166results about How to "Solve vanishing gradient" patented technology

The invention discloses a deep learning-based method for predicting a lithologic sequence model through using seismic data. The method includes the following steps that: 1) the lithologic data of a target stratum section of a well in a work area and near-well trace seismic data are measured so as to be adopted as training data; 2) the near-well trace seismic data are normalized, so as to be converted to a range of -1 to 1; 3) a stacked recurrent neural network and a sequence-to-sequence recurrent neural network model are adopted to respectively train the processed near-well trace seismic dataand the well lithologic data, with the near-well trace seismic data adopted as observation data, and the well lithologic data adopted as target data, iterative computation is performed, so that a learning model reaches convergence; and 4) actual seismic data are inputted to the learning model which is obtained after calculation in the step 3), so that a predicted lithologic sequence is obtained. With the deep learning-based method for predicting the lithologic sequence model through using the seismic data of the invention adopted, a lithologic data body capable of effectively reflecting reservoir distribution can be generated under the control of a seismic data sequence, and an inter-well reservoir prediction problem can be solved, and a basis can be provided for exploration and development.