摘要
针对煤层气储层识别问题,提出了天然源超低频电磁探测技术,并阐述了探测机理。运用独立成分分离和提升小波变换相结合的方法对探测信号进行滤波与重构,压制了工频干扰。选取了沁水盆地不同储层埋深、不同工频干扰强度的3口煤层气排采井,利用重构的超低频信号对多个储层进行了有效识别,结合电磁波特性评价了储层位置的探测精度。某排采井剖面研究表明,超低频探测技术可以对储层分布和排采过程中的水文等异常信息进行提取,发现在3号和15号煤储层之间存在一个疑似充水断层,需要实际资料进一步验证。
Proposed the natural source super-low frequency （SLF）electromagnetic prospecting technology in identifying coal-bed methane（CBM） reservoirs, and illustrated the theory, the strategy and the feasibility of reservoir information extraction. Applied the integrated method of the independent component analysis （ICA） and lifting wavelet transform to filter and reconstruct the SLF curves, and the results successfully suppress the power line interference. By means of the reconstructed SLF signal, authors effectively recognize multi-reservoirs in three CBM wells with different reservoir depths and varying scales of power line interference, and meanwhile evaluate the identification accuracy with depth de- viations from 2 to 14 meters. In the profile study of one production CBM well, observe that the SLF prospecting technol- ogy contributes to deriving the CBM reservoir distribution and the hydrological information. The analysis indicates that a low resistance body is inferred as a water-filled fault,which may reduce the CBM capacity and should be verified.
出处
《煤炭学报》
EI
CAS
CSCD
北大核心
2014年第1期141-146,共6页
Journal of China Coal Society
基金
国家科技重大专项子课题"基于静态信息/排采历史耦合的煤储层分析与探测技术"资助项目(2011ZX05034-02)
关键词
超低频
电磁探测
煤层气
储层识别
独立成分分析
提升小波
super-low frequency （SLF）
electromagnetic prospecting
coal-bed methane （ CBM ）
reservoir identifica- tion
independent component analysis（ICA）
lifting wavelet transform
