Transient electromagnetic inversion based on improved Quantum Genetic Algorithm

Zhuang, Qiong; Zhang, Huaiqing

doi:10.1109/ifeea51475.2020.00187

Cited by 1 publication

(1 citation statement)

References 4 publications

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“…There are two types of TEM inversion methods: linear inversion and nonlinear inversion methods. Nonlinear inversion methods, such as genetic algorithm [20], simulated annealing algorithm [21], particle swarm optimization [22], and others, start with a random model. The nonlinear inversion method reduces the dependence of the initial model when compared to linear inversion methods such as least square, but the model update is stochastic and requires a lot of forwarding simulation and inversion calculation.…”

Section: Introductionmentioning

confidence: 99%

Tunnel Concealed Karst Cave Joint Detection by Tunnel Seismic and Transient Electromagnetic

et al. 2022

Lithosphere

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The water-rich giant karst cave is the risk source of tunnel construction in the karst area. To reduce the risk of tunnel construction, it is necessary to accurately explore the spatial distribution range of the karst cave in the direction of advance and both sides of the tunnel. Reflection seismic and transient electromagnetic (TEM) are the primary geophysical tools for tunnel advanced prediction; they have strengths and weaknesses. The tunnel seismic can only describe the boundary interface between cave bodies and surrounding rock in the direction of advance. Although the TEM method can detect the spatial distribution range of cave bodies, the inversion results depend on the initial resistivity model. The single method is insufficient to describe the spatial distribution of cave bodies. To overcome the shortcoming of a single method, we developed tunnel seismic and TEM joint detection of karst cavern and established a complete data processing flow. The tunnel seismic migration profiles can describe the interface between the karst cave and surrounding rock in the direction of advance. We put forward a reasonable initial model: (1) the layer’s thicknesses are determined by the impedance interface from the tunnel migration data; (2) the initial resistivity values are determined from the pilot hole and prior geological data. Comparison of the inversion results of different initial models of tunnel face horizontal line data proves that the proposed initial model method can reduce multisolution, save calculation time, and improve inversion accuracy. The multidirectional TEM inversion profiles can describe the spatial distribution of the giant cave. Combined with the results of tunnel seismic and TEM, the interpretation errors can be reduced and the extension of the karst cave can be delineated. Later excavation results also verify the accuracy of the prediction results.

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Section: Introductionmentioning

confidence: 99%

Tunnel Concealed Karst Cave Joint Detection by Tunnel Seismic and Transient Electromagnetic

et al. 2022

Lithosphere

View full text Add to dashboard Cite

show abstract

Transient electromagnetic inversion based on improved Quantum Genetic Algorithm

Cited by 1 publication

References 4 publications

Tunnel Concealed Karst Cave Joint Detection by Tunnel Seismic and Transient Electromagnetic

Tunnel Concealed Karst Cave Joint Detection by Tunnel Seismic and Transient Electromagnetic

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