U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2013–5038

Investigation of the Structure and Lithology of Bedrock 

Concealed by Basin Fill, Using Ground-Based MagneticField-Profile Data Acquired in the San Rafael Basin, 

Southeastern Arizona
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Investigation of the Structure and Lithology 

of Bedrock Concealed by Basin Fill, Using 

Ground-Based Magnetic-Field-Profile 

Data Acquired in the San Rafael Basin, 

Southeastern Arizona

By Mark W. Bultman

Scientific Investigations Report 2013–5038

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

SALLY JEWELL, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2013

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Suggested citation: 

Bultman, M.W., 2013, Investigation of the structure and lithology of bedrock concealed by basin fill, using groundbased magnetic-field-profile data acquired in the San Rafael Basin, southeastern Arizona: U.S. Geological Survey 

Scientific Investigations Report 2013–5038, 26 p.
 iii

Contents

Abstract...........................................................................................................................................................1

Introduction.....................................................................................................................................................1

Data Acquisition.............................................................................................................................................3

Estimating Concealed Lithology .................................................................................................................5

Graphical Analysis and Descriptive Statistics of Ground-Based 

Magnetic-Field-Profile Data................................................................................................10

The Power Spectrum of Ground-Based Magnetic-Field-Profile Data.......................................11

The Multifractal Spectrum of Ground-Based Magnetic-Field-Profile Data .............................13

Caveats in the Estimation of Concealed Lithology .................................................................................15

Estimation of Concealed Lithology at Target Site 1.......................................................................16

Structural Analysis near Target Site 1.............................................................................................18

Estimation of Concealed Lithology at Target Sites 2a and 2b......................................................19

Modeling Bedrock Structure over a Potential Mineral-Resource Target .........................................22

Conclusions...................................................................................................................................................23

References....................................................................................................................................................24

Figures

 1. Illustration showing a cross section of a typical basin 

in the Basin and Range geologic province...............................................................................1

 2. Photograph of a basin-fill/bedrock contact visible in a small stream valley

in the San Rafael Basin................................................................................................................2

 3. Data showing the Earth’s total-intensity magnetic field 

acquired at 3.5-m height above ground over exposed bedrock ...........................................3

 4. Photograph of a truck-mounted magnetometer acquiring data 

on the Earth’s total-intensity magnetic field in the San Rafael Valley .................................4

 5. Plot showing the heading error for truck-mounted magnetometer 

in the San Rafael Valley ...............................................................................................................4

 6. Plot showing truck-mounted magnetometer noise plotted along profile ...................................5

 7. Map showing the San Rafael Basin area.........................................................................................6

 8. Geologic map of the San Rafael Basin area....................................................................................7

 9. Image showing a Landsat Thematic Mapper (TM) image 

of the San Rafael Basin, southeastern Arizona in June 1999................................................7

10. Geologic map of the San Rafael Basin, southeast Arizona 

with basin depth contours based on a gravity model.............................................................8

11. Plot showing heading corrected magnetic signatures 

of candidate lithologies and deep basin fill in the San Rafael Basin...................................8

12. Plot showing decorrugated heading corrected magnetic signatures 

of candidate lithologies and deep basin fill in the San Rafael Basin.................................10

13. Plot showing power spectra of candidate lithologies 

and deep basin fill in the San Rafael Basin............................................................................13

14. Plot showing power spectrum of map unit TKvs ..........................................................................13
iv 

15. Plot showing pultifractal spectra of ground-based magnetic-fieldprofile data acquired over exposed bedrock lithologies .....................................................15

16. Plot showing multifractal spectrum of ground-based magnetic-field-profile data ................16

17. Plot showing ground-based magnetic-field-profile data 

over the three high-amplitude candidate lithologies............................................................16

18. Plot showing power spectra of target site 1 and three high-amplitude 

candidate lithologies..................................................................................................................17

19. Plot showing multifractal spectra of ground-based magnetic-field-profile data

 acquired over candidate lithologies.......................................................................................18

20. Plot showing ground-based magnetic-field-profile data 

acquired over basin fill along profile 1....................................................................................18

21. Figures showing profile1, how ground-based magnetic-field-profile data 

provide detailed geologic model of concealed lithology and bedrock geometry............19

22. Plot showing ground-based magnetic-filed-profile data from target sites 2a and 2b............20

23. Plot showing power spectra for target sites 2a and 2b 

and three high-amplitude candidate lithologies....................................................................21

24. Plot showing multifractal spectra of ground-based magnetic-field-profile data 

acquired over candidate lithologies........................................................................................22

25. Plot showing heading-corrected ground-based magnetic-field-profile data for profile 2 ....22

26. Figures showing profile 2, how ground-based magnetic-field-profile data 

provide a detailed model of concealed lithology, bedrock geometry, 

and a mineral resource target..................................................................................................23

Tables

1. Explanation of selected map units ......................................................................................................9

2. Descriptive statistics for candidate lithologies and deep basin fill.............................................12
Investigation of the Structure and Lithology of Bedrock 

Concealed by Basin Fill, Using Ground-Based MagneticField-Profile Data Acquired in the San Rafael Basin, 

Southeastern Arizona

By Mark W. Bultman

Abstract

Data on the Earth’s total-intensity magnetic field acquired near 

ground level and at measurement intervals as small as 1 m include 

information on the spatial distribution of nearsurface magnetic 

dipoles that in many cases are unique to a specific lithology. Such 

spatial information is expressed in the texture (physical appearance 

or characteristics) of the data at scales of hundreds of meters to 

kilometers. These magnetic textures are characterized by several 

descriptive statistics, their power spectrum, and their multifractal 

spectrum. On the basis of a graphical comparison and textural 

characterization, ground-based magnetic-field profile data can 

be used to estimate bedrock lithology concealed by as much as 

100 m of basin fill in some cases, information that is especially 

important in assessing and exploring for concealed mineral deposits. 

I demonstrate that multifractal spectra of ground-based magneticfield-profile data can be used to differentiate exposed lithologies 

and that the shape and position of the multifractal spectrum of the 

ground-based magnetic-field-profile of concealed lithologies can 

be matched to the upward-continued multifractal spectrum of an 

exposed lithology to help distinguish the concealed lithology.

In addition, ground-based magnetic-field-profile data also 

detect minute differences in the magnetic susceptibility of rocks 

over small horizontal and vertical distances and so can be used for 

precise modeling of bedrock geometry and structure, even when 

that bedrock is concealed by 100 m or more of nonmagnetic 

basin fill. Such data contain valuable geologic information on 

the bedrock concealed by basin fill that may not be so visible in 

aeromagnetic data, including areas of hydrothermal alteration, 

faults, and other bedrock structures. Interpretation of these data in 

the San Rafael Basin, southeastern Arizona, has yielded results for 

estimating concealed lithologies, concealed structural geology, and 

a concealed potential mineral-resource target.

Introduction

The Basin and Range geologic province of North 

America supplies nearly all the copper and most of the 

gold and silver mined in the United States. Most producing 

mineral deposits in this region occur in exposed bedrock that 

occupies only about 38 percent of land cover (Heathcote, 

1983).An accurate understanding of the remaining potential 

for undiscovered mineral deposits in the Basin and Range (and 

in many other areas) requires knowledge of the structure and 

lithology of the bedrock that is concealed by relatively shallow 

basin fill, primarily on the piedmont slopes of the ranges 

(fig. 1), an area also referred to as the basin margin (fig. 2). 

modern

nickpoint

exposed bedrock pediment

buried pediment surface

basin and range faults

high Pleistocene

surface

mid-Pleistocene

gravel deposit terrace

gravel

deposits

modern

alluvium

trunk stream

2–5 km wide piedmont slopes modern floodplain

Holocene alluvium

Granite

Volcanic rocks

(basalts, rhyolites)

Sedimentary rocks

(limestones, dolomites, sandstones, etc.)

Sedimentary deposits, clayey, muddy and evaporitic

Sandy soil

Gravelly soil

Bedrock

Figure 1. Illustration showing a 

cross section of a typical basin 

in the Basin and Range geologic 

province (after Pierce, 1985).
2 Investigation of the Structure and Lithology of Bedrock Concealed by Basin Fill

Identification of concealed lithology 

at regional scales by using aeromagnetic 

data has been shown to be feasible by 

Gettings (2008). This study focuses on 

the identification of concealed lithology 

and the structural interpretation of 

magnetic-field-profile data at larger scales 

(hundreds of meters to kilometers) for 

use in the study of basin margins. At 

these scales, aeromagnetic data generally 

contain insufficient information for the 

estimation of concealed lithology or 

precise structural modeling of concealed 

bedrock. Information on the Earth’s totalintensity magnetic field is lost extremely 

fast as the magnetic sensor moves away 

from the ground, and so for large-scale 

interpretations magnetic-field data must 

be acquired as near to the ground and as 

closely spaced as possible. 

Profiles created from near-ground, 

closely spaced total-intensity-magneticfield data are generally much rougher 

in appearance than those created from 

aeromagnetic data, even those acquired 

at low altitude, owing to the greater 

Figure 2. Photograph of a basin-fill/bedrock contact visible in a small stream valley in

the San Rafael Basin, southeastern Arizona. Here, andesite underlies the 3-m thick basin 

fill.

information content of near-ground data relative to aeromagnetic 

data, commonly acquired at altitudes of 100 to 300 m above the 

surface. Such near-ground data, which are acquired by using a 

magnetometer mounted on a utility vehicle, are herein referred to 

as “ground-based magnetic-field-profile data” and the acquired 

data as the “magnetic signal,” which may be from a specific 

exposed lithology (map unit) or from a target site over basin fill 

where the identity of the lithology concealed by the basin fill is 

to be determined. Acquisition of data near the ground (near the 

magnetic sources) maximizes the information content extracted 

from the Earth’s total-intensity magnetic field, information 

important in discriminating the magnetic signal from both 

exposed and concealed lithologies. The high information content 

of ground-based magnetic-field-profile data also allows for the 

use of novel techniques in data analysis.

A typical ground-based magnetic-field-profile is shown in 

figure 3. Upward continuation of the data illustrates how the 

data would appear if acquired at a height above ground equal to 

the value of upward continuation. High-precision aeromagnetic 

data are commonly acquired at an altitude of 100 m in lowrelief areas and at altitudes of 300 m or more in mountainous 

areas. Most compilations of aeromagnetic data use the highest 

survey as a common denominator so that any surveys flown 

at lower altitudes are upward continued to the height of the 

highest survey, commonly 300 m or more. The large-scale 

features visible in ground-based magnetic-field-profile data are 

lost in airborne data (fig. 3).

The rough appearance of ground-based magnetic-fieldprofile data reflects the heterogeneous distribution of magnetic 

sources and their susceptibilities within the volume of rock 

contributing to the signal acquired by the sensor. Because this 

distribution of magnetic sources is often unique to individual 

lithologies, ground-based magnetic-field-profile data acquired 

over an exposed lithology generally represent the magnetic 

signature of that lithology, at least locally. These data can 

be plotted and compared by using their textural properties 

(physical appearance or characteristics). In addition, nearground magnetic-field-profile data can contain precise 

information on contacts and fault locations and the depth of 

burial of concealed magnetic bedrock.

When a lithology with a distinctive and high-amplitude 

magnetic signature is concealed by nonmagnetic basin fill, 

in some cases the textural properties of that lithology’s 

magnetic signature can be observed and identified through 

the basin fill if the depth of burial is known and not too deep 

(generally less than 100 m), if the magnetic signature of the 

concealed lithology has a high amplitude so that its properties 

are identifiable at depth, and if the magnetic properties of the 

basin fill are negligible. 

Some concealed lithologies can be estimated by matching 

the magnetic signature of the ground-based magnetic-fieldprofile data acquired over shallow basin fill with that of similar 

data acquired over nearby exposed bedrock, called candidate 

lithologies. To match these signatures, the data acquired over 

candidate lithologies are upward continued to the estimated 

depth of burial (generally based on a gravity survey or 

other information) of the concealed bedrock. Magnetic data 

representing just the basin fill (from a deep part of the basin) 

are added to the upward-continued candidate lithology’s data 

if needed. Graphical analysis, statistical analysis, and spectral 
Data Acquisition 3

Figure 3. Data showing the Earth’s total-intensity magnetic field acquired at 3.5-m height above ground 

over exposed bedrock and upward continued by 10, 25, 50, 100 and 300 m to show how the data would look 

if acquired from the air. A height of 300m above ground is common for aeromagnetic surveys.

Ground-based magnetic-field profile

data acquired over exposed bedrock 

Data upward continued 10 m

Data upward continued 25 m

Data upward continued 50 m

Data upward continued 100 m

Data upward continued 300 m

EXPLANATION

Magnetic field, in microteslas

Distance along profile, in meters

48.2

48.0

47.8

47.6

47.4

47.2

47.0

0 200 400 600 800 1000

and multifractal properties of the ground-based magnetic-fieldprofile data are then used to compare the upward-continued 

magnetic signatures of the candidate lithologies with the 

magnetic signal from the concealed bedrock lithology. 

Although a perfectly quantitative match generally does not 

occur, both graphical analysis and the statistical, spectral, and 

multifractal properties of the data each provide information 

that may allow for the elimination of one or more candidate 

lithologies or even uniquely define a concealed lithology. 

Even when this identification is not obtained, the data, in 

combination with knowledge of the local geology, can at least 

allow estimation of a concealed lithology.

Large-scale structural interpretation of near-ground 

magnetic-field-profile data yields much information that is 

not discernible in aeromagnetic data. Even when flown at an 

altitude of 100 m, aeromagnetic data lose the ability to discern 

steep gradients on anomalies, information that is important to 

the understanding of structure in basin bedrock. Because of the 

closely spaced acquisition locations of near-ground magneticfield-profile data and the high information content of these 

data near ground, ground-based magnetic-field-profile data 

contain information that allows estimation of the geometry and 

structure of shallow bedrock with a high degree of precision.

Data Acquisition

The ground-based magnetic-field-profile data used 

here were acquired with a Geometrics G-823A Cs-vapor 

magnetometer mounted approximately 3.5 m above the Earth’s 

surface and 4 m directly behind a four-wheel-drive utility 

vehicle on July 20, 2008. A tripod arrangement of fiberglass 

windsurfer masts were used to suspend the magnetometer 

sensor (fig. 4) off the back of the utility vehicle. All mounting 

hardware was built from fiberglass, polyvinyl chloride, 

aluminum, bronze, or brass. Data were acquired at 10 Hz and 

logged to a computer. The magnetometer was accurate to 

better than 2 nT throughout the range of orientations where a 

signal was strong enough to be acquired. Over most common 

angular orientations of the sensor, the sensor was compensated 

to be accurate within less than 0.5 nT (Geometrics, 1996).

Steel in the utility vehicle contributed to a large anomaly 

from the induced magnetic field due to the vehicle itself. The 

mounting system was designed to move the sensor as far 

away from the vehicle anomaly as practical and to minimize 

sensor movement with respect to the vehicle. Also, several 

neodymium magnets were placed along the rear of the vehicle 

in an attempt to counter the vehicle’s magnetic field. Even 
4 Investigation of the Structure and Lithology of Bedrock Concealed by Basin Fill

with these modifications, however, the interaction of the 

vehicle’s magnetic anomaly with the inclined Earth’s magnetic 

field introduced a large heading correction to the system. This 

heading correction was unique to each region being surveyed, 

as shown in figure 5. The heading correction was treated in 

only two dimensions since no pitch or roll measurements for 

the vehicle were available. Because the data were analyzed 

along relatively short continuous profiles, International 

Geomagnetic Reference Field (IGRF) and diurnal corrections 

were not usually needed. If data are acquired in a region at 

differing time periods, a correction can be applied on the 

basis of leveling. Data were also analyzed as true values, not 

as anomaly values, because the mean values of the Earth’s 

total magnetic field over a given lithology are related to that 

lithology’s magnetic susceptibility and the use of magneticanomaly values removes that information.

Location information was obtained with a Wide-Area 

Augmentation System (WAAS)-enabled Global Positioning 

System (GPS) instrument, generally with an accuracy of 4 m 

or better. GPS information was logged to the computer at 1 Hz 

and used to calculate vehicle heading. The location of the each 

magnetic signal’s data point, recorded at 10 Hz, was interpolated 

from the 1-Hz GPS data. In addition, the utility-vehicle platform is 

capable of acquiring data with a GR-320 gamma-ray spectrometer 

equipped with a 4-L NaI detector crystal (fig. 4). 

Data for the heading correction were based entirely on 

GPS readings. Because this signal can have a short-term 

variance on the order of meters, in a few areas of poor GPS 

reception the interpolated heading data were smoothed through 

a running-mean filter 21 data points long (two GPS readings). 

Owing to the large heading correction for the vehicle (fig. 5), 

straight roads were preferred where possible, and north-south 

Figure 4. Photograph of a truck-mounted magnetometer 

acquiring data on the Earth’s total-intensity magnetic field in the 

San Rafael Valley, southeastern Arizona (see figs., 7 and 8). Roof 

mounted cargo container holds a 4 L Nl crystal that is used with a 

GR-320 gamma ray spectrometer.

routes were preferred, owing to the smaller change in heading 

correction as a function of direction along these roads. Also, 

data from sharp corners (for example, a 90° corner with a 

small radius of curvature) generally were not used because 

GPS data may not accurately reflect the position of the vehicle 

with respect to the Earth’s magnetic field over short timespans, 

owing to the 1-s acquisition rate of the GPS instrument, which 

may be even longer in areas of heavy vegetation. All GPS data 

were inspected to ensure that an anomaly at a corner was not 

due to a heading correction. All the data used in this analysis 

have been heading corrected.

The noise created from movement of the sensor with 

respect to the magnetic anomaly of the vehicle was measured 

by driving the vehicle over a typical unpaved surface in an area 

of a relatively flat magnetic field, here the deep part of the basin 

where the observed amplitudes of magnetic anomalies due to 

geologic features are no larger than 30 nT (fig. 6). This noise 

estimated from sensor movement is the ±~4-nT component of 

the signal visible in figure 6, and no appreciable noise difference 

was observed in the magnetic signal acquired while driving at 

different speeds. Given that most anomalies of interest in groundbased magnetic-field-profile data are hundreds to thousands 

of nanoteslas, this noise is unimportant to the analysis. By 

comparing data acquired over deep basin fill on hills of varying 

aspect and slope, three-dimensional heading corrections due to 

pitch and roll were determined to be negligible. 

Large, narrow excursions in the magnetic field 

(commonly with amplitudes of thousands of nanoteslas) 

were generally from cultural features, such as bridges and 

culverts. Cultural features were determined by matching the 

locations of their large associated magnetic anomalies with 

features determined from aerial photography. The availability 

200

100

0

-100

-200

0 50 100 150 200

Heading, in degrees

Magnetic field, in nanoteslas

250 300 350

Figure 5. Plot showing the heading error for truck-mounted 

magnetometer in the San Rafael Valley, southeastern Arizona. 

Red circles, data obtained at 180° offsets in heading, all in a 

small region with a flat magnetic filed. Curve is a sine wave 

with an amplitude of 260 nT, centered on an azimuth of 003°, 

declination at this site is 10.4°
Estimating Concealed Lithology 5

of aerial-photographic data from online mapping services 

greatly facilitated both acquisition and interpretation of the 

ground-based magnetic-field-profile data. These anomalies 

were removed by hand for quantitative analysis of the signal 

or simply identified if the profile was analyzed qualitatively.

The fast Fourier transform-based spectral interpretation 

and multifractal analyses used in this study both required 

equally spaced intervals in the data. Therefore, in these 

analyses only, the raw data were resampled at a 1-m interval, 

allowing the wavenumber plots used in spectral interpretation 

to have properties that are easily interpreted; that is, the 

wavenumber units are inverse meters. Whenever this 

resampling was done, the resampled data were compared to 

the original data to ensure that the resampled data correctly 

represented the original data.

Estimating Concealed Lithology 

The San Rafael Basin, southeastern Arizona (figs. 7,8), 

was chosen as a study area to demonstrate the benefits of 

ground-based magnetic-field-profile data. The study area 

lies in the porphyry copper and large-deposit mining district 

of southeastern Arizona (Bultman and Drewes, 1996). In 

addition, the San Rafael Basin is bounded by major northwesttrending fault systems that may control the emplacement of 

intrusive bodies responsible for the generation of porphyry 

copper and other ore deposits (Hildenbrand, 2000). Several 

major mineral deposits, including the Red Mountain porphyry 

copper deposit, the Sunnyside Porphyry copper deposit, and 

many other deposits, prospects, and occurrences, mostly 

on the east flanks of the Patagonia Mountains, occur in this 

region (fig 8; Bultman and Drewes, 1996). Mapped bedrock 

surrounding the basin includes intrusive and volcanic rocks 

and a wide variety of potential host rocks, including volcanic 

Distance along profile, in meters

0 50 100 150 200 250

Magnetic field, in microteslas

50.30

50.29

50.28

50.27

50.26

Figure 6. Plot showing truckmounted magnetometer noise 

plotted along profile. At least 

part of high frequency ± ~4-nT 

noise (total magnetic anomaly 

height, ~8 nT) is due to sensor 

movement with respect to files 

of utility vehicle. Data were 

acquired on a typical gravel 

road over deep basin fill, ~20- to 

~30-nT anomalies are due to 

near surface geology.

sedimentary rocks and Paleozoic limestone and dolomite. In 

addition, interpretations of previous ground-based magneticfield-profile data (Bultman and Gettings, 1994; Bultman, 

1999) indicated that the San Rafael Basin is a geologically 

complex and prospective area. Bultman presented a model 

of depth to bedrock in the basin based on gravity data 

obtained from only a few gravity stations. Nonetheless, his 

report indicates that the San Rafael Basin has shallow buried 

pediments along its west and north side. In addition, the basin 

has a good unpaved-road system that allows vehicle access 

to many important localities, including the buried pediment 

on the north and west sides of the basin. The overall depth of 

the central part of the basin, nearly 1 km, is considered to be 

well constrained and is controlled by three deep petroleumexploration wells (Bultman, 1999). 

Basin fill in the San Rafael Basin is not nonmagnetic. 

Ground-based magnetic-field-profile data acquired over deep 

parts of the basin generally display low-amplitude magnetic 

anomalies of ±10–30 nT (fig. 6). On the basin margins, where 

the basin is shallow, the anomalies can be larger, whether 

from basin fill or underlying concealed bedrock. If a lithology 

with a large-amplitude magnetic signal is concealed below 

the basin fill, this amplitude may show through the basin fill, 

provided the concealed lithology is not too deeply buried and 

the signal from the basin fill does not overwhelm that from 

the concealed lithology. Concealed lithologies with smallamplitude magnetic signals are undetectable through basin fill 

and can be eliminated as candidate lithologies when a large 

amplitude signal is observed in ground-based magnetic-fieldprofile data acquired over shallow basin fill.

Estimation of concealed lithology began by acquiring 

ground-based magnetic-field-profile data over basin fill and 

adjacent exposed bedrock in the study area (fig. 7). Data 

acquired over exposed bedrock were used to identify the 

textural properties of the magnetic signal of lithologies that 

may be concealed by basin fill, that is, candidate lithologies. 
6 Investigation of the Structure and Lithology of Bedrock Concealed by Basin Fill

When a candidate lithology has a uniquely describable magnetic 

signal, the signal is referred to as that lithology’s magnetic 

signature. Data acquired over shallow basin fill were used in 

an attempt to identify the bedrock lithology concealed by the 

basin fill at a target site; data acquired over deep basin fill were 

used to estimate the magnetic signal from the basin fill itself. 

Whenever possible, the magnetic properties of different facies 

of exposed basin-fill material were considered, using Landsat 

Thematic Mapper (TM) imagery.

A June 1999 Landsat TM image of the San Rafael 

Basin is shown in figure 9. This ratio image, which works 

well to differentiate lithology, is used here to show how the 

mineralogy of the surface of the basin fill differs from one part 

of the basin to another. This type of image is used to locate a 

possible difference in the magnetic signal from surficial basin 

fill. In the San Rafael Basin, the northeastern margin of the 

basin has a relatively high content of Fe oxides and clays, 

whereas the central part of the surficial basin fill is dominated 

by nonmagnetic high-silica minerals. The target sites where 

Figure 7. Map 

showing the San 

Rafael Basin area, 

southeastern 

Arizona. Red 

shading denotes 

the area of figure8.

concealed lithology were inferred (sites 1, 2a, 2b, fig.9) were 

chosen partly on the basis of the absence of Fe-rich minerals at 

the surface as determined from figure 9, but ultimately depend 

on the locations of the roads used to acquire the data. Site 1 

is along a wash (orange-red area, fig. 9) and may have a high 

Fe oxide mineral content; site 2a (green area, fig. 9) likely 

contains nonmagnetic siliceous surficial material; and site 2b 

(light-yellow-orange area, fig. 9) may include some Fe oxide 

minerals that affect the magnetic signal acquired there. The 

site chosen to represent the basin fill (“QTg-Qg deep basin,” 

fig. 9; and henceforth referred to as “QTg deep basin”) lies 

in silica-rich surface material. From figure 9 it is evident that 

the mineralogy and, thus, the magnetic signature of basin fill 

material, on the basis of surface evidence, varies at each target 

site. Though used only qualitatively, this information helps 

avoid locating target sites in areas where highly magnetic 

basin fill may be present at the surface.

Five candidate lithologies were chosen for this study, 

all of which are exposed at the surface adjacent to the 

0 10 20 30

0

30°30’

32°00’

-111°00’ -110°30’

10 20 30 40

MILES

KILOMETERS

Contour interval is 100 meters.

N 
Estimating Concealed Lithology 7

+ +

QTg-Qg deep basin

Site 1

Site 2a

Site 2b

110°45’ 110°30’

31°30’

0 5 KILOMETERS

N

JTRvs

Kb

PPn

PPn

TKvs 1

2

JTRvs

Kb

PPn

PPn

TKvs 1

2

Saddle 

Mountain Santa Cruz River

110°45’ 110°30’

31°30’

0 5 KILOMETERS

N

Figure 8. Geologic 

map of the San Rafael 

Basin area, southeastern 

Arizona. QTg to Qg, 

basin fill. Diamonds, 

metallic mineral 

deposits, prospects, and 

occurrences. Indicated by 

red numbers are important 

known porphyry copper 

deposits: 1) Red Mountain 

porphyry copper deposit, 

2) Sunnyside porphyry 

copper deposit. Minerals 

data from the U.S. 

Geological Survey (2009), 

geology from Drewes and 

others (2002). Descriptions 

of important map units are 

listed in table 1. 

Figure 9. Image showing 

a Landsat Thematic 

Mapper (TM) image of 

the San Rafael Basin, 

southeastern Arizona in 

June 1999. TM bands 3/1 

in red, TM bands 5/4 in 

green, and TM bands 5/7 

in blue. Reds highlight iron 

oxides, greens highlight 

silica, and blues highlight 

clay minerals. Geologic 

linework, (thin black 

lines) from Drewes and 

others (2002). Site labeled 

“Qtg-Qg deep basin” 

was used to estimate the 

magnetic properties of 

basin fill.
8 Investigation of the Structure and Lithology of Bedrock Concealed by Basin Fill

basin and may represent the 

lithologies concealed by basin 

fill. The locations chosen for 

the acquisition of ground-based 

magnetic-field-profile data 

to represent these candidate 

lithologies are shown in figure 10. 

The candidate lithologies include 

map units that may be related to 

porphyry copper or other types 

of mineralization in the study 

area including Late Cretaceous 

through Eocene intrusive rock 

(map unit TKg, fig. 8; table 1) 

in the Patagonia Mountains, 

Late Cretaceous through Eocene 

volcanic and sedimentary rocks 

(map unit TKvs) to the north of 

the basin, and Late Triassic and 

Jurassic volcanic and sedimentary 

rocks (map unit JTRvs) both east 

and west of the basin. Two map 

units (Kbu, PPn) that might serve 

as mineral-deposit host rocks 

occur in the eastern Patagonia 

Mountains. The magnetic 

signature from the central part 

of the basin (map unit QTg) is 

considered in the analysis of data 

from unknown sites overlying 

shallow basin fill.

Candidate-lithology map unit 

TKg (fig. 8, table 1) occurs west of 

the basin. Although these intrusive 

rocks have numerous phases, 

including some with reversed 

remanent magnetism (Hagstrum, 

1994), a nearly 1-km section in the 

central part appears to be uniform 

in texture and apparently contains 

no reversals (fig.11). Candidatelithology map unit TKvs, which 

occurs north of the basin and 

extends westward as far as Red 

Mountain (fig. 8), also is fairly 

uniform in texture (fig.11) over 

the length of the acquired signal 

that was used for the magnetic 

signature. Candidate-lithology 

map unit Kbu is generally weakly 

magnetic and is insignificant 

as a host rock for replacement 

deposits the study area. Candidatelithology map unit JTRvs (fig. 

11), which is primarily andesitic 

in the area directly east of map 

TKvs

TKg

JTRvs

Kbu

QTg - deep basin

0 200 400 600 800 1,000

PPn

Distance along profile, in meters

50,000

49,500

49,000

48,500

48,000

47,500

47,000

Magnetic field, in microteslas

Figure 11. Plot showing heading corrected magnetic signatures of candidate lithologies 

and deep basin fill in the San Rafael Basin, southeastern Arizona (figs., 7 and 8). See table 1 

for definitions of map units.

Figure 10. Geologic map of the San Rafael Basin, southeast Arizona with basin depth 

contours (contour interval, 0.1 km) based on a gravity model (Bultman, 1999). Red x’s, gravity 

stations. Red lines, locations of ground based magnetic field profile data acquisition for 

candidate lithologies; magenta lines, target sites; brown lines, paths over which profiles 1 

and 2 were acquired. Descriptions of important map units are listed in table 1. Geology from 

Drewes and others (2002). Red circles, exploration wells that did not reach bedrock (Arizona 

Department of Water Resources, 2009) with depths (in feet) indicated.

JTRvs

Kb

PPn

PPn

1

2

JTRvs 

Kb 

PPn 

PPn 

110°45’

31°30’

110°30’

TKg 

TKvs 1 

2 

Saddle

Mountain

Saddle 

Mountain

0 5 KILOMETERS N

Santa Cruz River

TTgg
Estimating Concealed Lithology 9

unit TKg where its magnetic signature was acquired (fig. 10), 

has a high magnetic susceptibility or is underlain by rocks with a 

high magnetic susceptibility. Although the mean of its magnetic 

signature is nearly 2,000 nT higher than those of the others units, 

map unit JTRvs is most distinguished by its high-amplitude 

magnetic anomalies, which may be due to differing magnetic 

susceptibilities or the remanent magnetism of individual flows 

within the unit, or to groups of diorite dikes that occur in the 

study area. Candidate-lithology map unit PPn is locally significant 

for hosting replacement-mineral deposits. Specifically, where 

the ground-based magnetic-field-profile data were acquired, the 

underlying lithology is the Colina Limestone. Roads in the study 

area where this map unit crops out allowed only about 160 m of 

ground-based magnetic-field-profile data to be acquired. 

Three candidate lithologies (map units TKg, TKvs, JTRvs, 

fig. 8; table 1) have magnetic signatures with large amplitudes 

that might be identifiable while concealed under shallow basin 

fill, assuming a very low amplitude magnetic signature of the 

basin fill, similar to the signal from deep basin fill (map unit 

QTg, fig. 11). Map unit Kbu could not be detected under basin 

fill but might be identifiable by the absence of a high-amplitude 

magnetic signal in shallow parts of the basin. Map unit PPn 

has a moderately high amplitude magnetic signature, and its 

texture differs from that of map unit TKg, which has a similarly 

high amplitude magnetic signature but too short a profile to be 

characterized. Because map unit PPn consists of non magnetic 

limestone, its moderate-amplitude magnetic signal may be due 

to alteration and replacement within the limestone.

A gridded aeromagnetic map of the San Rafael Basin 

(fig.12) shows several immediately apparent features, including

a major magnetic high centered near Saddle Mountain (fig. 8) 

and extending eastward, a southeast-trending magnetic low that 

follows the Canelo Hills (fig. 8), and a magnetic high in the 

southern Patagonia Mountains (fig. 8). A northwest-trending 

magnetic low is associated with volcanic rocks in the Canelo 

Hills. If an intrusive body is responsible for the Saddle Mountain 

magnetic high, this feature may extend at depth southward under 

the San Rafael Basin to with about 5 km north of the United 

States-Mexican border. The Red Mountain porphyry copper 

system occurs on a relative magnetic high, and the Sunnyside 

porphyry system lies near the center of a major magnetic low. 

Note that the range of magnetic anomalies is about 450 nT, much 

less than the range of more than 3,000 nT in the ground-based 

magnetic-field-profile data in figure 11 and omitting data from 

the Saddle Mountain high shown in figure 12.

As mentioned above, two target sites in the San Rafael 

Basin have been chosen to demonstrate the magnetic-fieldprofile method for estimating concealed lithology. The first 

target site (1, figs. 10, 12) is in the southwestern part of the 

basin, and the second target site is in the northern part of the 

basin and comprises two subsites (2a, 2b, figs. 10, and 12).

Although large magnetic anomalies are visible in figure 12, 

no textural information, such as that shown in figure 11, 

is available to help differentiate exposed or concealed 

lithologies. Only on the basis of the surrounding geology 

(fig. 10), the concealed lithology at site 1 is assumed to be

map unit JTRvs. The second target site was split into two 

subsites so that the effects of two different depths could be 

observed. The depth to bedrock was estimated to be shallow 

in these areas, approximately 50 m for target sites 1 and 2a 

and at least 100 m for target site 2b (fig. 10). Although the 

gravity-based depth model shown in figure 10 would indicate 

that bedrock is at a depth of 400 m at target site 2b, the 

ground-based magnetic-field-profile has a large-amplitude, 

short-wavelength component at this site that suggests a depth 

nearer to 100 m. Initially, concealed geology was interpreted 

Table 1. Explanation of selected map units. 

[After Drewes (1996) and Drewes and others (2002) except where noted]

Map unit (fig. 8) Explanation

Qg Younger surficial deposits (Pleistocene and Holocene)—Gravel and silt in Alluvial pediments; includes some colluvium and 

soils. Deposits mostly light gray, unindurated, and of poorly rounded and locally derived clasts, except along larger valleycenter rivers. Mostly several meters but as much as 100 m thick.

QTg Gravel, sand, and conglomerate (Miocene through Holocene)—Alluvium filling intermontaine basins, on pediments, in 

alluvial aprons and stream terraces, and along watercourses.

Tg Pyroxene monzonite (after Simons, 1974).

TKg Intrusive rocks (Late Cretaceous through Eocene)—Patagonia diorite, consisting mainly Late Cretaceous through Eocene 

granite, monzonite, granodiorite, and diorite, with some Late Cretaceous through Oligocene peraluminous (two-mica and 

garnet bearing) granite.

TKvs Volcanic and sedimentary rocks (Late Cretaceous through Eocene)—Andesite flows and breccia sheets. Primarily 

trachyandesite north and northwest of the San Rafael Basin.

Kbu Bisbee Formation Group, undifferentiated (Early Cretaceous)—Upper part of the Bisbee Formation or Group, 

undifferentiated, and related rocks, consisting of brownish- to reddish-gray arkose, siltstone, sandstone, conglomerate, and 

some fossiliferous gray limestone. Commonly several hundred meters thick.

JTRvs (or JTRvs) Volcanic and sedimentary rocks (late Triassic and Jurassic)—Rhyolitic welded tuff and lava flows, andesitic lava flows, 

eolian sandstone and red beds.

PPn Naco Group (Pennsylvanian and Early Permian)—Mainly limestone and dolomite; some siltstone, sandstone, and 

marlstone.
10 Investigation of the Structure and Lithology of Bedrock Concealed by Basin Fill

0 5 KILOMETERS

N

110°45’ 110°30’

31°30’ + Profile 2 +

TKg

JTRvs

Kbu

QTg deep basin

Site 2b

Site 2a

TKvs

PPn

Site 1

Profile 1

RM

SP

SM CH

PM

+ Profile 2 +

TKg

JTRvs

Kbu

QTg deep basin

Site 2b

Site 2a

TKvs

PPn

Site 1

Profile 1

RM 

SP 

SM CH

PM

Magnetic anomaly in nT

-252.3 -175.9 -145.7 -124.1 -102.4 -84.8 -71.6 -55.6 -33.3 -2.7 21.6 48.3 176.486.9

Figure 12. Plot showing decorrugated heading corrected magnetic signatures of candidate lithologies and deep basin fill in 

the San Rafael Basin, southeastern Arizona.

to be map unit TKvs at target sites 2a and 2b , owing to the 

proximity of outcrops of map unit TKvs to the north and 

aeromagnetic information from figure 12.

Ground-based magnetic-field-profile data acquired over 

shallow basin fill contain one signal component from the 

basin fill and another from the underlying bedrock lithology 

in some cases. If the amplitude of the signal component 

from the concealed lithology dominates the texture of the 

total magnetic signal acquired over basin fill, the choices 

of potential concealed lithologies from the list of candidate 

lithologies may be narrowed. In addition, any candidate 

lithologies whose magnetic are indistinguishable from 

that of the basin fill (those with very low amplitudes) can 

be eliminated. Graphical analysis, descriptive statistics, 

the power spectrum, and the multifractal spectrum of the 

ground-based magnetic-field-profile data have all been 

shown to contribute information that may help in identifying 

a concealed lithology (Bultman and Gettings, 1994; Bultman, 

1999; Gettings, 1999, 2002, 2008).

Graphical Analysis and Descriptive Statistics of 

Ground-Based Magnetic-Field-Profile Data

In order to compare the magnetic signatures of candidate 

lithologies with the ground-based magnetic-field-profile data 

acquired over basin fill at a target site, both the original data 

and upward-continued (by their estimated depth of burial) 

data from a candidate lithologies were plotted to allow visual 

comparison of the mean and the textural properties of the 

magnetic signal. If the mean of the magnetic signature of a 

candidate lithology and the magnetic signal from a target site 

drastically differ, the candidate lithology under consideration 

may not be the concealed lithology, although statistical 

mean values can be highly influenced by rock at depth. If the 

magnetic anomalies from a target site’s magnetic signal are 

higher in amplitude than the magnetic signal from a candidate 

lithology, that candidate lithology can be eliminated as a 

concealed lithology because upward continuation will always 

reduce the heights of magnetic anomalies. 
Estimating Concealed Lithology 11

Textural measures, such as the number of peaks per 

kilometer, can also be compared. Upward continuation will 

always reduce the number of peaks per kilometer (it is a 

low-pass filter), and so that information can be included in the 

analysis. Although this qualitative analysis helps with initial 

estimates of concealed lithology, these descriptive statistics 

provide a more quantitative basis for comparison.

Descriptive statistics are used to quantitatively characterize 

the magnetic signatures of candidate lithologies and the 

magnetic signal from a target site, in an attempt to quantify 

the appearance or texture of the data with several measures 

that can then be compared. Useful measures include (1) the 

number of peaks per distance along the profile (p/x), (2) the 

Euclidean vector signal length (V) over distance along the 

profile (V/x), (3) the mean peak height (MPH), (4) the mean 

peak half-width (MPHW), (5) the signal variance, (6) the signal 

range, and (7) the signal mean (Bultman and Gettings, 1994; 

Bultman, 1999; Gettings, 1999, 2002, 2008). In this analysis, 

the number of peaks was calculated by using a routine that 

selects anomalies with a minimum signal height and width in 

order for a magnetic-signal component to be designated as a 

peak. Unless otherwise noted, those values are 10 nT and 5 m, 

respectively; they characterize the high-frequency components 

that are included in ground-based magnetic-field-profile data yet 

are large enough that most system noise is discarded. 

The Euclidean vector signal length of ground-based 

magnetic-field-profile data is defined as

V = i{(Bi – Bi+1)

2

 + (xi – xi+1)

2

}1⁄2, (1)

where B is the Earth’s total-intensity magnetic field (in 

nanoteslas) at an observation point and x is the distance (in 

kilometers) from the start of signal from which this point was 

observed. Thus, the units of V are the square root of the sum of 

nanoteslas squared plus kilometers squared ( nT2 + km2 ).

Candidate lithologies with high-amplitude magnetic 

signals display large values of MPH, p/x, V/x, and signal 

variance and range. The signal mean, which can be a 

reflection of the magnetic susceptibility of each map unit, 

can be important to distinguish both exposed and concealed 

lithologies, but as mentioned above, the signal mean can 

also depend on the magnetic susceptibility of underlying 

materials, and so care must be taken when this statistic is 

used. In some cases, these statistics can uniquely define 

candidate lithologies, but the statistics change drastically when 

a lithology is concealed by basin fill, primarily owing to the 

depth of concealment but also to the addition of the magnetic 

signal due to the basin fill. 

The descriptive statistics for each of the candidate 

lithologies used in this study differ significantly (table 2). 

The magnetic signatures derived from lithologies with highamplitude magnetic anomalies include map units TKg, TKvs, 

and JTRvs (table 1), all of which have high values of MPH, p/x, 

V/x, and signal variance and range and so are referred to as 

high-amplitude candidate lithologies. Map unit Kb is generally 

less magnetic than the other lithologies and has low values of 

MPH, p/x, and signal variance and range. Map unit PPn, which 

has a short signal length due to small exposure in outcrop, and 

moderate values of MPH, p/x, V/x, and signal variance and 

range, consists primarily of limestone but is altered and hosts 

mineral deposits in the area where the data were acquired, 

and so the magnetic signal from this lithology may be due to 

alteration and replacement. 

The MPHW value is nonlinearly related to the depth of 

burial of the magnetic sources. If the sources are dipping sheets, 

however, the MPHW value is strongly correlated to the depth of 

the sources, indicating that they are shallow except in the basin 

fill. The signal from the deep basin fill, which was obtained in 

an area with nearly 1,000 m of basin fill (fig. 10), shows very 

low values of MPH, p/x, V/x, and signal variance and range and 

a moderate to high mean. The high mean for this profile may 

indicate high-susceptibility bedrock concealed at depth.

The less magnetic lithologies and the basin fill tend to have 

much broader magnetic anomalies, indicating that the anomalies 

are coming from a greater depth than those of the high-amplitude 

lithologies. The value of the variable p, the number of peaks, which 

is a function of signal length and characteristics, is included to 

indicate that the mean and other values derived from p could be 

misleading for signals acquired over short distances. 

Table 2 also shows how these statistics change when 

candidate lithologies are upward continued. Upward 

continuation is a low-pass filter, and so much of the information 

content in a signal is removed after upward continuation. 

Because these statistics are greatly changed, they generally are 

useless for identification of a concealed lithology, although they 

may provide boundary conditions for such an estimation. When 

a lithology is concealed, the values of MPH, p/x, V/x and signal 

variance and signal range will always be less than those obtained 

when the lithology is exposed at the surface. The MPHW value 

will generally increase when lithology is upward continued, 

and the signal mean will change little and should be considered 

constant. The mean is not listed in table 2 because with these 

short profiles its value after continuation is strongly affected by 

what is happening at the tails of the profile. 

The Power Spectrum of Ground-Based 

Magnetic-Field-Profile Data

In addition to the statistics described above, the power 

spectrum of ground-based magnetic-field-profile data was used 

to characterize the magnetic signature of a candidate lithology 

of a target site. For a given profile, the power spectrum 

provides a plot of the portion of a signal’s power (energy per 

unit distance) for a given wavenumber, calculated by using 

the discrete Fourier transform, which requires that the signal 

be equally spaced and spatially stationary (no trends). Equal 

spacing was accomplished by interpolating the data to a 1-m 

interval, which preserved the signal shape in all cases and 

allowed these spectra to be presented with wavenumber units 

of inverse meters (m-1). All spectra were equally smoothed 
12 Investigation of the Structure and Lithology of Bedrock Concealed by Basin Fill

with a Daniell filter (Bloomfield, 2000) with window widths 

of length 5 and 3. The smoothing, which is similar to a 

running mean, removes excessive noise from the power 

spectra without changing their shape. 

The ground-based data were acquired at 10 Hz, andso

driving at a maximum speed of 72 km/h (20 m/s, ~45 mi/h) 

produces a sampling interval of 2 m. The speed of the vehicle 

while acquiring data was kept to 72 km/h or less in allcases.

In general, speeds are kept to less than 50 km/h (~14 m/s, 

1.4-m sampling interval, ~30 mi/h). Choosing a cutoff 

wavelength of 4m is therefore reasonable, which means that

the power spectrum for wavenumbers greater than about 0.25 

is ambiguous. 

The power spectra for the five candidate lithologies and 

the deep basin fill are plotted in figure 13. In general, the 

high-amplitude magnetic signatures display the highest power 

Table 2. Descriptive statistics for candidate lithologies and deep basin fill.

[See table 1 for description of map units, and text for description of target sites; x = Distance (in kilometers) along ground-based magnetic-field-profile; p = Number 

of peaks in ground-based magnetic-field-profile data; V = Euclidean length of ground-based magnetic-field-profile signal (in nT2 + km2 ); B = Earth’s total-intensitymagnetic-field data acquired as ground-based magnetic-field-profile data; MPH = Mean anomaly peak height (in nanoteslas); MPHW = Mean peak half-width (peak 

to trough) (in meters); * The mean of upward-continued data depends on the tails of the upward-continued data and has little meaning for these short profiles; Peak 

designation was based on a minimum amplitude of 10 nT and a minimum width of 5 m; Some upward-continued data were omitted because for some lithologies the 

upward-continued data become too smooth to find peaks; For “deep basin,” 5 nT and 3 m were used for peak height and minimum width, respectively, owing to the 

low amplitude of the signal.; Target site 2a data smoothed with running mean 5 due to much high-frequency noise—andesite; For target sites 1, 2a, and 2b, minimum 

peak height=35 nT, and minimum peak half-width =20 m (removes much of signal from basin fill.)]

Map unit or target site p

x

(km)

p/x

(per km)

V/x

( /km)

MPH

(nT)

MPHW

(m)

Stan. Dev. B

(nT)

Range B

(nT)

Mean B

(nT)

Qg, QTg 4 0.717 7.0 6.1E+04 16 146 9.3 35 47,314

TKg 24 0.920 27 1.7E+06 71 17 63.9 296 47,492

TKg up continued 25m 5 0.920 6.6 1.5E+05 36 90 25.7 97 *

TKg up continued 50m 3 0.920 4.4 6.6E+04 24 144 14.2 53 *

TKvs 23 1.150 20 4.8E+06 225 20 193.6 1099 47,584

TKvs up cont. 25m 4 1.150 4.3 6.0E+05 149 276 139.9 527 *

TKvs up cont. 50m 4 1.150 2.6 4.1E+05 185 231 116.3 457 *

Kbu 5 0.556 11 3.7E+05 35 33 93.8 287 47,203

JTRvs 15 1.047 15 2.1E+07 572 31 478.7 2278 48,906

JTRvs up cont. 25m 5 1.047 5.8 2.1E+06 385 121 299.7 1043 *

JTRvs up cont. 50m 4 1.047 4.8 1.1E+06 243 156 218.0 639 *

JTRvs up cont. 100m 2 1.047 2.9 4.5E+05 206 294 132.4 367 *

PPn 1,2 6 0.157 44 1.2E+06 71 15 31.5 130 47,164

Site 1 (~50m depth to bedrock) 5 0.894 6.7 1.3E+06 212 85 93.1 424 48,803

Site 2a (~50m depth to bedrock) 7 0.796 10 6.7E+06 149 32 67.6 401 50,496

Site 2b (~100+m depth to bedrock) 8 1.397 6.4 6.8e+05 129 105 64.9 307 49,273

1

The location data for map unit PPn were smoothed by a running-mean filter of length 21 sample points for heading correction due to poor GPS reception. The 

road representation was good. 

2

The short length of this profile prevented upward continuation of map unit PPn.

throughout their spectra. Map unit JTRvs displays the most 

power at all wavenumbers but less power with decreasing 

wavenumber relative to the other map units. Map unit TKvs has 

a higher power than map unit TKg at low wavenumbers, and a 

similar power at high wavenumbers. Map unit Kbu has a low 

power at all wavenumbers, and the highly nonmagnetic basin fill 

has less than a hundredth of the power at very low wavenumbers 

and less than a thousandth of the power at higher wavenumbers. 

In addition, the shape of these spectra at low wavenumbers is 

nonlinear, indicating that power-law scaling may be useful in 

describing the texture or characteristics of the ground-based 

magnetic-field-profile data. The shape of these spectra of the 

magnetic signature of each candidate lithology and the relations 

between spectra will help distinguish lithologies concealed at 

depth by nonmagnetic basin fill, again by establishing boundary 

conditions for each candidate lithology. 

nT2 +km2
Estimating Concealed Lithology 13

The power spectrum for a candidate lithology (here, map 

unit TKvs) when the acquired signal is upward continued is 

plotted in figure 14. The upward-continued spectra rapidly 

decrease in power at all wavenumbers, and rapidly increase in 

slope at very low wavenumbers. The low-pass-filter feature of 

the upward-continuation process creates spectra of lower power 

and with power concentrated in long-wavelength anomalies. 

From these observations, any concealed lithology must have a 

power spectrum that is lower in power at all wavenumbers than 

its candidate lithology. Although the spectrum for map unit 

TKvs upward continued 10 m shows a lower power than that 

for map unit TKvs upward continued 25 m at wavenumbers 

in the vicinity of 0.28, this change occurs beyond the cutoff 

wavenumber of 0.25. On the basis of figure 13, power added 

to the signal from basin fill will be insignificant because this 

power is generally less than a thousandth of the power from a 

high-amplitude candidate lithology.

The Multifractal Spectrum of Ground-Based 

Magnetic-Field-Profile Data

The fractal dimension of a signal, which describes howthat

signal fills the space that it occupies, is characterized by 

noninteger dimensions. Multifractal objects display a differing 

fractal dimension, depending on differing scaling exponents 

(Feder,1989). Multifractal analysis therefore provides information 

on the spectrum of fractal dimensions required to characterize 

how a multifractal object fills the space that it occupies. 

Multifractal scaling has been demonstrated in many 

geologic processes, including porosity measurements derived 

from neutron density logs; borehole resistivity; density and 

natural gamma-ray borehole logs; magnetic susceptibility 

from borehole logs (Pilkington and Todoeschuck, 1993); 

aeromagnetic-field-profiles (Pilkington and Todoeschuck, 

1993); the distribution of faults, fractures, and joints; the 

TKg

TKvs

JTRvs

Kb

PPn

QTg

Power, in decibels

Wavenumber, in inverse meters

0

1e+05

1e+02

1e-01

1e-04

0.05 0.10 0.15 0.20 0.25 0.30 0.35

Figure 13. Plot showing power 

spectra of candidate lithologies 

and deep basin fill in the San 

Rafael Basin, southeastern 

Arizona.

TKvs ground - based magnetic - field - profile data

TKvs upward continued 10 m

TKvs upward continued 25 m

TKvs upward continued 100 m

TKvs upward continued 50 m 

Power, in decibels

Wavenumber, in inverse meters

0 0.05

1e+06

1e+03

1e+00

1e-03

1e-06

0.10 0.15 0.20 0.25 0.30 0.35

Figure 14. Plot showing power 

spectrum of map unit TKvs, 

upward continued 10, 25, 50, and 

100 m.
14 Investigation of the Structure and Lithology of Bedrock Concealed by Basin Fill

sizes and spatial distribution of ore deposits; the topographic 

shape of the Earth’s surface; and closely spaced Earth’s totalintensity-magnetic-field data (Gettings and Bultman, 1997). 

Several workers (Pilkington and Todoeschuck, 1993; Lovejoy 

and others, 2001; Pecknold and others, 2001; Gettings, 1995, 

2004, 2005, 2006) have shown that magnetic-susceptibility 

distributions in drillhole logs exhibit multifractal behavior. 

Gettings (2005) constructed a physical fracture-diffusion 

model that explains the multifractal distribution of the 

magnetic susceptibilities of hydrothermally altered rocks. 

Lovejoy and others (2001) and Pecknold and others (2001) 

showed that anisotropic multifractal distributions describe the 

three-dimensional distribution of magnetization within the 

Earth. The spatial distribution of lithology has been modeled 

with fractals (Maus and Dimri, 1996; Dolan and others, 1998). 

Multifractal models thus provide a natural way to describe the 

distribution of magnetic sources in the Earth’s crust.

A multifractal can be considered as an assemblage of 

independent monofractals, each with its own dimension. A 

multifractal distribution can be determined from box counting 

as follows. A set consisting of NT points distributed in space 

will have N(d)i points in the ith box, the size of the box being 

defined by the box side length d. The product d • N(d)i defines 

a measure of the set N. Then mi denotes the relative weight 

(probability) of the measure within the ith box with respect to 

the total number of points in the set NT :

 

 (2)

A q measure can be defined as (Feder, 1988; Falconer, 1990; 

Berkowitz and Hadad, 1997):

 (3)

where d=t(q) and

 (4)

Mq is finite and nonzero only if d=t(q); therefore (Berkowitz 

and Hadad, 1997),

 (5)

The mass exponents t(q), which control how the moments of 

the probabilities (m) scale with differing d, can be estimated 

from equation 5 by plotting log(1/d) versus log (N(q, d)) for 

each q value:

 (6)

If the plot is reasonably linear, t(q) is the estimated linear 

slope of the plotted points.

The Lipschitz-Holder exponent a defines the scaling of 

probabilities (m1) as a function of box size (d1) for the ith box 

(Feder, 1988):

for 

 (7)

where a1 represents the fractal dimension for the ith box and 

can vary from place to place. The number of boxes required to 

cover a subset in the range between a and a+da is defined by 

(Feder, 1988; Berkowitz and Hadad, 1997):

 (8)

where (a) da denotes the number of subsets between a and 

a+da and f 9 a and f(a) represents the fractal dimension of 

each of the a1 subsets. 

From equation 3, the q measure of the complete set can 

be defined as follows (Feder, 1988; Falconer, 1990; Berkowitz 

and Hadad, 1997)

 (9)

The solution to equation 9 by the steepest-descent method 

in the limit of small d yields (Feder, 1988; Falconer, 1990; 

Berkowitz and Hadad, 1997):

 

 (10)

where = f '(a(q))=q and where Mq is finite if:

 (11)

Equation 11 is valid for every q, and so its derivative with 

respect to q is:

 

 (12)

Equations 11 and 12, the Legendre transform, define f (a) 

once t(q) is known. t(q) is obtained from equation 6, and 

f(a) is referred to as the singularity spectrum or multifractal 

spectrum.

The f(a) curve achieves its maximum value at f (a(q=0)). 

This point, which is the most probable singularity subset, 

describes the fractal dimension of the geometric support of the 

multifractal set (Feder, 1988). Because all minerals have some 

magnetic susceptibility, a support dimension of 1.0 is observed 

in ground-based magnetic-field-profile data. The f(a) curve 

equals zero at the two extremes of a, amax and amin, which are 

related to q approaching negative infinity and positive infinity, 

respectively. For many real-world variables, these values may 

not be calculable, depending on the type of data, but may be 

approximated from the shape of the f(a) curve. Multifractals 

with a large amax- a min are commonly said to have more 

strength than multifractals with a smaller amax- a minn. A point 

known as the measure concentrate (Berkowitz and Hadad, 

1997) occurs at f (a (q=1)), where f(a)=a and f (a)=1.

N(δ)i

NT

μi = .

N (q, δ) = ∑ . Ν(δ)

i = 1 μq

 i

Mq = . N(q,δ) • δτ(q) limδ→0

log N(q, δ) = log Mq + τ (q)• log ( ) . 1

δ

∫ lim

δ→0

∞

α = 0

Mq ∝ . dα • δ qα+τ(q)− f(α)

f(α) = α • q +τ(q).

α = τ(q). –d

dq

Mq = = N(q,δ)δd→{ , 0, d > τ (q)

∞, d > τ (q) ∑ μ lim

δ→0

Ν(δ)

i = 1

q

i δ di

inf

δi < δ

μi ∝ δ α for i > 0, ai

i

N(α,δ) = ρ(α) dα , • δ− f(α)

Mq = , δ [α•q+τ(q)−f(α)] limδ→0
Caveats in the Estimation of Concealed Lithology 15

The multifractal spectra of the magnetic signature from 

each of the candidate lithologies, calculated by using box 

counting based on the Legendre transform in FRACLAB 

(Lévy-Véhel and Legrand, 2004), are plotted in figure 15. 

These spectra demonstrate that the multifractal spectrum can 

differentiate the magnetic signatures of exposed lithologies on 

the basis of ground-based magnetic-field-profile data. Each 

candidate lithology and the basin fill have a unique multifractal 

spectrum that is distinguishable by the a location of f(a)=1, 

the width of the spectrum in a (amax- a min, its strength), and the 

general shape of the spectrum (symmetrical, right or left skew).

Map unit JTRvs has the lowest value (0.72) at f(a)=1; 

its spectrum is also much weaker than those of the other 

map units and is slightly right skewed. Map unit TKvs is 

differentiated from the others by a=0.81 at f (a)=1, by its 

strength, and by its symmetrical form. Map unit TKg is 

differentiated from the other candidate lithologies by its 

spectrum reaching the support dimension f(a)=1 at a =0.78 

and by its spectrum being weaker than that of map unit TKvs 

and only slightly stronger than that of map unit JTRvs. The 

rest of the spectra can be similarly discriminated. None of 

these spectra extends to f(a)=0, simply because no data are 

available at very large (q<0) and very small (q<0) box sizes to 

calculate these values.

The effect of upward continuation on the multifractal 

spectrum of ground-based magnetic-field-profile data is shown 

in figure 16 for map unit TKvs. Upward continuation tends to 

change the multifractal spectrum in two ways. First, increases 

for f nonlinearly and the position of the entire curve moves to 

the right. Second, the left side (left of f(a)=1) of the spectrum 

is increasingly removed with increasing upward continuation. 

Both of these changes result from to the loss of information 

in the magnetic-field profile associated with low-pass filtering 

due to upward continuation. 

In equation 2, m1 denotes the relative weight (probability) 

of the measure within the ith box with respect to the total 

number of points in the set NT. In addition, equation 4 shows 

that t(q) depends on mq

i

 and that the value of f(a) depends 

on t(q). The net effect of these relations means that the farleft-hand side of the f(a)-versus-a curve (where q→+∞) 

emphasizes boxes with more information. Because upward 

continuation acts as a smoothing filter on ground-based 

magnetic-field-profile data, removing more information from 

the signal with increasing upward continuation, t(q) and, thus, 

f(a) become incalculable for signals with very low information 

content and high q values. Also, as information is lost, the 

rest of the multifractal spectrum steepens to the left of the 

point where f(a)=1, becoming weaker and less singular with 

increasing upward continuation. The shape of the right-hand 

parts of the spectrum, to the right of where f(a)=1, is nearly 

unchanged but is offset by the offset value of a at f(a)=1.

These changes in the multifractal spectrum with upward 

continuation have important implications for the estimation of 

concealed lithology. Owing to the loss of information content of 

the signal with upward continuation, the multifractal spectrum 

of a concealed lithology should tend to lose the far-left-hand 

side of the spectrum. The magnitude of this effect depends on the 

amplitude of the anomalies in the magnetic-field profile from the 

concealed lithology, which is also related to the depth of burial 

and requires a nonmagnetic basin fill. Therefore, if a lithology 

concealed by basin fill has a significant left-hand side of the 

multifractal spectrum visible, then this part of the spectrum may 

contain information from magnetic basin fill. The upper part 

and right-hand side of the multifractal spectrum best represent 

the concealed lithology upward continued to the depth of burial. 

Also, the relative positioning of the spectrum is important. If the 

right-hand side of the multifractal spectrum from a concealed 

lithology falls to the left of the right-hand side of the multifractal 

spectrum from a candidate lithology, then that candidate lithology 

can be eliminated from contention as the concealed lithology. 

Examples of these types of interpretation of the multifractal 

spectrum are given below in the real-world analysis of concealed 

lithologies.

Caveats in the Estimation of Concealed 

Lithology

Several potential problems contribute to the inability of the 

textural measures to consistently predict concealed lithology. The 

objective is to detect a magnetic signal from bedrock concealed 

by (nearly) nonmagnetic basin fill and to use the properties of 

that signal to determine the specific concealed lithology which 

generated it. The concealed lithology is chosen from several 

candidate lithologies that are possible geologic map units which 

may be concealed by basin fill on the basis of local geology, but 

the concealed lithology may not be a candidate lithology but 

some lithology that does not crop out in the region. In addition, 

U.S. geologic maps are based on a time-stratigraphic mapping 

TKg

JTRvs

Kbu

PPn

TKvs

QTg

0.4

1.0

0.8

0.6

0.4

0.2

0.6 0.8 1.0 1.2 1.4

f(α)

α

Figure 15. Plot showing multifractal spectra of ground-based 

magnetic-field-profile data acquired over exposed bedrock 

lithologies.
16 Investigation of the Structure and Lithology of Bedrock Concealed by Basin Fill

system, whereby map units may contain more than one 

lithology, and so we need to understand the relations between 

map units and their inclusive lithologies in the study area. Once 

an area within a map unit is chosen as a candidate lithology, 

data is acquired over that area to define the magnetic signature 

of that candidate lithology. For instance, map unit JTRvs, to the 

east of the Patagonia Diorite (map unit TKg, fig. 8), is extremely 

magnetic; it likely contains several andesitic flows of varying 

composition, but in figure 11 it seems to display consistent 

textural properties over the area used to define its magnetic 

signature. In the Canelo Hills (figure 10), to the northeast of the 

basin, map unit JTRvs is predominantly siliceous tuff and has 

different magnetic properties displaying a much lower mean and 

low-amplitude anomalies.

magnetic signature of the three high-amplitude candidate 

lithologies, map units JTRvs, TKg, and TKvs. From this plot, 

map unit JTRvs is likely the concealed geology for several 

reasons. First, the high mean of the concealed signal nearly 

matches the mean of map unit JTRvs. Although this similarity 

could be due to an unknown high-magnetic-susceptibility 

lithology at depth, the mean almost exactly matches that of 

nearby exposed map unit JTRvs. Second, as shown in figure17, 

the amplitudes of the magnetic anomalies at target site 1 are 

too large to be from map unit TKvs or TKg, considering that 

the magnetic signal from the candidate lithology must be 

upward continued by 50 m for comparison. Both the 25-mand 50-m-upward-continued signals from map units TKvs 

TKvs

1.0

0.8

0.6

0.4

0.2

0.5 1.0 1.5

TKvsupward continued 10 m

TKvs upward continued 50 m

TKvsupward continued 25 m

f(α)

α

Figure 16. Plot showing multifractal spectrum of ground-based magneticfield-profile data acquired over exposed bedrock lithology (map unit TKvs) 

and upward continued 10, 25, and 50 m.

TKg upward continued 

50 m dashed, 

upward continued

25 m dotted 

TKvs

JTRvs

Site 1

Distance along profile, in meters

0

50.0

49.5

49.0

49.0

48.5

48.0

47.5

200 400 600 800

Magnetic field, in microteslas

Figure 17. Plot showing ground-based magnetic-field-profile data over the 

three high-amplitude candidate lithologies, and upward continued 50 and 25 

m, and over basin fill at site 1.

The signal from bedrock acquired over basin 

fill also depends extremely on its depth of burial. 

As discussed above, the properties of this signal, 

including its power spectrum and its multifractal 

spectrum, vary greatly with depth of burial. An 

incorrect depth determination will cause problems 

when determining concealed lithology. In addition, 

many bedrock surfaces under basin fill are not 

perfectly level but display considerable relief, 

indicating that the bedrock surface over which the 

concealed lithology was acquired likely has differing 

depths of burial. Generally, this consideration cannot 

be taken into account without a detailed depth profile 

for the target site.

In aeromagnetic surveys, Cenozoic basin fill in 

the Southwestern United States is generally assumed 

to be nonmagnetic or very nearly nonmagnetic, but 

not for ground-based magnetic-field-profile data. As 

the TM data analysis has already shown, the surface 

composition of basin fill can vary significantly within 

a basin. Also, analysis of data from the target sites 

discussed below demonstrates that the magnetic 

properties of the basin fill are considerable in at least 

some places.

Estimation of Concealed Lithology at 

Target Site 1

Ground-based magnetic-field-profile data 

acquired over the basin fill at target site 1 were 

acquired just to the east of the basin-bedrock contact 

with map unit JTRvs (fig. 10). The depth of basin fill 

in this area is less than 100 m and was estimated 

at 50 m on the basis of the depth contours in figure 

10. The bedrock-basin contact is exposed in a 

stream valley just west of the basin (fig. 2). The 

underlying map unit JTRvs (andesite at this site) 

probably continues into the basin for some distance 

eastward, at least until a high-angle basin-margin 

fault occurs. The signal acquired over basin fill at 

target site 1 is plotted in figure 17, along with the 
Caveats in the Estimation of Concealed Lithology 17

and TKg have magnetic anomalies that are much too shallow 

and broad to match the magnetic signal from target site 1. On 

the basis of figure 17, map unit JTRvs is the only choice, but 

given the complexity of estimating concealed lithology, it is 

prudent to check all lines of evidence. Note how important 

simply plotting all the data is in the estimation of a concealed 

lithology. The plots summarize the descriptive statistics and 

allow textures to be easily differentiated.

The descriptive statistics for ground-based magneticfield-profile data acquired at target site 1 (and 2a and 2b) are 

listed in table 2. For the concealed target sites listed in table 2, 

the calculation of MPH values uses a minimum peak height of 

35 nT and peak half-width of 20 m, eliminating the influence 

of basin-fill magnetic anomalies (shown in fig. 6), which 

generally are less than 35 nT, at least in the central part of the 

basin. The descriptive statistics for target site 1 are compared 

with the descriptive statistics of the candidate lithologies 

upward continued by 50 m, the approximate depth of burial 

of bedrock at target site 1. From table 2, several descriptive 

statistics point to map unit JTRvs being the concealed lithology, 

including the values of MPH, V/x, and mean B. On the basis 

of MPH values, the closest candidate lithology is map unit 

JTRvs, and even for that lithology the MPH value at target 

site 1 is less than would be expected from map unit JTRvs 

upward-continued 50 m (table 1), indicating that either the 

magnetic anomaly for map unit JTRvs is less at target site 1 

than measured on the exposed lithology, or that depth of burial 

is more than 50 m. Only map unit JTRvs has upward-continued 

V/x values that could be comparable to those at target site 1; 

all other candidate lithologies have V/x values that are too 

small after upward continuation. As shown in the graphical 

analysis, the mean value at the target site most closely matches 

that of map unit JTRvs. The values of signal range and standard 

deviation listed in table 2 indicate that the candidate lithology 

is either is map unit JTRvs or TKvs but is more likely map unit 

JTRvs. MPHW and p/x values from table 2 are not of much use. 

MPHW values in the upward-continued data become too large, 

owing to the smoothing effect of upward continuation. At target 

site 1, the MPHW values must contain some information from 

basin fill that tends to make them smaller. Although the data 

were filtered to remove information from magnetic anomalies 

with an MPH value of less than 35 nT and an MPHW value 

of less than 20 m, the MPHW values of the upward-continued 

candidate lithologies are larger than 20 m. Likewise, the basin 

fill probably tends to make p/x values higher at the target sites 

than for the upward-continued candidate lithologies.

The power spectrum from the ground-based magnetic-fieldprofile data acquired at target site 1 shows lower power at all 

wavenumbers only when compared with the power spectrum of 

map unit JTRvs, making this map unit the likely concealed lithology 

(fig. 18). The power spectra of the upward-continued candidate 

lithologies display much less power than that for target site 1, 

indicating significant contributions to the magnetic signal from 

basin fill at all wavenumbers but especially those greater than 0.01.

The multifractal spectrum from the ground-based 

magnetic-field-profile data acquired at target site 1 is compared 

with the multifractal spectra from the three high-amplitude 

candidate lithologies in figure 19. In figure 16, upward 

continuation tends to move the multifractal spectrum to 

larger values and removes data points from the left side of the 

spectrum, and so a signal from a concealed lithology should 

display these same properties. In figure 19, the left-hand side of 

1e+05

1e+02

1e-01

1e-04

1e-07

0.05 0.10 0.15 0.20 0.25 0.30 0.35

Power, in decibels

Wavenumber, in inverse meters

TKg - upward continued 50 m dashed, upward continued 25 m dotted

TKvs - upward continued 50 m dashed, upward continued 25 m dotted

JTRvs - upward continued 50 m dashed, upward continued 25 m dotted

Site 1

Figure 18. Plot 

showing power 

spectra of target 

site 1 and three 

high-amplitude 

candidate 

lithologies, and 

upward continued 

25 and 50 m.
18 Investigation of the Structure and Lithology of Bedrock Concealed by Basin Fill

the multifractal spectrum from target site 1 is unaffected by the 

loss of information from upward continuation, as shown in the 

spectra in figure 16. The left-hand side of figure 1 is probably 

influenced by magnetic basin fill, and so this basin fill must 

be responsible for the left side of the spectrum at target site 

1. Results seen in the power spectrum of target site 1 could 

also indicate that the power spectrum is being influenced by 

magnetic basin fill. Target site 1 lies near a wash that was 

likely to have a high concentration of Fe oxide minerals at the 

surface (fig. 9). Because the left-hand side of the multifractal 

spectrum is influenced by the basin fill here, the best way 

to use the multifractal spectrum to help estimate concealed 

lithology is to compare the location of the spectrum in as well 

as the shape of the top and right side of the spectrum. Here, 

the right side of the spectrum is most similar to the upwardcontinued spectrum of map unit JTRvs, contributing to the 

evidence that the concealed lithology is, indeed, this map unit. 

On the basis of the above analysis, the logical candidate for 

the concealed lithology at target site 1 is map unit JTRvs. After 

the initial analysis described above, the magnetic signal from deep 

basin fill was added to those of the upward-continued candidate 

lithologies and reanalyzed for target site 1, but no significant 

change was observed in the descriptive statistics or spectra. Many 

of the descriptive statistics, as well as the power spectrum and 

the multifractal spectrum, indicate a large input to the magnetic 

signal from the basin fill at target site 1, indicating a bigger Earth’s 

magnetic-field component due to basin fill at target site 1 than the 

contribution estimated from deep basin fill in the center of the basin.

Structural Analysis near Target Site 1

The heading-corrected ground-based magnetic-fieldprofile data acquired over profile 1 (fig. 10) are plotted in figure 

20, including data from target site 1. The first 7 km of these 

data displays several regular magnetic anomalies that tend to 

increase in amplitude from about 2.1 to 4.5 km along the profile 

(“High-amplitude section,” in fig. 20). After km 7, several very 

large anomalies likely indicate some major structural features. 

upward continued

50 m dashed,

upward continued

25 m dotted 

TKg

JTRvs

Site 1

TKvs

f(α)

α

0.4

1.0

0.8

0.6

0.4

0.2

0.6 0.8 1.0 1.2 1.4 1.6

Target site 1

High-amplitude section

Anomaly from Santa 

Cruz River bridge

Anomalies from cattle guards, etc. 

Distance along profile, in meters

Magnetic field, in microteslas

50.5

50.0

49.5

49.0

48.5

48.0

0 2,000 4,000 6,000 8,000 10,000 12,000

Figure 19. Plot showing 

multifractal spectra of groundbased magnetic-field-profile data 

acquired over candidate lithologies, 

and upward continued 25 and 50 m, 

and at target site 1.

Figure 20. Plot showing groundbased magnetic-field-profile data 

acquired over basin fill along profile 1.
Caveats in the Estimation of Concealed Lithology 19

The data from profile 1 were modeled in two dimensions, 

using the program GM-SYS, and the results are plotted in figure 

21. The sudden change in profile direction at 7 km changes 

the shape and amplitude of anomalies in the model because 

the profile is based on how geologic units interact with the 

Earth’s magnetic field in the direction of the profile. Thus, the 

geometry of the model is only approximate after km 7. On the 

basis of the interpretation of target site 1, the concealed bedrock 

present there is map unit JTRvs. Although no measurements 

of magnetic susceptibility are available for this map unit, it is 

arbitrarily assigned a relatively high magnetic susceptibility 

of 0.008 cgs unit, owing to its high observed mean value (fig. 

11), which is not unreasonable for andesite (Clark, 1997) and 

could also be considered an apparent susceptibility. That is, 

the susceptibility used in the model is somewhat high because 

it includes the remanent magnetism of the rock. Andesites 

can have high Koenigsberger ratios, the ratio of remanent 

to induced magnetic intensity (Clark, 1997). Assuming 

the remanent magnetization is of the same polarity as the 

Earth’s current magnetic field and that the declination and 

inclination of the remanent magnetism do not greatly differ 

from the current declination and inclination, the remanent 

magnetism would increase the overall magnetism of the rock. 

According to both Simons (1974) and Drewes and others 

(2002), the flow bedding in this andesite dips to the east or 

southeast. The magnetic anomalies present from km 1 to km 

7 along the profile can be modeled as higher susceptibility 

(0.017 cgs unit) flows or other dipping planar features in the 

bedrock under about 80 m of basin fill. Note that the area 

of high-amplitude magnetic anomalies (“High amplitude 

section,” figs. 20, 21) which is shown in both figures 20 and 

21 can be modeled with similar flows at shallower depth 

(approx 30-40 m). Beyond km 7, major basin faults and a 

very high susceptibility (0.025 cgs unit) rock are needed to 

model the data, but note that the geometry of these features 

is only approximate, owing to changing profile direction. 

The 0.025-cgs-unit material could be highly altered andesite 

or other alteration affiliated with an intrusive body. Rocks 

with such high magnetic susceptibilities occur in the Saddle 

Mountain region to the north of the basin. Basin faults lower 

the basin depth at km 12 along the profile to 400 m, which is 

shallower than the 600 m defined in the gravity-based depth 

model shown in figure 10. However, this model has few data 

points in the region, and the basin is deepening rapidly to the 

north at this point, and so this model is not unreasonable. To 

match the depth of the gravity-based model here, very high 

susceptibility (~0.050 cgs unit) material would be needed.

Estimation of Concealed Lithology at Target 

Sites 2a and 2b

Target site 2 occurs in the northern part of the San Rafael 

Basin south of the large outcrop of map unit TKvs. In this 

area, map unit TKvs probably continues southward under the 

basin fill. This target site was split into two subsites, 2a and 

2b, to test the effects of increasing depth on the estimate of 

concealed geology. The depth model is based on data from 

only a few gravity stations, and although the general geometry 

and overall depth of the model are good, the exact geometry of 

the basin margin at large scales can differ considerably from 

that in the model shown in figure 10, as is often the case when 

trying to estimate concealed lithology. Especially at target site 

2b, the depth is only approximate because the site sits on a 

steep gradient with few gravity stations. 

JTRvs JTRvs

0.008

0.025

Flows/dikes 0.017

QTg 0.000001

Magnetic data and model results

for geologic model below

Target site 1

High-amplitude section

? ? ?

? ? ?

? ? ? Altered or high

susceptibility

rock 

0.025

Depth, in kilometers0.08

0.16

0.24

0.31

0.00

0.40

50.0

49.0

Magnetic field, in microteslas

0.0 3.0 6.0 9.0 12.0

V.E. = 11.92

Distance along profile, in kilometers 

Figure 21. Figures showing 

profile1, how ground-based 

magnetic-field-profile data 

provide detailed geologic model of 

concealed lithology and bedrock 

geometry.
20 Investigation of the Structure and Lithology of Bedrock Concealed by Basin Fill

Target site 2a is in a narrow neck of basin fill (fig. 10) 

that extends to the north of the main basin. The gravity model 

indicates that the basin fill in this area is less than 100 m thick. 

The entire neck area is surrounded by map unit TKvs, which 

here is composed of trachyandesite. The acquisition area for 

the magnetic signature of map unit TKvs lies just to the west 

(fig. 10). Saddle Mountain (fig. 8), at the northwest corner of 

the basin neck, was mapped as unit Tg (table 1) by Drewes 

(1996), but Simons (1974) was somewhat more specific and 

mapped this feature as Cretaceous pyroxene monzonite with 

two included volcanic necks. Drewes’ geologic map was 

influenced by more recent radiometric ages in the area, and he 

listed the age of the intrusive body as younger than map unit 

TKg (table1). This intrusive body is extremely magnetic, and 

ground-based magnetic-field-profile data acquired near it have 

heading-corrected values of more than 52,000 nT. Groundbased magnetic-field-profile data on the outcrop of this map unit 

were unobtainable, owing to property access and terrain. 

Target site 2b is about 2 km to the south of target site 2a 

(fig. 10), where the bedrock depth is supposedly near 400m.

As mentioned above, this depth estimate is based on data from 

only a few gravity stations (fig. 10) over a steep gradient and 

is likely to be incorrect. On the basis of textures visible in 

ground-based magnetic-field-profile data, bedrock in this area 

is probably not so deep and is likely more than 100 m but less 

than 150 m deep. Most short-wavelength (<50 m) textural 

information from bedrock disappears at depths greater than 

150m, even for concealed lithologies with very high magnitude

anomalies, such as map unit JTRvs. Three deep exploration 

wells were drilled in the basin in the 1970s (Arizona 

Department of Water Resources, 2009; red dots, fig.10), one

of which is only about 1.5 km southeast of target site 2b and 

reached 2,004 feet (611 m) deep without penetrating bedrock. 

On the basis of this information, a very steep increase in 

bedrock depth probably occurs south of target site 2b. The 

bedrock “canyon” seen on the northwest side of the basin in 

figure 10 and trending northwest is probably not real because 

it is based on data from only two gravity stations (fig. 10) and 

has depth contours extending into the exposed bedrock. On 

the basis of the 2,004-ft-deep well and another 1,893-ft (577 

m) deep well (fig. 10), which also did not penetrate bedrock, 

the bedrock depth gradient in the western and northern parts of 

the basin is steeper than that shown in the gravity-based model 

(fig.10). Owing to the textures in the ground-based magneticfield-profile data, a shallow margin occurs on the north side of 

the basin that includes target site 2b.

The ground-based magnetic-field-profile data acquired 

at target sites 2a and 2b are plotted in figure 22 along with 

the magnetic signatures of the high-amplitude candidate 

lithologies. Although the concealed lithology at both sites is 

believed to be map unit TKvs on the basis of the proximity 

of outcrop to the north, the means of the data at target sites 

2a and 2b are much higher than that of map unit TKvs. The 

magnetic signal at target site 2a is probably influenced by or 

derived from the pyroxene monzonite of Saddle Mountain 

that must extend at depth southward at least to this area. 

TKg

TKvs

JTRvs

Target site 2a

Target site 2b

upward continued 50 m dashed, 

upward continued 25 m dotted

0

50.5

50.0

49.5

49.0

48.5

48.0

47.5

200 400 600 800

Distance along profile, in meters

Magnetic field, in microteslas Figure 22. Plot showing ground-based magnetic-filed-profile data from target sites 2a and 2b, plotted with 

magnetic signatures of three high-amplitude candidate lithologies, with upward-continued data at 25 and 50 m.
Caveats in the Estimation of Concealed Lithology 21

Target site 2b is 2 km farther south, and although the mean 

is high, it is nearly identical to that of map unit JTRvs. The 

textures at both target site 2a and 2b are most similar to that 

of map unit JTRvs, especially given that target site 2b is 

concealed by at least 100 m of basin fill.

From the descriptive statistics in table 2, the mean B

value is what stands out most at target sites 2a and 2b. Target 

site 2b has a mean B value similar to that of map unit JTRvs, 

only about 370 nT higher, but target site 2a has a mean B value 

of about 50,500 nT, a full 1,600 nT higher. As indicated above, 

this difference is likely due to the presence of the pyroxene 

monzonite of Saddle Mountain at depth. At both target sites 2a 

and 2b, the p/x and V/x values would tend to indicate that map 

unit JTRvs is the concealed lithology, whereas the MPH value 

would tend to indicate map unit TKvs. Again, the MPHW, 

signal range of B, and standard deviation of B are not of much 

help. Because the depth at target site 2b is probably greater 

than 100 m, map unit JTRvs is the only candidate lithology 

that could cause the mean peak height, standard deviation, and 

signal range observed at target site 2b.

The power spectra of target sites 2a and 2b is plotted in 

figure 23 along with the power spectra from the three highamplitude candidate lithologies. From wavenumbers 0.08 to 

0.12, both target sites 2a and 2b have more power than map 

unit TKvs. These wavenumber represent anomaly wavelengths 

of 8.3 to 12.5 m, and the power from these anomalies may be 

contributed by basin fill. Nonetheless, a contribution to power 

at anywhere near the magnitude needed is not observed in that 

part of the spectrum from basin fill in the central part of the 

basin (fig. 13). The spectrum from target site 2a also has more 

power than map unit TKg at wavenumbers near 0.17 to 0.19, 

indicating that the power spectrum is probably not produced 

by map unit TKg.

The multifractal spectra from target sites 2a and 2b and 

the high-amplitude candidate lithologies is plotted in figure 

24. For both target sites 2a and 2b, there appears to be little 

contribution to the spectra from basin fill; that is, the left-hand 

sides of the spectra are missing. The top and right-hand side 

of the multifractal spectrum from target site 2b mimics the 

right-hand side of the upward-continued spectrum from map 

unit JTRvs. The multifractal spectrum from target site 2a shows 

no resemblance to any upward-continued spectra. Because this 

spectrum lies to the left of the multifractal spectrum of exposed 

map unit TKvs, it cannot be derived from map unit TKvs.

On the basis of the analysis of ground-based magneticfield-profile data from target sites 2a and 2b, the concealed 

lithology at target site 2a cannot be identified. Neither 

descriptive statistics, power spectra, nor multifractal spectra 

help uniquely identify a concealed lithology. The magnetic 

signal acquired at target site 2a is probably due to the 

pyroxene monzonite of Saddle Mountain. This interpretation 

would explain the high mean of the magnetic signal from 

that site, as well as the absence of any textural match to the 

candidate lithologies.

Target site 2b has a mean, MPH, signal range, and 

standard deviation that most resemble those of map unit JTRvs 

concealed by 100 m or more of basin fill. In addition, both the 

power spectrum and multifractal spectrum provide evidence 

that supports the conclusion that map unit JTRvs underlies 

basin fill at this site.

1e+05

1e+02

1e-01

1e-04

1e-07

0.05 0.10 0.15 0.20 0.25 0.30 0.35

Power, in decibels

Wavenumber, in inverse meters

TKg - upward continued 50 m dashed, upward continued 25 m dotted

TKvs - upward continued 50 m dashed, upward continued 25 m dotted

JTRvs - upward continued 50 m dashed, upward continued 25 m dotted

Target site 2a

Target site 2b

Figure 23. Plot showing power spectra for target sites 2a and 2b and three high-amplitude candidate 

lithologies, (and upward continued 25 and 50 m).
22 Investigation of the Structure and Lithology of Bedrock Concealed by Basin Fill

Modeling Bedrock Structure over a 

Potential Mineral-Resource Target 

The ground-based magnetic-field-profile data acquired 

from northeast to southwest along profile 2 (fig. 10) are plotted 

in figure 25. The bearing used for heading correction was 210°

true, the average bearing along the profile. Although some 

turns are evident in this profile, they all have a large radius of 

curvature, and the data appear to have been properly corrected. 

From the gravity-based depth model, the basin is shallow 

here, about 100 m. Eight gravity stations were added in the 

vicinity of this profile to help control model depth in this area. 

A relatively shallow depth seems to be confirmed by the high 

amplitude of magnetic anomalies and by the texture visible 

in the ground-based magnetic-field-profile data in figure 25. 

One obvious feature is bounded on the northeast side by the 

Dove Canyon Fault. This magnetic anomaly is formed by two 

nearly symmetrical highs, one of which is more than 1,000 nT, 

separated by a central low and bounded by even-lower values 

of the Earth’s total-intensity magnetic field to the southwest. 

Porphyry copper deposits commonly appear as magnetic 

highs with alteration halos generally manifested as surrounding 

annular magnetic lows (Berger and others, 2008). The central 

high is commonly due to potassic alteration, which often 

includes magnetite. The annular low is due to destruction of 

magnetite within the surrounding propolytic- and phyllicalteration zones; however, magnetic susceptibility varies 

N Sw

Dove Canyon Fault

Distance along profile, in meters

0 1000 2000 3000 4000 5000

Magnetic field, in microteslas

49.6

49.4

49.2

49.0

48.8

48.6

48.4

Figure 25. Plot 

showing headingcorrected groundbased magneticfield-profile data 

for profile 2.

1.0

0.8

0.6

0.4

0.2

0.4 0.6 0.8 1.0 1.2 1.4 1.6

f(α)

α

TKg - upward continued 50 m dashed, upward continued 25 m dotted

TKvs - upward continued 50 m dashed, upward continued 25 m dotted

JTRvs - upward continued 50 m dashed, upward continued 25 m dotted

Target site 2a

Target site 2b

Figure 24. Plot 

showing multifractal 

spectra of ground-based 

magnetic-field-profile 

data acquired over 

candidate lithologies, 

(and upward continued 

25 and 50 m) and from 

target sites 2a and 2b.
Conclusions 23

significantly throughout the altered rock in porphyry systems 

(Gettings, 2005). Whether owing to this variation or to the 

absence of a strong central potassic-alteration zone, some 

porphyry systems can display a central magnetic low and have 

been referred to as nonmagnetic porphyries (Clark and others, 

1992). The nearby Sunnyside porphyry copper system, (area2,

fig. 8; SP, fig. 12) has no known associated central magnetic 

high. The magnetic anomaly shown in figure 25 is due either to 

a nonmagnetic porphyry system or to a porphyry system where 

the potassic-alteration zone has been weathered from the top of 

the porphyritic stock responsible for the system, leaving only 

high-magnetic-susceptibility potassic alteration on its margins. 

The best aeromagnetic data from the study area are 

shown as a decorrugated grid in figure 12. Although a slight 

magnetic high is visible in profile 2 (where it is intersected 

by the northeasterly green line whose intersection indicates 

the northeastern most magnetic high in fig. 25), it is by no 

means as prominent or distinguishing a feature as the same 

anomaly in the ground-based magnetometer data, owing to 

the location of the aeromagnetic-survey line and the altitude 

of the survey (nearly 300 m here). The survey lines near the 

anomaly happen to be a little more widely spaced in this area 

than the overall 1/3-mi spacing of the survey as a whole. 

The southwestern magnetic anomaly in figure 25 (800 nT 

in the ground-based data) is almost invisible in figure 12 

(southwestern green line intersecting profile 2). 

The ground-based magnetic-field-profile data from 

profile 2 are plotted in figure 26. In this area, map unit JTRvs 

is composed of siliceous tuff and has much different magnetic 

properties than near the Patagonia Mountains. The magnetic 

anomaly has been modeled here as if it is caused by a 

porphyry copper system in which potassic alteration has been 

eroded from the top of the system and remains only adjacent 

to the intrusive stock that formed the system. The system was 

then buried by Cenozoic sedimentary deposits. 

Conclusions

Ground-based magnetic-field-profile data acquired with 

a truck-mounted Cs-vapor magnetometer can complement 

aeromagnetic data in studies of the geometry, structure, 

and lithology of bedrock concealed by basin fill. Although 

aeromagnetic data are useful at smaller scales (tens to hundreds 

of kilometers), ground-based magnetic-field-profile data are most 

useful at scales of hundreds to thousands of meters. They provides 

high-resolution data of the Earth’s total-intensity magnetic field 

acquired near the ground and at closely spaced locations, which 

?

?

Ksv ? TKg

JT vs R

0.0008

0.0002

QTg 0.000001

0.002

Magnetic data and model results

for geologic model below

Dove 

Canyon 

Fault

0.005 0.010 0.015 0.007 0.014 0.000005 NE SW

F lows or dikes

Ksv ?

Alteration/skarn

Depth, in kilometers

0

0.08

0.16

0.24

0.32

0.40

0.48

49.6

49.2

48.8

48.4

Magnetic field, in microteslas

0 1.0 2.0 3.0 4.0 5.0

Vertical exaggeration = 4.1 Distance along profile, in kilometers

Figure 26.
24 Investigation of the Structure and Lithology of Bedrock Concealed by Basin Fill

are needed for precise structural modeling and for the large-scale 

estimation of concealed lithology in some cases.

Estimation of concealed lithology is based on four 

methods: graphical analysis, descriptive statistics, and 

analysis of both the power spectra and multifractal spectra 

of the ground-based magnetic-field-profile data. Estimation 

is not quantitative but uses information from these four 

methods to remove some potential candidate lithologies 

from consideration and possibly to deduce a concealed 

lithology. Graphical analysis provides information on 

the mean value of the magnetic field and the ability to 

visually compare the textural properties of the exposed 

and concealed lithologies. Descriptive statistics provide 

quantitative evidence for characterizing the textural 

properties of the data that can be compared between exposed 

and concealed lithologies. The descriptive statistic of the 

mean of B is important, as well as the values of MPH, p/x

and V/x. Standard deviation of B, range of B, and MPHW 

value are not particularly effective at discriminating 

concealed lithology, probably owing to the influence of the 

magnetic signal from basin fill. 

The power spectra of ground-based magnetic-fieldprofile data provide boundary conditions that can also 

be used to eliminate potential concealed lithologies 

from consideration. In general, the power spectrum 

of the magnetic signal from an upward-continued 

candidate lithology must always display less power at all 

wavenumbers than the power spectrum of the magnetic 

signal from a target site where that candidate lithology 

is buried. Otherwise, that candidate lithology can be 

eliminated from consideration as a concealed lithology. 

The power spectrum from the deep basin fill in the San 

Rafael Basin has a hundredth to a thousandth of the power 

at all wavenumbers of the power spectra of any of the 

candidate lithologies. Therefore, adding the magnetic 

signal from basin fill acquired in the central part of the 

basin to the magnetic signal from upward-continued 

candidate lithologies did not affect any comparisons of 

power spectra. However, at the target sites that are near the 

basin-fill/bedrock contact, more of a contribution to the 

total magnetic signal from basin fill certainly occurs than if 

the composition of the basin fill was identical to that in the 

central part of the basin.

I propose here that the multifractal spectrum of 

ground-based magnetic-field-profile data can be used for 

estimating concealed lithology by matching the right side 

of the spectrum (for a>f (a)=1)for the upward-continued 

(by estimated depth of burial) magnetic signal from the 

estimated concealed lithology and the magnetic signal from 

the target site. Although more research needed, this method 

does seem to work for target sites in the San Raphael Basin 

and has a logical basis. At target site 1, a well-constrained 

area with a concealed lithology with a very high magnetic 

amplitude, the method does help determine the concealed 

lithology. At target site 2b, which is deeper and where 

the depth is less constrained, the method also provides 

information as to what lithology might be concealed. At 

target site 2a, the multifractal spectrum does not point to any 

candidate lithology being concealed but does help determine 

what lithology is not concealed.

Ground-based magnetic-field-profile data are extremely 

important in understanding the geometry and structure 

of basin margins at scales of hundreds to thousands of 

meters. Such data allow for precise models that help in 

depth determination, basin structural evaluation, and 

target assessment that are impossible to construct by 

using aeromagnetic data. Given the benefits of estimating 

concealed lithology and of precision modeling of basinmargin geometry and structure, acquisition and analysis 

of ground-based magnetic-field-profile data becomes an 

extremely important component in the understanding of 

concealed mineral resources in the Basin and Range, as well 

as in many other regions.

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Manuscript approved for publication, February 26, 2013

Edited by George Havach

Design and layout by Jeanne S. DiLeo
Bultman—Investigation of the Structure and Lithology of Bedrock Concealed by Basin Fill—Scientific Investigations Report 2013–5038