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在多尺度小波分解理论的基础上，提出利用速度剖面和测井曲线的多尺度小波分解结果，在测井约束下分别确定砂体的位置、几何形态，计算薄砂体的视累计厚度和含油气砂体的视累计厚度；并将各尺度下计算的视累计厚度作为人工神经网络的输入，反演得到最终精确的薄砂体的累计厚度和含油气砂体的累计厚度。经三维地震资料连片处理证实：该方法稳定可靠，确定的砂体位置准确，反演结果具有较高的精度
Based on the theory of multi-scale wavelet decomposition, the multi-scale wavelet decomposition results of velocity profile and well logging curve are proposed to determine the position and geometry of sand body under logging constraints and to calculate the apparent cumulative thickness and oil content of the thin sand body And the apparent cumulative thickness of the gas sand body is calculated. The apparent cumulative thickness calculated at each scale is used as the input of the artificial neural network to obtain the final and accurate cumulative thickness of the thin sand body and the cumulative thickness of the oil-gas sand body. It is confirmed by the contiguous processing of the 3D seismic data that the method is stable and reliable, the position of the sand body is determined accurately, the inversion result has high precision