A method,
system and device for monitoring downhole flow and
moisture content specifically comprises the steps that S1, DAS signals are collected, and the obtained DAS signals are preprocessed; s2,
signal features in the DAS are extracted, and
time domain features,
frequency domain features, time-
frequency domain features and
time sequence features in the DAS are extracted; s3, the DAS
signal features extracted in the S2 are fused, and comprehensive feature representation is generated; and S4, identifying the DAS
signal features, training an AI model to obtain a flow
water content identification model, and identifying the comprehensive feature representation through the flow
water content identification model to obtain flow and
water content identification. The method has the advantages that four DAS signal
feature extraction methods are provided, and time-frequency
feature extraction, frequency-frequency
feature extraction, time-frequency feature extraction and
time sequence feature extraction are achieved respectively; designing a
feature fusion algorithm, and realizing feature-based event discrimination capability enhancement; a
deep learning algorithm implementation method is provided, and a high-precision
feature recognition technology is improved.