Adaptive wave impedance inversion method and system based on deep convolutional neural network

The invention provides an adaptive wave impedance inversion method and system based on a deep convolutional neural network, and belongs to the field of seismic inversion interpretation. The method comprises the following steps: (1) generating a training set; (2) constructing a one-dimensional deep convolutional neural network wave impedance inversion model; (3) training the neural network wave impedance inversion model by using the training set to obtain a trained wave impedance inversion model; and (4) inputting seismic data to be inverted and low-frequency constraint data into the trained wave impedance inversion model, and outputting an inversion result. According to the method, a semi-supervised learning mode is adopted, an objective function composed of a seismic waveform loss item and a low-frequency constraint loss item is established, a deep convolutional neural network model which comprises a plurality of convolutional layers and a full-connection layer and is suitable for wave impedance inversion is