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地质导向技术是在煤层气水平井、多分支水平井钻井中提高煤层钻遇率,进而提升煤层气单井产量的有效技术手段。针对国内煤层气水平井钻井中地层岩性随钻判识技术的不足,提出一种利用多源信息融合技术实现煤层随钻判识的方法。基于人工神经网络建立了随钻判识模型,通过对多种能够表征地层岩性参数的融合分析,综合处理,达到了快速准确地自动判识煤层的目的。实践表明,在现有技术条件下,将多源信息融合技术应用于煤层随钻判识是可行的,能够为煤层气水平井地质导向钻井的有效实施提供有效的技术支持。
Geosteering technology is an effective technical means to improve the drilling rate of coal seam in coalbed methane horizontal wells and multi-lateral horizontal well drilling so as to enhance single well production of coalbed methane. In view of the lack of the stratigraphic lithology in drilling horizontal well of domestic CBM wells, a method of judging coal seam while drilling using multi-source information fusion technology is proposed. The model of LWD is established based on the artificial neural network. Through the fusion analysis and comprehensive processing of various lithologic parameters that can characterize the stratum, the purpose of quickly and accurately identifying the coal seam is achieved. The practice shows that it is feasible to apply multi-source information fusion technique to coal seam while drilling, and to provide effective technical support for the effective implementation of the geological-guided drilling of horizontal wells in coalbed methane under the existing technical conditions.