Semi-supervised resistivity inversion method and system based on adversarial generative network and pseudo labeling

Abstract

The invention provides a semi-supervised resistivity deep learning inversion method and a semi-supervised resistivity deep learning inversion system based on an adversarial generative network and pseudo-annotation, which can realize a deep learning inversion network under the condition that part of apparent resistivity data lacks a corresponding geological model; vertical features of the electrical method data are extracted, a resistivity model is finally obtained by extracting a feature map, and the mapping relation between the apparent resistivity data and the underground resistivity geologic model is completed; meanwhile, a discriminator is added into the network structure, pseudo labeling is introduced into apparent resistivity data without corresponding geological models, the data size of labeled data is expanded, and a semi-supervised learning strategy is achieved. Through the semi-supervised deep learning electrical method data inversion network, the deep learning network inversion effect is improved when the label data is less.

Description

technical field [0001] The disclosure belongs to the technical field of geophysical exploration, and relates to a semi-supervised resistivity inversion method and system based on confrontation generation network and pseudo-labeling. Background technique [0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art. [0003] The resistivity method is a common geophysical prospecting method. It is widely used in exploring coal mines and groundwater, solving related geological problems, etc., and has broad application prospects. The main principle of the resistivity method is based on the electrical difference between the rocks, two power supply electrodes A, B and two measurement electrodes M, N are driven into the ground, power is supplied to the ground through the power supply electrodes and a stable current field is established underground , when the resistivity value of the unde...

AI Technical Summary

Problems solved by technology

For electrical data, due to the difficulty of obtaining information on underground media, it is impossible to obtain the corresponding labels of all electrical data, which cannot meet the conditions of supervised deep learning

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