| Summary: | After long-term water flooding development in old oilfields, oil layers are generally flooded. Accurate and rapid recognize the water flooding layer is the key to later infill well layout and development plan adjustment. In this paper, taking Xingbei area of Daqing Oilfield as an example, on the basis of clarifying the characteristics of the water-flooded layer curve, through logging curve optimization, data preprocessing and algorithm model optimization processes, a rapid identification model of water-flooded layer suitable for this block is established. The results show that the HAC, CAL, RLLS and RMG curves with hidden duplicate information can be removed through the correlation screening of logging curves and the importance score of the tree model, which can reduce the amount of data calculation. When the four algorithms are used to identify the flooding level of each layer, the recognition rate of the XGboost algorithm can reach up to 95.45%; the reliability of this result has been confirmed in the model verification process (87.89%), which further shows that the model can be used to identify Xingbei area flooded.
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