An empirical approach to inversion of an unconventional helicopter electromagnetic dataset

www.elsevier.com/locate/jappgeo

Journal of Applied Geophysics 53 (2003) 49–61

An empirical approach to inversion of an unconventional

helicopter electromagnetic dataset

Louise Pellerina,*, Victor F. Labsonb

aConsulting Geophysicist, 2215 Curtis Street, Berkeley, CA 94702, USAbU.S. Geological Survey, P.O. Box 25046, MS 964, Denver, CO 80225, USA

Received 29 January 2002; accepted 20 January 2003

Abstract

A helicopter electromagnetic (HEM) survey acquired at the U.S. Idaho National Engineering and Environmental Laboratory

(INEEL) used a modification of a traditional mining airborne method flown at low levels for detailed characterization of

shallow waste sites. The low sensor height, used to increase resolution, invalidates standard assumptions used in processing

HEM data. Although the survey design strategy was sound, traditional interpretation techniques, routinely used in industry,

proved ineffective. Processed data and apparent resistivity maps were severely distorted, and hence unusable, due to low flight

height effects, high magnetic permeability of the basalt host, and the conductive, three-dimensional nature of the waste site

targets.

To accommodate these interpretation challenges, we modified a one-dimensional inversion routine to include a linear term in

the objective function that allows for the magnetic and three-dimensional electromagnetic responses in the in-phase data.

Although somewhat ad hoc, the use of this term in the inverse routine, referred to as the shift factor, was successful in defining

the waste sites and reducing noise due to the low flight height and magnetic characteristics of the host rock. Many inversion

scenarios were applied to the data and careful analysis was necessary to determine the parameters appropriate for interpretation,

hence the approach was empirical.

Data from three areas were processed with this scheme to highlight different interpretational aspects of the method. Wastes

sites were delineated with the shift terms in two of the areas, allowing for separation of the anthropomorphic targets from the

natural one-dimensional host. In the third area, the estimated resistivity and the shift factor were used for geological mapping.

The high magnetic content of the native soil enabled the mapping of disturbed soil with the shift term.

Published by Elsevier Science B.V.

Keywords: Electromagnetics; Helicopter electromagnetics; Airborne electromagnetics; Inversion; Waste site characterization

1. Introduction

In 1991, a helicopter electromagnetic (HEM)

survey was acquired at the U.S. Department of

0926-9851/03/$ - see front matter. Published by Elsevier Science B.V.

doi:10.1016/S0926-9851(03)00011-9

* Corresponding author. Tel.: +1-510-70166; mobile: +1-510-

326-7269.

E-mail address: [email protected] (L. Pellerin).

Energy (DOE) Idaho National Engineering and

Environmental Laboratory (INEEL). Data were col-

lected by Ebasco Inc., using the Aerodat Inc., HEM

system. The survey targets were buried waste sites

composed of trenches and pits that contained drums,

ordnance, and other waste, which are highly three-

dimensional (3D) in nature. The host geology,

composed primarily of basalt, had a strong magnetic

L. Pellerin, V.F. Labson / Journal of Applied Geophysics 53 (2003) 49–6150

signature. The strategy was to reduce the flight

height to increase the resolution. Applying standard

processing procedures, as discussed in Palacky and

West (1991), resulted in uninterpretable results;

stripes due to differential coupling between the 3D

targets, magnetic structures and flight height varia-

tions dominated the apparent resistivity maps. Only

sources for the most obvious anomalies could be

delineated, and these were severely distorted. Hence,

the dataset was released to the U.S. Geological

Survey for an innovative processing and interpreta-

tion.

To the authors’ knowledge, the INEEL HEM

survey is the first application of a mineral explora-

tion airborne method used for detailed characteriza-

tion of shallow waste sites. The focus of the study

was to evaluate the effectiveness of helicopter geo-

physics in waste site characterization, and to estab-

lish guidelines for low-level environmental surveys.

This study aided in defining survey design criteria

and identifying interpretational pitfalls in a large

HEM survey flown over the Oak Ridge Reservation

(Doll et al., 2000). Traditional mining techniques,

which are designed to locate large conductive targets

at depth, cannot always be directly transferred to the

environmental arena without a clear understanding of

the differences between mining and near-surface,

small-scale environmental characterization objec-

tives.

Fig. 1. Location map of the U.S. Idaho National Engineering and Environ

site and Subsurface Disposal Area (SDA) survey areas in the south of the

2. Survey description

The INEEL is located in the state of Idaho in the

northwestern US on the Snake River flood basalt as

shown in Fig. 1. Vegetation of the desert environment

consists primarily of low-level brush including sage.

The flood basalts have low topographic relief and

buildings, vehicles, power lines, pipelines and other

cultural features were minimal so that cultural noise

and topography did not cause significant problems.

High spatial density, low flight level HEM data

were acquired over three of the INEEL buried waste

sites—the SL-1 site, the Cold Test Pit (CTP), and the

Subsurface Disposal Area (SDA), all located in the

southern section of the INEEL. The SL-1 area, meas-

uring approximately 200 m� 175 m, contains a few

large metallic objects. The CTP, a small 50 m� 100 m

site, engineered for testing characterization and reme-

diation techniques contains drums and boxes. The

term ‘cold’ implies the absence of radioactive waste.

The SDA, the largest site flown measuring roughly

250 m� 275 m, contains trenches and pits that have

received mixed waste for the last 50 years.

Data were acquired at a line spacing of 7.5 m and a

nominal altitude of 15 m using horizontal coplanar

(HCP) coil pairs at 500, 4175, and 33000 Hz and

vertical coaxial (VCA) coil pairs at 935 and 4600 Hz.

In-phase and quadrature data were recorded in parts

per million (ppm) of the primary, or free space,

mental Laboratory (INEEL) showing the Cold Test Pit (CTP), SL-1

laboratory.

Fig. 2. HEM profiles over the SDA site for the 500 Hz HCP

configuration: (a) flight height in meters, (b) in-phase and (c)

quadrature responses in ppm. Data are typical for the survey.

Table 1

Definition of labels used in Fig. 3

Label Forward

solution

Layer 1

resistivity

Layer 1

thickness

Layer 2

resistivity

Shift

NIfix numerical

integration

free free 500 V m yes

NIfree numerical

integration

free free free yes

IMfix complex

image

free free 500 V m yes

IMfree complex

image

free free free yes

no shift complex

image

free free free no

L. Pellerin, V.F. Labson / Journal of Applied Geophysics 53 (2003) 49–61 51

response in both the north–south and east–west

directions. Accurate flight height information is very

important due to the low flight height. Laser altimeter

data was used with confidence because of the sparse

vegetation at the INEEL.

Accurate position recovery is one of the most basic

requirements of any survey. Without it, the results from

all of the geophysical methods are compromised.

Because of the very close line spacing, the INEEL

survey is particularly affected by position recovery

errors, much more so than standard mining surveys.

Three navigation or position recovery systems were

employed in this survey: Global Positioning System

(GPS), radar range positioning system (MiniRanger),

and down-looking video both on the helicopter and the

bird. Each system produces a particular set of system-

atic errors that are minimized after making appropriate

comparisons with the other two systems. This proce-

dure is tedious and time consuming, but necessary.

Errors, identified as small random errors and system-

atic data-delay errors causing the herringbone effect,

were minimized by using the combination of techni-

ques, and we estimate position accuracy of 1 m or less.

3. Interpretational challenges

Traditionally processed data, and the correspond-

ing apparent resistivity maps, were severely distorted,

and hence unusable. Interpretational problems were

encountered because of low flight height effects, the

high magnetic permeability of the soils and basement

basalt, and the very conductive, magnetic, 3D nature

of targets within the waste site.

3.1. Effect of flight height

A basic assumption in standard HEM interpreta-

tion is that the separation between the transmitting

and receiving coils is less than one-third the flight

height (Palacky and West, 1991). With an inter-coil

separation of 7 m and a nominal flight height of 15

m, this assumption is violated, and the resulting

apparent resistivity maps are in error. When the

flight height is small with respect to inter-coil

separation, data are extremely sensitive to variations

in flight height. Low flight height can result in an

overestimate of resistivity, and conversely flight

height above the nominal altitude can result in

underestimates. The 500 Hz dataset, which is the

least sensitive to these effects, was analyzed first.

Fig. 2 shows the (a) altitude, (b) in-phase and (c)

quadrature responses for the HCP configuration at

500 Hz for a representative east–west profile across

the SDA. The profile line is just north of the center

of the survey area. These responses and variation in

flight height are typical for the entire INEEL

survey.


Variations in flight height do not pose a significant

problem when the subsurface is one-dimensional (1D),

as seen on the west or left side of Fig. 2. However, to the

east, or right side, the in-phase and quadrature re-

sponses are complicated by a highly anomalous subsur-

Fig. 3. Inversion parameters and the correspondingmisfit for CTP L2040: (a

(c) estimated resistivity of bottom layer, (d) shift for HCP configuration,

different forward models and constraints: NIfix refers to the numerical integr

m; NIfree is the numerical integration solution for all parameters being free;

m; IMfree is the image solution with all parameters free; and ‘no shift’ is th

face and the variations in flight height. It is not clear

how much of the anomalous response is due to struc-

ture and how much is due to variations in flight height.

This effect will be discussed in detail for the SL-1 site

below.

) estimated resistivity of top layer, (b) estimated thickness of top layer,

and (e) shift for VCA configuration. These figures show results for

ation forward solution with the bottom layer resistivity fixed at 500V

IMfix is the image forward solution with the bottom layer set at 500V

e inversion results without the shift terms and all parameters free.

Fig. 3 (continued).


3.2. High magnetic permeability

The INEEL is located on the Snake River flood

basalt that has a high magnetic permeability. The

soils derived from the basalt also possess a high

magnetic permeability (Olhoeft, personal communi-

cation). In addition, the metallic conductors in many

of the waste sites have a magnetic signature. The

magnetic response in the host is apparent in Fig. 2b.

Values for the 500 Hz in-phase background response

were expected to be small and positive for layered

sediments (Beard and Nyquist, 1998), but are

roughly -50 ppm. The responses over an anomalous

area are greater than 100 ppm for the in-phase and

300 ppm for the quadrature.

Data recorded as a percent of the free-space

response is valid only when the response is from the

primary field and that due to induction in the earth.

When calculating a model response assuming a free-

space magnetic permeability, the results will be in

error in the presence of an earth having a high

magnetic permeability (Fraser, 1981). The error is

small for the quadrature component, but significant

for the in-phase component (Parasnis, 1986). Invert-

ing data using an inappropriate model can result in

erroneously high resistivity estimates (Beard and

Nyquist, 1998). As the magnetic permeability of the

basalt varies from point to point, false anomalies can

result. This effect is greatly enhanced by variation in

the low-level flight height.

3.3. Three-dimensional targets

The buried waste problem is highly 3D and, in this

case, highly conductive. Hence, standard 1D inversion

is incapable of reconstructing a realistic image of the

subsurface. Highly conductive targets have a signifi-

cant response above the low-induction limit; where


the quadrature is linearly proportional to the conduc-

tivity, and the predominant response is in the in-phase

component. When currents are trapped in a near

surface conductor, a strong response is maintained

even at low frequencies. A 1D inversion assumes

currents have diffused into the earth at low frequen-

cies. Therefore, a true 1D inversion will place a

fictitious conductive layer at depth to account for

the strong low frequency response.

4. Inversion strategy

The inversion method used to obtain the 1D

layered earth models from dipole loop–loop data

follows the algorithm by Anderson (1982) that des-

cribes an adaptive nonlinear least-squares method for

constrained minimization problems. Dennis et al.

(1979, 1981) published the original algorithm that

we adopted for unconstrained solutions. Two 1D

forward calculations were available in the inverse

solution: a numerical integration scheme described

in Anderson (1982) and a rapid, approximation using

complex image theory (Anderson, 1992). The latter

scheme was newly developed and tested in the hopes

of finding a fast processing technique. In general, the

two forward solutions gave equivalent inversion

results. After running many inversions with different

parameterization and the two forward solutions,

results are presented from the image solution on the

CTP dataset and the numerical integration scheme on

the SDA and the SL-1 datasets. The 1D inversion

routine fits the in-phase and quadrature data to a

locally layered earth utilizing point-by-point inclusion

of the laser altimeter data.

A special modification to the inversion technique is

the addition of an in-phase shift factor that accounts

for the high magnetic permeability of the basalt, and

high conductivity and 3D nature of targets within the

waste site. The objective function S to be minimized

subject to minimum length regularization, is given by

S ¼ d � ½ðFID�HCP þ UHCPÞ� þ ½ðFID�VCA þ UVCAÞ�:

Where F1D is the 1D function for the HCP and VCA

configurations, UHCP and UVCA are the corresponding

shift factors and d are the data.

The algorithm allows for inversion of resistivity

and thickness for a specified number of layers, along

with the linear shift factor for magnetic and 3D

effects. We found that a two-layer inversion was most

appropriate to estimate the resistivity and thickness of

the alluvial layer, which contains the buried waste,

over the basement basalt. Separate shift factors were

used for the HCP and VCA configurations. A priori

information was used to set inversion parameters

whenever possible. We computed inverse models with

the basement resistivity set at different values and as a

free parameter to be determined by the inversion

algorithm. The best results were obtained when the

basement resistivity was fixed, because the basement

basalt is resistive and hence a poorly resolved param-

eter. We found estimates for the top layer resistivity

and thickness were insensitive to the basement resis-

tivity as long as the latter was greater than 500 V m.

Tests showed variations of only a few percentage in

the top layer parameters for basalt resistivity fixed at

500, 1000 and 1500 V m.

5. Survey results

An empirical approach was taken with the inter-

pretation of the INEEL datasets: several parameters

were tested in the inversion and the most favorable

combination was used to produce the final maps. A

priori information was used whenever possible to set

inversion parameters and to evaluate results, in addi-

tion to geological/geophysical experience and data

misfit. The percent misfit is defined as

misfitðmÞ ¼

ffiffiffiffiffiffiffiffiffiffiffiffirðmÞ2

q

EðmÞ � 100;

where r2 is the variance, E is the prediction error of

the least-squares solution, and m the model parameter

(Dennis et al., 1981; Menke, 1989). We selected lines

to describe the process used to produce the final maps.

5.1. Cold Test Pit (CTP)

The subsurface conditions are very well known at

the CTP (Pellerin et al., 1997), because of its small

size and being an engineered structure. Both numer-

ical integration and complex image forward solutions


were tested in the inversion routine. The resistivity of

the second layer, the basement basalt, was allowed as

a free parameter in the inversion and was set to 500

and 1000 V m. Inversions were also calculated with

and without the shift factor for both HCP and VCA

configurations. Table 1 summarizes the various com-

binations presented in Fig. 3.

Five pairs of plots for a representative profile line

(L2040) are shown in Fig. 3. These show the layer 1

resistivity (q1) and thickness (t1), layer 2 resistivity

(q2), and shift terms (UHCP and UVCA) along with the

corresponding percent misfit for the five combinations

defined in Table 1. The solution used to produce the

maps in Fig. 4 is noted in bold type. The location of

profile L2040, near the center of the CTP, is shown in

Fig. 4.

First, let us consider the five solutions in Fig.

3a, b and c. The ‘no shift’ solution is by far the

Fig. 4. The CTP plan view maps for (a) estimated resistivity for the alluvia

the soil disturbed to build the CTP. Flight lines are superimposed as faint bla

site. The dotted white line, with arrows showing the flight direction, depi

noisiest with respect to data misfit, having many

values greater than 500% and the least smooth of

the curves for q1, t1 and q2, respectively. As

anticipated the ‘no-shift’ solution was easy to

reject.

The next step is to look at the effect of the bottom

layer resistivity, q2 in Fig. 3c. Resistive basalt under-

lies the INEEL and it was not expected that this would

be a well-resolved parameter. As discussed above, q2

was set at 500 V m for the fixed parameter inversion.

When allowed to vary freely in the inversion, the

numerical integration scheme (NIfree) returned values

generally around 10000 V m, whereas the complex

image solution (IMfree) estimated q2 at values bet-

ween 50 and 70 V m, similar to the ‘no-shift’ solution.

The latter estimates indicated the presence of the

highly conductive waste in the near surface was

downwardly influencing the estimates of q2. The more

l layer and (b) HCP shift parameter. The HCP shift factor delineates

ck dots in (b). The dashed white line shows the location of the waste

cts flight line L2040 analyzed in Fig. 3.


resistive values of the NIfree solution are geophysi-

cally reasonable, but the misfits are large.

The resistivity and thickness of the top layer are the

most important parameters to resolve. After fixing the

value of q2 at 500 V m, the numerical integration

(NIfix) and complex image (IMfix) solutions were

examined. The q1 parameter in Fig. 3a for the IMfix

solution was the best resolved with misfit values

consistently less than 20%, and values were in good

agreement with ground surveys (Pellerin et al., 1997).

The misfit for q1 for NIfix was quite noisy with valuesas high as hundreds of percent; the resistivity values

were as low as 5 V m.

The t1 parameter (Fig. 3b) was difficult to estimate

with confidence for any of the solutions. IMfix gave

Fig. 5. Resistivity and thickness of the top layer, and corresponding misfits

L1050 crossed an anomalous area. The solid lines represent the estimated re

the shift factor.

the smoothness estimates with the lowest misfit, but

the values were unreasonable high, ranging from

about 18 to 35 m. The NIfix values for were more

reasonable at less than 5 m, but the average misfit was

approximately 100%. Therefore, final maps were not

produced for this parameter.

Turning to Fig. 3d and e, we see that the linear shift

term is well resolved. All solutions gave misfits well

under 1% for UHCP and under 3% for UVCA. The HCP

shift was more than an order of magnitude larger than

that of the VCA shift, and the anomaly was much

more clearly defined. This can be attributed to the fact

that the HCP configuration is more sensitive to flat

lying objects, and as we shall see below that is the

geometry of the mapped structure.

, for representative lines of the SL1 site. (a) L1230 does not and (b)

sistivity, the long-dash lines the thickness, and the short-dashed lines


Given these results, only the estimated resistivity

of layer 1 and the HCP shift parameters for the IMfix

solution were used to produce final maps, as shown in

Fig. 4a and b, respectively. Fig. 4a shows the resis-

tivity structure of the alluvial layer, and in particular

the two low resistivity anomalies to the east of the

CTP that were apparent in long-offset ground elec-

trical resistivity and high-frequency ellipticity surveys

described by Pellerin et al. (1997). These anomalies

are associated with natural features in the subsurface,

and are not apparent in the shift. The map of the HCP

shift factor in Fig. 4b shows an anomalous area

surrounding the CTP that is larger than the waste

pit, which is depicted by the dashed white line. These

results were at first rather puzzling, but magnetic

permeability measurements on soil samples (Olhoeft,

personal communication) indicate that the native soil

is highly magnetic and lossy, while the soil imported

from another site to build the CTP is neither. The

positive shift is characteristic of the native soil. The

negative shift outlines the disturbed soil boundary at

the CTP site that has a depth extent to the basement

basalt.

5.2. SL-1

The final model for the SL-1 site was obtained

with the numerical integration solution for the sec-

Fig. 6. Plan view maps for SL-1 site showing the (a) HCP shift parameter a

Lines 1050 to L1080. Flight lines analyzed in Figs. 5 and 7 are noted wi

ond layer resistivity set at 500 V m. Fig. 5a and b

shows the resistivity and thickness of the top layer,

respectively, with the corresponding misfits for rep-

resentative lines L1230 and L1050. L1230 is over an

area showing no anomalous structures whereas

L1050 crosses two large objects. Variations in layer

thickness, t1, track the variations of the resistivity,

q1. The misfits are almost indistinguishable and

values are quite high, making both of these param-

eters highly suspect. Therefore, only the UHCP map

is presented.

Three large metallic objects along with the

surrounding fence are outlined with UHCP as shown

in Fig. 6a. The positive value of the shift indicates

that the waste objects have a combination of high

magnetic permeability and a 3D signature. There

are herringbone distortions over the two anomalies

in the northeast portion of the survey area due to

large variations of over 25% in flight height, shown

in Fig. 6b, which could not be corrected. Although

the targets are clearly present, accurate placement of

the objects could be problematic due to these

distortions.

The correlation between the anomaly map and the

variations in flight height can be seen in Fig. 5a and b,

however a more detailed view of representative lines

is warranted. Plots of flight height (long dash), and the

resistivity of the top layer (solid) for (a) L1080 and (b)

nd (b) flight height. Note the severe variations in flight height along

th bold, black dots and arrows showing the flight direction.

Fig. 7. Plots of flight height (dash), and the resistivity of the top

layer (solid) for flight lines (a) L1080, and (b) L1050. L1080 has

a low flight height of 12 m with about 3 m variation, and L1050

is anomalously high with flight height of 22 m and a 6-m

variation.


L1050 are shown in Fig. 7a and b, respectively. L1080

shows low flight heights of 12 m with about 3 m

variation, and L1050 shows abnormally high flight

heights of 22 m with a 6-m variation.

Given the close proximity and similar character of

L1050 and L1080, it is reasonable to assume the

estimated resistivity values are distorted by variations

in flight height. At the north end of the lines, resis-

tivity values are roughly 75 V m and flight height 16

m. On the southern half of L1080, the flight height

drops to about 13 m and resistivity is about 30 V m. In

contrast, on L1050 flight height increases to 22 m and

the average resistivity drops to 10 V m. If this were a

purely 1D environment, the inversion results would be

independent of flight height. However, we observe a

low flight height corresponding to increased signal

strength that results in an overestimate of resistivity,

and conversely for the case of increased altitude,

which is consistent with the modeling results of Beard

and Nyquist (1998).

5.3. Subsurface Disposal Area (SDA)

Fig. 8 is the engineering drawing for the SDAwith

the HEM survey area outlined in red, and the SDA

boundary in blue. Engineers excavated to bedrock in

constructing the SDA. The bottom of the waste is

located at 10 m and we fixed that value in the

inversion along with a basement resistivity of 500 V

m. Fig. 9a and b shows the resistivity of the top layer

and the ratio of UHCP and UVCA, respectively. The

triangle-shaped boundary of the SDA can be seen in

both maps. The trenches and pits are clearly de-

lineated in the north section of the SDA with the shift

factor ratio. In the southern part of the survey area, it

appears that waste may be outside of the boundary.

The resistivity map characterizes the background

structure that hosts the waste pits and trenches,

showing a resistive zone, presumed to be gravel, to

the NW. The low resistivity in the SDA is probably

due to clay used in the construction of the disposal

area. Stripes, mostly to the east of the SDA, in the

resistivity map in Fig. 9a are effects due to extreme

variations in flight height.

The use of the shift ratio was determined empiri-

cally. The HCP is sensitive to flat lying structure and

the VCA to vertical contrasts. In the complex structure

of the SDA, both structures are present. This was

evident in the fact that the amplitude for both shift

factors was equivalent. Experimentation showed that

the ratio of the shift factors was best in emphasizing

the trenches and pits.

The quality of the solution is appraised in Fig. 10

with parameter misfits for pairs of lines representing

anomalous areas. Fig. 10a and b shows the misfits for

the alluvial resistivity and the two shift factors,

respectively. Fig. 10c is a distribution of the misfit

for all three parameters. The misfit is generally less

than 5% for the resistivity and less than 2% for the

shifts. Higher misfits of over 20% are present in the

highly anomalous waste zones. Fixing the values of q2

and t1 increases the accuracy of and the confidence in

Fig. 9. Plan view of (a) estimated resistivity of the alluvial and (b) ratio of UHCP to UVCA for the SDA site. Flight lines are superimposed on

maps with selected lines noted. The outline of the SDA is noted in white.

Fig. 8. Engineer plan of the SDA site showing the HEM survey area in red, trenches and wastes pits, and the SDA boundary in blue.


Fig. 10. The percent misfit for the SDA site for (a) resistivity of the alluvial layer and (b) UVCA and (c) UHCP for selected flight lines. (d) shows

the cumulative distribution of parameter misfit for the three parameters for over 3000 data points.


the remaining parameters, which were used to make

the final maps.

6. Discussion and conclusions

Magnetic structures and highly 3D targets can

cause interpretational problems even for a well-

designed HEM survey. The HEM survey described

here contained these problematic features and was

further complicated with irregular low-level flight

height that caused a layered-earth model that was

highly variable from adjacent sounding points. Due

to the density of HEM datasets, an efficient processing

technique was required. A 1D inversion with the

addition of a real shift parameter to accommodate

magnetic and 3D responses was developed for data

processing. The inversion was not so robust that all

inverted parameters were reliable, and many inversion

designs were tried. Careful analysis of the data misfit

was necessary to determine appropriate parameters for

interpretation. Hence, it can be said that an empirical

approach was taken to interpret the inversion results.

The low-level HEM surveys, which used standard

commercial instrumentation, were effective in locat-

ing and characterizing buried waste areas at the

INEEL. The 1D inversion algorithm proved to be an

effective processing tool when specifically modified

to accommodate the volcanic geology underlying the

INEEL, the highly conductive buried waste targets,

and the extremely low flight height at which the

survey was flown. All but the most dramatic effects

due to variations in flight height were removed. At the

CTP site, the shift factor outlines a disturbed soil


boundary. The highly magnetic and lossy native soil is

characterized by a high shift factor, while the soil

imported from another site to build the CTP is

distinguished with a negative shift. For the SL-1 and

SDA sites, the response due to the highly magnetic

basalt did not seem to severely distort the 1D esti-

mates of the alluvium hosting the buried waste, and

the shift factor was very effective in delineating the

highly conductive buried waste.

Acknowledgements

The Department of Energy, Office of Environ-

mental Management funded this project. Support to

publish the study was received from the U.S.

Geological Survey and University of Aarhus, Den-

mark. Special thanks is given to Walter L. Anderson,

USGS, retired, for processing the data, Jens Ensted

Danielsen, University of Aarhus, for inspiring, hall-

way discussions, and Les P. Beard, William E. Doll

and David L. Fitterman for their thoughtful reviews.

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Documents

An empirical approach to inversion of an unconventional helicopter electromagnetic dataset