Zhou Nannan

Understanding of Grounded-Wire TEM Sounding with Near-Source Configuration

In order to understand the near-source TEM sounding method, the topic on the time domain electromagnetic exploration of deep targets is addressed using a grounded dipole source. At first, the development of the near source TEM is reviewed in this paper, then a new kind of technique capable of detecting geological targets located at deeper levels in the subsurface is proposed using the short-offset transient electromagnetic method (hereafter referred to as SOTEM). The detection abilities of this system, such as the feasibility of near-source detection for SOTEM, the investigation depth of SOTEM and the sensitivity of SOTEM, have been analyzed. The conclusion has been achieved that the proposed method is more applicable and convenient for exploration and could be used to obtain a greater detection depth with higher detection accuracy.

Inversion of TEM Conductive Thin Layer Based on Genetic Algorithm

Using the adaptive shrinkage genetic algorithm in the feasible region to operate the inversion of TEM (transient electromagnetic method) conductive thin layer with the apparent vertical conductance differential imaging. In contrast, this inversion method accelerates the calculation speed and improves the calculation precision. Meanwhile, we utilize the genetic algorithm to derive the conductive imaging parameter and realize the global non-linear inversion compared to traditional method in local scope.Using the adaptive shrinkage genetic algorithm in the feasible region to operate the inversion of TEM (transient electromagnetic method) conductive thin layer with the apparent vertical conductance differential imaging. In contrast, this inversion method accelerates the calculation speed and improves the calculation precision. Meanwhile, we utilize the genetic algorithm to derive the conductive imaging parameter and realize the global non-linear inversion compared to traditional method in local scope.

An Optimized Method for Transient Electromagnetic Field

During the forward transformation of wave-field, two-step optimized algorithm is used for decreasing the number of integral coefficients and sampling in dispersed digital integral, as while as ensure transient electromagnetic field’s calculation precision. This algorithm solves the ill-posed problem produced by large quantity of integral coefficients and depresses the ill character of the first calculation function. During wave-field inverse transformation, normalized algorithm is introduced to the inverse transformation by adopting the deviation theory and the Newton iterative form to make the transformed wave field stable and reliable. It is concluded that this algorithm is effective and useful.During the forward transformation of wave-field, two-step optimized algorithm is used for decreasing the number of integral coefficients and sampling in dispersed digital integral, as while as ensure transient electromagnetic field’s calculation precision. This algorithm solves the ill-posed problem produced by large quantity of integral coefficients and depresses the ill character of the first calculation function. During wave-field inverse transformation, normalized algorithm is introduced to the inverse transformation by adopting the deviation theory and the Newton iterative form to make the transformed wave field stable and reliable. It is concluded that this algorithm is effective and useful.