A gas migration law study of a large-scale 3D physical similarity simulation with an adaptive Kalman filter algorithm

Abstract

Purpose

In this study, a physical similarity simulation plays a significant role in the study of crack evolution and the gas migration mechanism. A sensor is deployed inside a comparable artificial rock formation to assure the accuracy of the experiment results. During the building of the simulated rock formation, a huge volume of acidic gas is released, causing numerous sensor measurement mistakes. Additionally, the gas concentration estimation approach is subject to uncertainty because of the complex rock formation environment. As a result, the purpose of this study is to introduce an adaptive Kalman filter approach to reduce observation noise, increase the accuracy of the gas concentration estimation model and, finally, determine the gas migration law.

Design/methodology/approach

First, based on the process of gas floatation-diffusion and seepage, the gas migration model is established according to Fick’s second law, and a simplified modeling method using diffusion flux instead of gas concentration is presented. Second, an adaptive Kalman filter algorithm is introduced to establish a gas concentration estimation model, taking into account the model uncertainty and the unknown measurement noise. Finally, according to a large-scale physical similarity simulation platform, a thorough experiment about gas migration is carried out to extract gas concentration variation data with certain ventilation techniques and to create a gas chart of the time-changing trend.

Findings

This approach is used to determine the changing process of gas distribution for a certain ventilation mode. The results match the rock fissure distribution condition derived from the microseismic monitoring data, proving the effectiveness of the approach.

Originality/value

For the first time in large-scale three-dimensional physical similarity simulations, the adaptive Kalman filter data processing method based on the inverse Wishart probability density function is used to solve the problem of an inaccurate process and measurement noise, laying the groundwork for studying the gas migration law and determining the gas migration mechanism.

Citation

Hao, Y., Li, S. and Zhang, T. (2022), "A gas migration law study of a large-scale 3D physical similarity simulation with an adaptive Kalman filter algorithm", Assembly Automation, Vol. 42 No. 1, pp. 126-133. https://doi.org/10.1108/AA-06-2021-0084