首页|Mapping coal water-filled zones using multi-radiation source transient electromagnetic pseudo-seismic Born approximation imaging and apparent resistivity imaging in Gansu, China
Mapping coal water-filled zones using multi-radiation source transient electromagnetic pseudo-seismic Born approximation imaging and apparent resistivity imaging in Gansu, China
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NSTL
Elsevier
The coal water-filled zones have become a growing safety hazard, so effective detection techniques and accurate interpretation methods are of great concern. In this paper, we adopt multi-radiation source transient electromagnetic method (TEM) in the data collection, and employ joint imaging method in the data interpretation. A single-radiation source can only be coupled with the geological body from one side, making holographic photography problematic, but multi-radiation source can suppress random noise, improve the signal-to-noise ratio, and reduce the volume effect. Typically, the apparent resistivity method can reflect the electrical distribution characteristics, while the pseudo-seismic imaging method (PSI) can quickly locate the position and shape of the geological structure, so the two imaging methods can be combined. Therefore, firstly using multi-window time-sweep wavefield inverse transformation technology converts the TEM data into the multi-resolution pseudo-wave, then utilizing the joint interpretation method obtains the underground electrical distribution characteristics, the location of the water-filled zones and stratum's continuous undulations. In this paper, through the calculation of the theoretical model, the results verify the effectiveness of the proposed method. Through processing the field data in Gansu, China, the results demonstrate that the joint interpretation method can map the coal water-filled zones and reflect the geological structures.
Transient electromagneticCoal water-filled zonespseudo-seismic Born approximation imagingApparent resistivity imagingFIELDTRANSFORMATIONEQUIVALENTALGORITHM
NSTL
Elsevier
