基于地震波波形相似的薄互层识别方法

Thin interbed identification method based on seismic waveform similarity

随着油田勘探开发程度的深入,目标储层大都具有薄、小、深、碎的特点,高精度薄互层识别成为储层预测的热点和重点。目前常用的时频分析方法和谱分解技术受限于地震数据,无法满足薄互层精确刻画的要求;高分辨率反演方法也因地球物理反演的非线性特征导致结果存在多解性。为此,提出基于地震波波形相似的薄互层识别方法:首先采用波形库思想,构建井旁道—测井敏感曲线波形库;之后利用改进Manhattan距离联合线性相关系数法计算波形相似度,进行波形匹配;最后将波形相似度作为唯一驱动,建立地震数据与高分辨率测井数据间的数学联系,最终得到高分辨率处理剖面。该方法充分利用了地震、测井数据分别具有的横向和纵向高分辨率优势,能够有效识别薄互层目标,极大地降低了反演结果的多解性。模型试算验证了方法的可行性;实际资料处理结果表明该方法显著提高了纵向分辨率,对调谐尺度内的薄互层识别提供了技术支撑。

As degrees of oil field exploration and development deepen,most target reservoirs are found to be thin,small,deep,and fractured.High⁃precision identification of thin interbedding has become the focus of re⁃servoir prediction.At present,time⁃frequency analysis methods and spectral decomposition techniques com⁃monly used in thin interbedding identification are limited by seismic data,and the processing results fail to meet the requirements of accurate characterization of thin interbedding.Due to the nonlinear characteristics of geo⁃physical inversion,the results of high⁃resolution inversion have multiple solutions.In this paper,a thin inter⁃bedding identification method based on the similarity of seismic waves is proposed.Firstly,the idea of a wave⁃form library is used to construct the waveform library of well bypass⁃sensitive logging curves.Secondly,the im⁃proved Manhattan distance combined linear correlation coefficient method is then used to calculate the wave⁃form similarity.Finally the waveform similarity is taken as the only driver to establish the mathematical relation⁃ship between seismic data and high⁃resolution logging data,until the high⁃resolution processing profile is obtained.This method makes full use of the high transverse resolution of seismic data and the high longitudinal resolution of logging data,effectively identifies thin interbedding,and greatly reduces the multi⁃solution of inversion re⁃sults.The feasibility of this method is verified by model test.The actual data processing results show that the proposed method significantly improves the longitudinal resolution and provides technical support for the identi⁃fication of thin interbedding within a tuned scale.