因此如何利用低测井成本方法识别裂缝，是能否提高碳酸盐岩油田开发能力的重要途径。
So the primary way to improve exploited potential is how to use low logging cost method to identify fractures in carbonate reservoir.
裂缝性储层流体类型识别一直是测井界亟待解决的难题。
Fluid type identification of fracture reservoir is a worldwide difficult problem.
本文基于人工神经网络理论，开展了常规测井资料识别评价裂缝的研究。
Based on artificial neural network theory, using routine logging data in fracture identification is studied.
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