谱分解技术在断层描述及储层预测中的应用

Application of Spectrum Decomposition to Faults Recognition and Reservoir Prediction

黄龙泽 周晶 王岭

HUANG Longze ZHOU Jing WANG Ling

中国石油化工股份有限公司上海海洋油气分公司研究院, 上海 200120

Institute of SINOPEC Shanghai Offshore Oil and Gas Company, Shanghai 200120, China

谱分解技术是通过离散傅里叶变换或最大熵变换等数学方法,将地震资料从时间域变换到频率域,利用振幅谱及相位谱识别薄储层和不连续地质体边界的一项新技术。谱分解主要形成两种调谐体,一种是振幅调谐体,通常用于描述薄层的厚度变化,另一种是相位调谐体,通常可以指示小断层。谱分解已被证明是一种薄储层估算和识别小断层的有效方法。此次谱分解应用区为W断背斜区,该区断裂系统复杂,尤其是小断层比较发育。已钻井揭示油气层很薄,不超过10 m。利用谱分解技术处理后,小断层在平面上表现更加清晰,砂岩储层段在平面上的展布得到了更为精细的刻画描述,为进一步勘探提供了有力依据。

Spectral decomposition is a new technique,by which the seismic data is transformed into frequency domain through Discrete Fourier Transform (DFT) or Maximum Entropy Method transform (MEM),the amplitude spectra and phase spectra is used to identify thin reservoir and discontinuous geological boundary.By spectral decomposition,two kinds of spectrum can be developed,one is transformed amplitude spectrum,and the other is phase spectrum.The transformed amplitude spectrum is used to delineate change of bed thickness,while the phase spectrum is used to indicate lateral geologic discontinuities.This technique has proven to be an effective method for thickness estimation and fault identification.There are a lot of faults in W area,and the thickness of the hydrocarbon reservoirs is less than 10 m.By using spectral decomposition,the fault can be identified,and the lateral distribution of thin reservoirs can be described finely,which can provide a solid basis for future hydrocarbon exploration.

https://doi.org/10.3969/j.issn.1008-2336.2015.01.036