Author/Authors :
Asadian، Abolfazl نويسنده Faculty of Mining, Petroleum and Geophysics, Shahrood University, Shahrood, Iran Asadian, Abolfazl , Arab-Amiri، Alireza نويسنده Faculty of Mining, Petroleum and Geophysics, Shahrood University, Shahrood, Iran Arab-Amiri, Alireza , Nejati kalateh، Ali نويسنده Faculty of Mining, Petroleum and Geophysics, Shahrood University, Shahrood, Iran Nejati kalateh, Ali , Rajabi، Davood نويسنده Faculty of Mining, Petroleum and Geophysics, Shahrood University, Shahrood, Iran Rajabi, Davood
Abstract :
The helicopter-borne electromagnetic (HEM) frequency-domain exploration method is an airborne
electromagnetic (AEM) technique that is widely used for vast and rough areas for resistivity imaging.
The vast amount of digitized data flowing from the HEM method requires an efficient and accurate
inversion algorithm. Generally, the inverse modelling of HEM data in the first step requires a precise
and efficient technique provided by a forward modelling algorithm. The exact calculation of the
sensitivity matrix or Jacobian is also of the utmost importance. As such, the main objective of this
study is to design an efficient algorithm for the forward modelling of HEM frequency-domain data for
the configuration of horizontal coplanar (HCP) coils using fast Hankel transforms (FHTs). An attempt
is also made to use an analytical approach to derive the required equations for the Jacobian matrix. To
achieve these goals, an elaborated algorithm for the simultaneous calculation of the forward
computation and sensitivity matrix is provided. Finally, using two synthetic models, the accuracy of
the calculations of the proposed algorithm is verified. A comparison indicates that the obtained results
of forward modelling are highly consistent with those reported in Simon et al. (2009) for a four-layer
model. Furthermore, the comparison of the results for the sensitivity matrix for a two-layer model with
those obtained from software is being used by the BGR Centre in Germany, showing that the proposed
algorithm enjoys a high degree of accuracy in calculating this matrix.