In order to solve the problem of low data quality and unsatisfactory detection effect of Wide Field Electromagnetic Method (WFEM) caused by noise, this paper proposes a WFEM denoising method and application based on improved dung beetle optimization (Improved DBO, IDBO) and Long Short Term Memory (LSTM) network. Firstly, the Spatial Pyramid Matching (SPM) chaotic mapping, variable spiral strategy, Levy flight mechanism, adaptive t-distribution variance perturbation strategy are used to improve the IDBO algorithm. Then, the mean square error is used as the fitness function of the IDBO algorithm to optimize the hyperparameters of the LSTM algorithm. Finally, the IDBO-LSTM method is applied to the WFEM data de-noising processing. The experimental results show that the search ability of IDBO is significantly better than that of other intelligent optimization algorithms, and the LSTM algorithm optimized by IDBO has a significantly higher denoising accuracy than the probabilistic neural network(PNN) and the LSTM algorithms. The data quality of the WFEM data processed by the IDBO-LSTM method is significantly improved, and the electric field curve shape is more stable. The proposed method can provide technical support for the interpretation of electromagnetic method inversion.