淡水侵入油藏饱和度解释模型和水淹级别的识别

Saturation Interpretation Model of Freshwater Invaded Reservoir and Identification of Waterflooded Grades.

利用双孔隙水模型计算淡水侵入油藏的含水饱和度 ,该方法不必已知束缚水的电阻率。用迭代法计算饱和度模型的解释参数。利用神经网络 (BP算法 )识别水淹层水淹级别 ,选择深浅电阻率幅度差、深浅电阻率比值、自然电位异常幅度、孔隙度和岩性系数等 5个量作为输入特征 ,处理了 2个构造带 15口井。经试油验证效果良好。

Determining water saturation of freshwater invaded zones from dual porous water model was detailed without bound water resistivity. The parameters of the model were calculated with iterative algorithm. The neural network technique was used to classify the waterflooded degrees. The input of the network may be the routine logging curves, such as deep shallow resistivity amplitude difference, deep shallow resistivity ratio, SP anomaly, porosity and lithology coefficient, etc.. Log data from 15 wells in Qinling area, Tuha Basin, were processed with ANN (artificial neural network) technique, the result of which agrees well with the oil production test.