据集;然后采用DeepLabv3+网络结构及softmax损失函数,建立基于深度学习网络的地震地质灾害遥感影像图像语义分割模型方法;最后采用半监督学习方法进行结果验证。研究结果表明,基于深度学习网络的地震地质灾害识别方法可有效识别九寨沟地震地质灾害分布信息,整体分类识别准确率为94.22%,F1分数值为0.77,结果具有较好的一致性和准确性,可提升地震现场灾情获取和重点地震隐患识别等工作效率及服务能力。  相似文献   

12.
Seismic detection of faults, dykes, potholes and iron-rich ultramafic pegmatitic bodies is of great importance to the platinum mining industry, as these structures affect safety and efficiency. The application of conventional seismic attributes (such as instantaneous amplitude, phase and frequency) in the hard-rock environment is more challenging than in soft-rock settings because the geology is often complex, reflections disrupted and the seismic energy strongly scattered. We have developed new seismic attributes that sharpen seismic reflections, enabling additional structural information to be extracted from hard-rock seismic data. The symmetry attribute is based on the invariance of an object with respect to transformations such as rotation and reflection; it is independent of the trace reflection amplitude, and hence a better indicator of the lateral continuity of thin and weak reflections. The reflection-continuity detector attribute is based on the Hilbert transform; it enhances the visibility of the peaks and troughs of the seismic traces, and hence the continuity of weak reflections. We demonstrate the effectiveness of these new seismic attributes by applying them to a legacy 3D seismic data set from the Bushveld Complex in South Africa. These seismic attributes show good detection of deep-seated thin (∼1.5 m thick) platinum ore bodies and their associated complex geological structures (faults, dykes, potholes and iron-rich ultramafic pegmatites). They provide a fast, cost-effective and efficient interpretation tool that, when coupled with horizon-based seismic attributes, can reveal structures not seen in conventional interpretations.  相似文献   

13.
频谱成像技术是近年来发展起来的一项基于频率谱分解的储层特色解释技术,是地震属性分析中重要组成部分.频谱成像技术具有在空间横向上分辨率高的特点,是一种利用三维地震资料的多尺度信息对储层进行高分辨率成像、检测储层时间厚度变化的工具.地震数据振幅谱可以识别地层的时间厚度变化,相位谱可以检测地质体横向不连续性,在确定油藏边界、计算地层厚度方面比传统地震属性研究方法具有更大的优势.频谱成像技术的核心模块是信号的时频分析,本文回顾了频谱成像技术的基本概念和目前在频谱成像中广泛应用的时频分析方法,简单介绍了几种新的时频分析方法:广义S变换和改进的匹配追踪算法.  相似文献   

14.
Segmentation of geologic features plays a significant role in seismic interpretation. Based on the segmentation results, interpreters can readily recognize the shape and distribution of geologic features in three-dimensional space and conduct further quantitative analysis. Usually, there are mainly two steps for the segmentation of geologic features: the first step is to extract seismic attributes that can highlight the occurrence of geologic features, and the second step is to apply the segmentation algorithm on the seismic attribute volumes. However, the occurrence of geologic features is not always corresponding to the anomaly value on the seismic attribute volumes and vice versa because of several factors, such as noise in the seismic data, the limited resolution of seismic images and the limited effectiveness of the seismic attribute. Therefore, the segmentation results, which are generated solely based on seismic attributes, are not sufficient to give an accurate depiction of geologic features. Aiming at this problem, we introduce the connectivity constraint into the process of segmentation based the assumption that for one single geologic feature all of its components should be connected to each other. Benefiting from this global constraint, the segmentation results can precisely exclude the interference by false negatives on seismic attribute volumes. However, directly introducing the connectivity constraint into segmentation would face the risk that the segmentation results would deteriorate significantly because of false positives with relatively large area when the connectivity constraints are enforced. Therefore, based on the seismic attribute that highlights the boundary of geologic feature, we further propose a post-processing technique, called pruning, to refine the segmentation results. By taking the segmentation of the channel as an example, we demonstrate that the proposed method is able to preserve the connectivity in the process of segmentation and generate better segmentation results on the field data.  相似文献   

15.
提出一种自适应协方差的时频域极化滤波方法。该方法在广义S变换时频方法的基础上,构造时频域自适应协方差矩阵,通过特征分析计算时频域瞬时极化参数,设计极化滤波器,实现多分量地震极化分析和滤波。其优势在于协方差矩阵的分析时窗的长度由多分量地震数据的瞬时频率确定,可以自适应于有效信号的周期,在每个时频点计算极化参数不需要进行插值处理;结合时间频率信息,解决在时间域或频率域波形或频率重叠的信号具有明显的直观性。模型数据及实际三分量台站地震数据处理结果表明,该极化滤波方法在台站地震资料分析和处理方面具有很好的直观性和较高的分辨率。  相似文献   

16.
Hydrocarbon prediction from seismic amplitude and amplitude‐versus‐offset is a daunting task. Amplitude interpretation is ambiguous due to the effects of lithology and pore fluid. In this paper, we propose a new attribute “J” based on a Gassmann–Biot fluid substitution to reduce ambiguity. Constrained by seismic and rock physics, the J attribute has good ability to detect hydrocarbons from seismic data. There are currently many attributes for hydrocarbon prediction. Among the existing attributes, far‐minus‐near times far and fluid factor are commonly used. In this paper, the effectiveness of these two existing attributes was compared with the new attribute. Numerical modelling was used to test the new attribute “J” and to compare “J” with the two existing attributes. The results showed that the J attribute can predict the existence of hydrocarbon in different porosity scenarios with less ambiguity than the other two attributes. Tests conducted with real seismic data demonstrated the effectiveness of the J attribute. The J attribute has performed well in scenarios in which the other two attributes gave inaccurate predictions. The proposed attribute “J” is fast and simple, and it could be used as a first step in hydrocarbon analysis for exploration.  相似文献   

17.
Most positive/negative curvature and flexure are among the most useful seismic attributes for detecting faults and fractures in the subsurface based on the geometry of seismic reflections. When applied to fracture characterization and modelling of a fractured reservoir, their magnitude and azimuth help quantify both the intensity and orientation of fracturing, respectively. However, previous efforts focus on estimating only the magnitude of both attributes, whereas their associated azimuth is ignored in three‐dimensional (3D) seismic interpretation. This study presents an efficient algorithm for simultaneously evaluating both the magnitude and azimuth of most positive/negative curvature and flexure from 3D seismic data. The approach implemented in this study is analytically more accurate and computationally more efficient compared with the existing approach. The added value of extracting most positive/negative curvature and flexure is demonstrated through the application to a fractured reservoir at Teapot Dome (Wyoming). First, the newly extracted attributes make computer‐aided fault/fracture decomposition possible. This allows interpreters to focus on one particular component for fracture characterization at a time, so that a composite fractured reservoir could be partitioned into different components for detailed analysis. Second, curvature/flexure azimuth allows interpreters to plot fracture histogram and/or rose diagram in an automatic and quantitative manner. Compared with the conventional plotting rose diagram based on manual measurements, automatic plotting is more efficient and offers unbiased insights into fracture systems by illuminating the most likely orientations of natural fractures in fractured reservoirs.  相似文献   

18.
多属性融合技术在苏14井区的应用   总被引:2,自引:1,他引:1  
In this study area the geological conditions are complicated and the effective sandstone is very heterogeneous. The sandstones are thin and lateral and vertical variations are large. We introduce multi-attribute fusion technology based on pre-stack seismic data, pre-stack P- and S-wave inversion results, and post-stack attributes. This method not only can keep the fluid information contained in pre-stack seismic data but also make use of the high SNR characteristics of post-stack data. First, we use a one-step recursive method to get the optimal attribute combination from a number of attributes. Second, we use a probabilistic neural network method to train the nonlinear relationship between log curves and seismic attributes and then use the trained samples to find the natural gamma ray distribution in the Su-14 well block and improve the resolution of seismic data. Finally, we predict the effective reservoir distribution in the Su-14 well block.  相似文献   

19.
The seismic performance of existing structures can be assessed based on nonlinear static procedures, such as the Capacity Spectrum Method. This method essentially approximates peak responses of an inelastic single‐degree‐of‐freedom (SDOF) system using peak responses of an equivalent linear SDOF model. In this study, the equivalent linear models of inelastic SDOF systems are developed based on the constant strength approach, which does not require iteration for assessing the seismic performance of existing structures. To investigate the effects of earthquake type and seismic region on the equivalent linear models, four ground‐motion data sets—Japanese crustal/interface/inslab records and California crustal records—are compiled and used for nonlinear dynamic analysis. The analysis results indicate that: (1) the optimal equivalent linear model parameters (i.e. equivalent vibration period ratio and damping ratio) decrease with the natural vibration period, whereas they increase with the strength reduction factor; (2) the impacts of earthquake type and seismic region on the equivalent linear model parameters are not significant except for short vibration periods; and (3) the degradation and pinching effects affect the equivalent linear model parameters. We develop prediction equations for the optimal equivalent linear model parameters based on nonlinear least‐squares fitting, which improve and extend the current nonlinear static procedure for existing structures with degradation and pinching behavior. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

20.
The accurate interpretation and analysis of seismic data heavily depends on the robustness of the algorithms used. We focus on the robust detection of salt domes from seismic surveys. We discuss a novel feature-ranking classification model for saltdome detection for seismic images using an optimal set of texture attributes. The proposed algorithm overcomes the limitations of existing texture attribute-based techniques, which heavily depend on the relevance of the attributes to the geological nature of salt domes and the number of attributes used for accurate detection. The algorithm combines the attributes from the Gray-Level Co-occurrence Matrix (GLCM), the Gabor filters, and the eigenstructure of the covariance matrix with feature ranking using the information content. The top-ranked attributes are combined to form the optimal feature set, which ensures that the algorithm works well even in the absence of strong reflectors along the salt-dome boundaries. Contrary to existing salt-dome detection techniques, the proposed algorithm is robust and computationally efficient, and works with small-sized feature sets. I used the Netherlands F3 block to evaluate the performance of the proposed algorithm. The experimental results suggest that the proposed workflow based on information theory can detect salt domes with accuracy superior to existing salt-dome detection techniques.  相似文献   

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