Application of surveying and mapping technology based on deep learning model in petroleum geological exploration

Abstract

Surveying and mapping technology is one of the key technologies used in petroleum geological exploration and has made significant contributions to geological exploration. However, with the development of science and technology, traditional surveying and mapping technology has low work efficiency and poor information accuracy, which limits its application. This study proposes a surveying and mapping technology based on the 1DCNN-LSTM deep learning model. Through feature selection and feature optimization, the important features extracted by 1DCNN are predicted through LSTM, and the development direction of surveying and mapping technology is optimized and predicted to promote the development of new surveying and mapping technologies. application. By using the orthogonal test to optimize the input factors, determine the relative order of the influence of the factors, and use the 1DCNN-LSTM and BP neural network to train and verify the input factors respectively. The research results show that 1DCNN-LSTM has higher prediction accuracy, and the prediction accuracy is The results show that the 1DCNN-LSTM deep learning model used in the optimization of petroleum geological exploration and mapping technology in this study has strong practical significance.