煤层气地震资料高分辨率处理与含气性预测研究

发布时间：2018-04-02 07:15

本文选题：煤层气　切入点：高分辨率　出处：《中国石油大学(华东)》2015年硕士论文

【摘要】：煤层气是一种清洁能源,煤层气的勘探开发在世界范围内日益受到重视。煤层气的研究已经成为地震学中的前沿课题之一,开展对煤层气的研究对于深入了解地球介质结构,勘探开发复杂油气藏和地质灾害的预报等具有重要理论意义和现实意义。地震资料分辨率是进一步提高地震反演、地震属性分析、煤储层含气性预测精度的重要研究内容。实际上由于地层的吸收以及采集、接收等各方面因素的影响,使常规地震勘探得到的地震记录频带较窄,分辨率较低。对地震数据同时进行振幅和相位的补偿,提高地震资料的有效带宽,使地震资料在保持信噪比前提下提高分辨率。本文讨论了通过反Q滤波的方法提高地震资料的分辨率。地震道时频分解方法可以将地震道分解为各种各样不同的子波,这些子波具有不同主频、不同子波宽度、以及不同时间位置。时频分析作为分析时变非平稳信号的有力工具,成为现代信号处理研究的一个热点。地震信号属于一种非平稳信号,这种分析方法提供了时间域与频率域的联合分布信息,清楚地为我们描述了地震信号频率随时间变化的关系,本文主要通过匹配追踪以及视频谱分解的方法对地震数据进行时频分析。某地区煤层气产层单煤层薄,煤层气含量横向变化大,通过对高分辨率处理的应用研究,对地震数据同时进行振幅和相位的补偿,提高地震资料的有效带宽,使地震资料在保持信噪比前提下提高分辨率;利用追踪匹配算法的时频分解方法进行薄层分析和煤层气富集区预测研究,根据地震数据的频率域变化特征,运用神经网络综合聚类方法对煤系地层的空间分布及含气性进行描述。
[Abstract]:Coalbed methane (CBM) is a kind of clean energy, and the exploration and development of CBM have been paid more and more attention in the world. The study of CBM has become one of the frontier topics in seismology. Exploration and development of complex reservoirs and geological hazard prediction have important theoretical and practical significance. The resolution of seismic data is to further improve seismic inversion, seismic attribute analysis, In fact, due to the influence of stratigraphic absorption, acquisition, reception and other factors, the frequency band of seismic records obtained from conventional seismic exploration is relatively narrow. Low resolution. The amplitude and phase of the seismic data are compensated at the same time to increase the effective bandwidth of the seismic data. In this paper, we discuss how to improve the resolution of seismic data by inverse Q filter. The seismic trace can be decomposed into a variety of wavelet by time-frequency decomposition method. These wavelets have different main frequencies, different wavelet widths, and different time positions. Time-frequency analysis is a powerful tool for analyzing time-varying non-stationary signals. Seismic signal is a kind of non-stationary signal, which provides the joint distribution information between time domain and frequency domain. The relationship between the frequency of seismic signal and time is clearly described for us. In this paper, the time-frequency analysis of seismic data is carried out by means of matching tracing and video spectrum decomposition. The transverse variation of CBM content is large. By studying the application of high-resolution processing, the amplitude and phase of seismic data are compensated at the same time, the effective bandwidth of seismic data is increased, and the resolution of seismic data is improved under the premise of keeping signal-to-noise ratio. Thin-layer analysis and prediction of coalbed methane rich area are studied by time-frequency decomposition method of tracing matching algorithm. According to the variation characteristics of seismic data in frequency domain, The spatial distribution and gas-bearing property of coal measure strata are described by neural network comprehensive clustering method.
【学位授予单位】：中国石油大学(华东)
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：P631.44;P618.13

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