Bi-LSTM-based magnetotelluric signal denoising method and system

Abstract

The invention discloses a Bi-LSTM-based magnetotelluric signal denoising method and system, the method comprises the steps: constructing a large number of noise contours conforming to magnetotelluric weak signals and containing strong interference characteristics, and adding the noise contours to obtain noisy signals; dividing the noisy signals into a corresponding training set and a test set according to a proportion, defining input and output corresponding to the network, preferably selecting related parameters of an optimal bidirectional long-short-term memory neural network by using NPSO, and then sending the training set into the neural network for training to obtain a prediction model; predicting the actually measured magnetotelluric data by using the prediction model to obtain the noise contour; and finally, subtracting the predicted noise contour from the actually measured magnetotelluric data to obtain useful magnetotelluric signals. According to the method, the noise contours can be effectively and accurately predicted, so that the noise in the noisy signals is eliminated, and more useful magnetotelluric signals are reserved.

Description

technical field [0001] The invention belongs to the technical field of magnetotelluric signal processing, in particular to a method and system for denoising magnetotelluric signals based on Bi-LSTM. Background technique [0002] With the rapid development of social economy, my country's dependence on foreign energy and metal mineral resources is increasing year by year. The shortage of mineral resources and insufficient proven reserves of energy reserves have become major bottlenecks restricting the development of the national economy. Magnetotelluric (MT) is a geophysical exploration method proposed by Soviet scholar Tikhon and French scholar Cagiard in the early 1950s to study the electrical structure of the earth by using natural alternating electromagnetic fields. MT plays an important role in geophysical exploration because of its large exploration depth, low exploration cost, convenient construction, and mature data processing and interpretation technology. Many geop...

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Problems solved by technology

Therefore, how to accurately predict the complex noise profile in the measured data, effectively complete the separation and removal of noise, and solve the problem of noise overprocessing in the prior art is an urgent need for consideration in the present invention.

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