Water inrush during tunnel excavation severally threatens the mining safety as blind water-bearing structures may develop in front of the working face. The transient electromagnetic method (TEM) has been widely applied in the advanced detection of tunnel water-bearing structures. However, the metal interference of both supports and tools in the tunnel has become a bottleneck that reduces the forecast accuracy of this method. In this paper, we analyse the effect of metal interference on TEM data and propose a novel set of an observation and correction method under metal interference based on the ratio of anomalous and background apparent resistivity. Flume model experiments both with and without metal interference are carried out, showing that this interference can affect TEM measurements significantly and result in false anomalies, and that our proposed method can remove this ambient noise caused by metal interference appropriately. The practical application further proves that this method can effectively reduce low-resistivity interference introduced by the support and other metal tools inside the tunnel. By applying this correction method, the location of water-rich anomalies can be detected more precisely during the excavation process of the same tunnel, which is of high application value of reducing exploration difficulty and tunneling risk.

Water inrush in tunneling poses serious harm to safe construction, causing economic losses and casualties. The prediction of water hazards before tunnel excavations becomes an urgent task for governments or enterprises to ensure security. The three-dimensional (3D) direct current (DC) resistivity method is widely used in the forward-probing of tunnels because of its low cost and highly sensitive response to water-bearing structures. However, the different sizes of the tunnel will distort the distribution of the potential field, which causes an inaccurate prediction of water-bearing structures in front of the tunnels. Some studies have pointed out that the tunnel effect must be considered in the quantitative interpretation of the data. However, there is rarely a predicted model considering the tunnel effect to be reported in geophysical literature. We developed a predicted model algorithm by considering the tunnel effect for forward-probing in tunnels. The algorithm is proven to be feasible using a slab analytic model. By simulating a large number of models with different tunnel sizes, we propose an equation, which considers the tunnel effect and can predict the water-bearing structures ahead of the tunnel face. The Monte Carlo method is used to evaluate the quality of the predicted model by simulating and comparing 10,000 random models. The results show that the proposed method is accurate to forecast the water-rich structures with small errors.

Small-loop transient electromagnetic (TEM) devices, several meters in size, are increasingly applied to near-surface geophysical exploration in space-limited environments. But the transmitter (TX) coil significantly affects the early time data acquisition of the receiver (RX) coil during current turn-off, resulting in the loss of shallow signals and creating a significant blind zone problem. We report a double-coil decoupling TEM (DCDTEM) device to solve this problem. The novel DCDTEM device ensures a weak primary magnetic flux region between the two coplanar TX coils with the same current direction and different radii. Simulation results indicate that the transmitting field of the DCDTEM device is more focused than the traditional central loop device, ensuring a stronger coupling with the target. The 3D TEM forward-modeling results show that the DCDTEM device has the highest detection sensitivity, together with a relatively high lateral resolution compared with other small-loop TEM devices. We further carry out several physical experiments to test the response characteristics of the DCDTEM device with reference to the offset and the ratio of turns between the TX and RX coils. The experimental results ensure that the position of the zero magnetic flux point can be accurately calibrated and mitigate interference from TX coils. Our DCDTEM device is also applied in a field test on water pipe detection, demonstrating its practicality in near-surface detection.

We have proposed a goal-oriented iteration algorithm with adaptive error estimation for the 3-D modeling of the time-domain marine controlled-source electromagnetic (CSEM) method. The algorithm is based on finite-element time-domain (FETD) formulations, and it updates both the time step and the mesh size in a staggered manner. With this scheme, the computational error is well suppressed, and the efficiency of the FETD simulation is guaranteed by adaptive time-stepping within each iteration. The verification results of an electric dipole radiation model and a synthetic 1-D marine CSEM model have shown that the proposed algorithm achieves a fine balance between computational accuracy and efficiency. Through numerical examples incorporated with stratum anisotropy and seafloor topography, we further conclude that both background anisotropy and topography impede the identification of submarine high-resistivity bodies with the electric field response. Contrarily, the time derivative of the magnetic field is sensitive to high-resistivity reservoirs over an extensive period of time in both anisotropic and topographic models. Based on this, we suggest that the magnetic field should be collected along with the electric field over the whole target area to reveal the anisotropic structure of submarine sediments and the existence of oil and gas reservoirs.

The resistivity method has been widely used to predict the water-bearing structure of tunnels. The traditional resistivity uses the point electrode (PE) source in the tunnel to excite the electric field. Because the tunnel face is inaccessible, its exploration depth is limited and small. In order to overcome this problem, the horizontal pilot hole is used as the long electrode (LE) source in the tunnel. We use the finite element method (FEM) to establish a three-dimensional modeling algorithm for tunnel detection using a long electrode source. The accuracy of the algorithm is verified by using the long electrode source model. By a lot of numerical simulations, a prediction model of a long electrode source for tunnel detection is firstly proposed. The predicted results show that it has good applicability in detecting long-distance anomaly. The comparison of the long electrode source and point electrode source models shows that the detection depth of the long electrode prediction model is farther than that of the point electrode source. This long electrode source method can improve the construction efficiency and effectively prevent water inrush in the tunnel.