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Short Note: VLFPROS-A Matlab code for

processing of VLF-EM data

 ARTICLE  in  COMPUTERS & GEOSCIENCES · DECEMBER 2006

Impact Factor: 2.05 · DOI: 10.1016/j.cageo.2006.02.021

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Computers & Geosciences 32 (2006) 1806–1813

Short Note

VLFPROS—A Matlab code for processing of VLF-EM data$

N. Sundararajana,, V. Ramesh Babub, N. Shiva Prasadb, Y. Srinivasa

aCentre for Exploration Geophysics, Osmania University, Hyderabad 500 007, IndiabAtomic Minerals Directorate for Exploration and Research, Department of Atomic Energy, Hyderabad 500 016, India

Received 25 February 2006; accepted 25 February 2006

1. Introduction

The very low frequency electromagnetic (VLF-

EM) technique is well established for rapid geolo-

gical mapping and detection of buried conductive

targets. The technique makes use of signal radiation

from military navigation radio transmitters. There

are about 42 global ground military communication

transmitters1 operating in VLF frequency in the

range of 15–30 kHz. These stations, located aroundthe world, generate signals which are effectively

used for a variety of applications including naviga-

tion and communication, ground water detection or

contamination, soil engineering, cultural detection,

ionospheric, meteorological, archeological, nuclear

waste detection and VLF band transmission studies,

besides mineral exploration, mapping of fault zones,

etc. (Wright, 1988;   Philips and Richards, 1975;

Sundararajan et al., 2006).

The detection of subsurface conductors is made

feasible by means of a portable VLF receiver,which, in most commercial instruments, provides a

measure of the inphase and quadrature components

of the vertical secondary magnetic fields relative to

the horizontal and primary field. Although both

inphase and quadrature components contain valu-

able diagnostic information about the subsurface

targets, only a few schemes exists for extracting the

required information and thereby relating the

observed anomalies to their causative sources. One

such a scheme first proposed by   Fraser (1969)   is a

simple filtering technique known as Fraser filtering.The technique is analogous to passing the inphase

data through a band pass filter which (i) completely

removes DC bias and greatly attenuates long

wavelength signals; (ii) completely removes Nyquist

frequency related noise; (iii) phase shifts all fre-

quencies by 901; and (iv) has the band pass centered

at a wave length of five times the station spacing.

Fraser filtering converts somewhat noisy, non-

contourable inphase components to less noisy,

contourable data which ensures greatly the utility

of VLF-EM survey. VLF-EM contour maps form ameaningful complement to magnetic maps.

Yet another filtering proposed by   Karous and

Hjelt (1977, 1983), enables the geophysicist to

generate an apparent current density pseudosection

by filtering the inphase data and which provides a

pictorial indication of the depth of the various

current concentrations and hence the spatial dis-

position of subsurface geological features such as

mineral veins, faults, shear zones and stratigraphic

ARTICLE IN PRESS

www.elsevier.com/locate/cageo

0098-3004/$- see front matterr 2006 Elsevier Ltd. All rights reserved.

doi:10.1016/j.cageo.2006.02.021

$Code available from server at:   http://www.iamg.org/

CGEditor/index.htm.Corresponding author. Tel.: +91 40 27174793;

fax: +91 40 27099020.

E-mail address:  sundararajan_n@yahoo.com

(N. Sundararajan).1ABEM Printed Matter No. 93062 (http://www.abem.se/

products/wadi/vlf-freq.pdf ).

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conductors (Ogilvy and Lee, 1991). The finite Hjelt

filter method is a more generalized and rigorous

form of the widely known Fraser filter (Fraser,

1969), however is derived directly from the concept

of magnetic fields associated with the current flow in

the subsurface. Application of either Fraser or Hjeltfilter or both to VLF inphase component enables

one to obtain the equivalent current densities at a

constant depth which would cause a magnetic field.

In the absence of numerical modeling, Fraser and

Hjelt filtering techniques are proved to be effective

as they provide a simple scheme for semi-quantita-

tive interpretation.

The aim of this work is to present a simple and

elegent code with GUI-based MATLAB functions

for processing and interpretation of VLF-EM data.

The utility of this program includes: (i) plotting of 

VLF-EM anomalies as stacked profiles using a userdefined filter; (ii) contouring and imaging of the

filtered data for understanding the spatial distribu-

tion of EM conductors; and (iii) preparation of 

pseudodepth section of a chosen traverse using

Fraser and Hjelt filters. Stacking of profiles,

contouring and imaging of magnetic data can be

carried out by this code. These features are

illustrated graphically over a set of inphase compo-

nent of VLF-EM besides contours of magnetic

signal, over a mineralized fracture zone from

Chhattisgarh, India (Ramesh Babu et al., 2004).

2. Filtering of VLF-EM data

Modern commercial VLF-EM instruments read

directly the inphase and quadrature components in

digital form of the vertical secondary magnetic field

expressed as percentage of the primary horizontal

magnetic field. VLF inphase data often yield

complex patterns which require a considerable

study for proper interpretation of the profiles. The

most popular form of presenting 2-D VLF-EM data

over a given area is in the form of stacked profiles.

These are profiles along each survey line plotted on

a 2-D plane in the same relative position as the lines.

VLFPROS facilitates plotting the data in the form

of stacked profiles, which in turn demarcates spatial

location of conductors.

Linear filtering technique developed by   Fraser

(1969)   transforms non-contourable inphase data to

contourable form. Inphase component (VIP) ex-

hibits crossovers in the presence of a conductor/

conducting zones (McNeill and Labson, 1991) as

shown in   Fig. 1(a). The filtering process simply

involves running a four-point weighted average

using the weights of  1,  1, +1, +1. This simple

digital filter operator passes over the inphase

component as shown in Fig. 1(b).

Fraser filtered inphase component when plotted

generally peaks over the top of the conductor asshown in dotted line (Fig. 1(a)). This alteration of 

the raw data is termed as Fraser filtering and can be

summarized in two statements: (i) the filter phase

shifts all spatial frequencies by 901, i.e., it turns

crossovers into peaks or troughs; and (ii) it exhibits

a band pass response, in other words, it greatly

diminishes either sharp irregular responses (noise)

or long rolling responses. At the same time, it

accentuates responses which are the nearest to the

filter’s shape. Subsequently, the filtered output is

plotted again at the center of the filter shown (Fig.

1(b)) as Fraser filter coefficients. The filter is thenmoved ahead of one data spacing and the procedure

is repeated. Once all the profiles are filtered, the

filtered output is contoured and imaged. The

interpretation of maps/images generated from the

Fraser filtered output is qualitative in nature. A

large amplitude can be considered as a large

conducting zone. Very sharp and low amplitudes

indicate shallow sources, and, conversely, broader

amplitudes of large wavelengths indicate progres-

sively deeper sources.

The Hjelt filter technique is a more generalizedand rigorous form of the Fraser filter but is directly

derived from the concept of magnetic fields asso-

ciated with current flow in the earth. From the

filtered VLF inphase component, one obtains the

equivalent current densities at a constant depth

which would cause a magnetic field. That is, the

filter attempts to determine the current distribution

responsible for producing the measured magnetic

field. Determination of the filter shape (coefficients)

is fairly a simple mathematical process (Karous and

Hjelt, 1977). A number of filters with various

lengths and shapes can be developed, however the

optimized Hjelt filter (Karous and Hjelt, 1983) can

be expressed as

DZ =2PI að0Þ ¼ 0:205 H 3 0:323H 2 þ 1:446H 1

1:446H 1 þ 0:323H 2 0:205H 3,

where   I a   (0) ¼ 0.5 [I (DX /2)+I (DX /2)] and where

H 3,   H 

2, etc., are the measured data at six

consecutive stations,   DX   is the measurement inter-

val and   I a   is the apparent current density. Proce-

dures for applying the Hjelt filter is exactly the same

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as that of Fraser filter, including proper orientation

so as to match expected anomaly shapes. While the

filter passes along the data profile, the inphase

components are multiplied by the filter coefficients

and then all the six products are added to produce

one output value which is represented at the center

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-6

-4

-2

0

2

4

6

8

10

12

14

0   9060 70 805040302010   100

inphase componentFraser filteredHjelt filtered

X-axis

(operator facingtransmitter i.e., Y-axis)

(conductor)

   F   i   l   t  e  r  c  o  e   f   f   i  c   i  e  n   t  s

   F   i   l   t  e  r  c  o  e   f   f   i  c

   i  e  n   t  s

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

0 2 4 5 6

-2

-1

0

1

2

(centre)

(profile)

(-1) (-1)

(1)(1)

Hjelt filter coefficients

Fraser filter coefficients

Conductor response

1 3

(a)

(b)

(c)

Fig. 1. (a) Schematic sketch of conductor response. (b) Schematic sketch of Fraser filter coefficients. (c) Schematic sketch of Hjelt filter

coefficients.

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of the filter as shown in   Fig. 1(c). The process

continues till the end for all the profiles. Then the

output is contoured and interpreted in a similar way

to that of the Fraser filter.

3. Pseudosection

An additional interpretative tool is based on

pseudosection of the filtered outputs. This is

obtained by processing a chosen single data profile

either by Fraser or Hjelt or both at various lengths

or spans. As the length of the filter increases,

responses from increasing depths are successively

emphasized. Therefore if the outputs are arranged

on a section such that greater depths correspond to

longer filters than the section should approximately

resemble the current pattern in the ground. How-

ever, it must be emphasized that this is only anapproximation to the section (Wright, 1988; Fraser,

1981). Thus, construction of the pseudosection

consists of a number of steps like processing the

profiles with as many as number of levels (approxi-

mately 5 or 6), at each level, in terms of integer

multiples of the station spacing (n Dx) where n  is the

number of levels and   Dx   is the station spacing.

Finally, plotting the results separated by   nD

x   ateach level one below the other so as to form a

section. Interpretation of the pseudosection is also

fairly general and consists of the following se-

quences: (i) areas with high current-densities corre-

spond to good conductors; (ii) negative contours are

due to high resistivities; and (iii) the trend of the

contour pattern indicates the dip of the conductor.

4. Matlab implementation

VLFPROS is a Matlab Version 6.0 R12-based

program for processing of VLF-EM data and whichcan also be implemented on Version 7.0 R14. This

program can be activated either by an ‘m’ file

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Fig. 2. Flow chart of VLFPROS.

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‘‘VLFPROS ’’ or by a figure file of ‘‘VLFPROS ’’ as

found in flowchart (Fig. 2). From Matlab command

window, once the   VLFPROS   is loaded on activa-

tion, a window consisting of push buttons with

various options such as (i)   contouring, (ii)   stacked 

 profiles and (iii) pseudosection display on the screen.The VLF inphase component which is the input to

VLFPROS has to be created in three different

columns separated by a comma or space and free

from headers. The first column should contain   X 

location, second column   Y   location and the third

column should contain the inphase component of 

VLF-EM data. Example ‘vlfip.dat’ is a VLF inphase

component data which is available for demo

(Fig. 3).

To begin with stacked profiles option is selected

and which displays   filtering and stacked profiles

window. This window enables plotting of raw data,

filtering (with various options like Fraser, Hjelt_1,

Hjelt_2) and plotting of filtered outputs in the form

of stacked profiles. The input data file has to bespecified in the appropriate diallog box   enter file

name  option and then click  plot profile  for raw data

stacked profiles. Further, one of the three available

filters can be made use of to filter the input data by

entering the appropriate filter name (Fraser.txt/

Hjelt_ 1.txt/Hjelt_ 2.txt). Then specify an output file

name against  enter output file  name dialog box and

then enter to obtain the stacked profiles of the

filtered data. To contour/image of the filtered

output, go to   VLFPROS    and click   contouring.

Contouring and imaging   window appears on the

screen. Contouring and imaging can be realized byspecifying a data file name in the appropriate diallog

box, the  maximum and minimum value  of the input

data file appear. An appropriate  cell size  has to be

specified. Select a gridding method out of available

options linear, cubic, nearest, V4 (Matlab 4 griddata

method) from the popup menu, which results the

interpolated minimum and maximum contour

values. The cubic and V4 methods produce smooth

surfaces while ‘linear’ and ‘nearest’ have disconti-

nuities in the first and zeroth derivatives respectively

(Sandwell, 1987). Finally specify the appropriatecontour interval for contouring.

To prepare pseudosection, activate VLFPROS

and click   pseudosection   which displays the   pseudo-

section   window. Enter the   input file name   of raw

data and select a specific profile line number which

is to be pseudosectioned. Once the line number is

selected from the popup menu, enter the appro-

priate filter and output files in their respective dialog

boxes. Then choose the number of levels from popup

menu and then click to write the  filtered output  to a

file which can further be used for obtaining the

pseudosection using  contouring  option.

The entire operations are illustrated with VLF

inphase component (vlfip.dat) pertaining to miner-

alized fracture zone from Chhattisgarh, India. The

stacked profiles of raw data and its image are shown

in   Fig. 4(a) and (b), respectively. While the Fraser

and Hjelt filtered outputs in the form of stacked

profiles are given in   Fig. 5(a) and (b), and the

corresponding images are given in Fig. 6(a) and (b),

respectively. The pseudosections of the chosen line

(traverse 50) based on Fraser and Hjelt filters are

shown in Fig. 7(a) and (b). The magnetic data from

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Fig. 3. Location and geological map of area.

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100 200 300

0

100

200

300

400

500

0 % 

50 % 

100 200 300

0

100

200

300

400

500

600

distance in metres distance in metres

   d   i  s   t  a  n  c  e

   i  n  m  e   t  r  e  s

   d   i  s   t  a  n  c  e

   i  n  m  e   t  r  e  s

0 % 

50 % 

Fraser filtered Hjelt filtered

(a) (b)

Fig. 5. (a) Stacked profiles of Fraser filtered VLF-EM inphase component. (b) Stacked profiles of Hjelt filtered VLF-EM inphase

component.

Fig. 4. (a) Stacked profiles of VLF-EM inphase component. (b) Image with contours of VLF-EM inphase component.

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ARTICLE IN PRESS

Fig. 7. (a) Pseudodepth section of Fraser filtered VLF-EM inphase component. (b) Pseudodepth section of Hjelt filtered VLF-EM inphase

component.

Fig. 6. (a) Image with contours of Fraser filtered VLF-EM inphase component. (b) Image with contours of Hjelt filtered VLF-EM inphase

component.

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the same location is imaged and shown in Fig. 8 and

which may be compared with the Fraser and Hjelt

images (Fig. 6(a) and (b)) of the VLF-EM inphase

component.

5. Conclusion

The VLFPROS, thus a simple Matlab code with

GUI which produces stacked profiles of both raw

and filtered data, in addition to their images with

contours. This code can also be used for processing

of magnetic data to obtain the contours/images/

stacked profiles. This code can be modified for

additional features. Further, pseudosections provide

first hand information regarding the number, size,

depth and relative disposition of the conductors.

Acknowledgements

The authors wish to record their sincere and

profound thanks to Dr. Roger Guerin for many

useful suggestions to prepare this manuscript.

Further, they extend their heartful thanks to Prof.

A.V.R.S. Sarma, Head, Department of Electrical

Engineering, Osmania University for provi-

ding computational facilities. The second author

expresses his gratitude to Dr. R.N. Sinha, Director,

Atomic Mineral Directorate for Exploration and

Research (AMD), Department of Atomic Energy,

Hyderabad, India for his kind permission to publish

this paper and also his encouragement to do Ph.D.

One of the authors Y. Srinivas would like to thankthe Council of Scientific and Industrial Research

(CSIR), New Delhi, India for financial support.

Appendix A. Supplementary Materials

Supplementary data associated with this article

can be found in the online version at  doi:10.1016/

 j.cageo.2006.02.021.

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958–967.

Fraser, D.C., 1981. A review of some useful algorithms in

geophysics. Canadian Institute of Mining Transactions

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Karous, M., Hjelt, S.E., 1977. Determination of apparent current

density from VLF measurements: Report. Department of 

Geophysics, Univeristy of Oulu, Finland, Contribution No.

89, 19pp.

Karous, M., Hjelt, S.E., 1983. Linear filtering of VLF dip-angle

measurements. Geophysical Prospecting 31, 782–794.McNeill, J.D., Labson, V., 1991. Geological mapping using VLF

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of the VLF method for the location of narrow, mineralized

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Bhattacharya, A.K., 2004. VLF-EM surveys for uranium

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Fig. 8. Image of raw magnetic data.

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