gamma ray logs

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radioactivity with increased shale content is apparent. At the high radioactivity

extreme are organic-rich shales and potash (KCl). These plotted values can

include beta as well as gamma radioactivity (collected with a Geiger counter).

Modern techniques concentrate on gamma ray detection.

Fig. 1 – Distribution of relative radioactivity level for

various rock types (from Bigelow after Russell ).

Radioactive isotopes in rocks

The primary radioactive isotopes in rocks are potassium-40 and the isotope

series associated with the disintegration of uranium and thorium. Fig. 2

shows the equilibrium distribution of energy levels associated with each of

these groups. Potassium-40 (K ) produces a single gamma ray of energy of

1.46 MeV as it transforms into stable calcium. On the other hand, both

thorium (Th) and uranium (U) break down to form a sequence of radioactive

daughter products. Subsequent breakdown of these unstable isotopes

[2] [1]

40

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produces a variety of energy levels. Standard gamma ray tools measure a

very broad band of energy including all the primary peaks as well as lower-

energy daughter peaks. As might be expected from Fig. 2, the total count

can be dominated by the low-energy decay radiation.

Fig. 2 – Gamma-ray energy levels resulting from

disintegration of unstable isotopes (adapted from Tittman

et al . ).

The radionuclides, including radium, may become more mobile in formation

waters found in oil fields. Typically, the greater the ionic strength (salinity),

the higher the radium content. Produced waters can have slightly higher

radioactivity than background. In addition, the radionuclides are often

concentrated in the solid deposits (scale) formed in oilfield equipment. When

enclosed in flow equipment (pipes, tanks, etc.) this elevated concentration is

not important. However, health risks may occur when equipment is cleaned

for reuse or old equipment is put to different application.

[3]









Table 1 lists some of the common rock types and their typical content of

potassium, uranium, and thorium.

Potassium is an abundant element, so the radioactive K is widely

distributed (Table 2). Potassium, feldspars and micas are common

components in igneous and metamorphic rocks. Immature sandstones can

retain an abundance of these components. In addition, potassium is common

in clays. Under extreme evaporitic conditions, KCl (sylvite) will be deposited

and result in very high radioactivity levels. Uranium and thorium, on the other

hand, are much less common. Both U and Th are found in clays (by

absorption), volcanic ashes, and heavy minerals.

Table 1

40









Table 2

History of gamma ray tools

The gamma ray tool was the first nuclear log to come into service, around

1930 (see Fig. 3). Gamma ray logs are used primarily to distinguish clean,

potentially productive intervals from probable unproductive shale intervals. The

measurement is used to locate shale beds and quantify shale volume. Clay

minerals are formed from the decomposition of igneous rock. Because clay

minerals have large cation exchange capacities, they permanently retain aportion of the radioactive minerals present in trace amounts in their parent

igneous micas and feldspars. Thus, shales are usually more radioactive than

sedimentary rocks. The movement of water through formations can

complicate this simple model. Radioactive salts (particularly uranium salts)

dissolved in the water can precipitate out in a porous formation, making

otherwise clean sands appear radioactive.









Fig. 3 – A timeline of nuclear logging highlights the

introduction and evolution of commercial nuclear-logging

measurements.

Gamma ray logging tool

Before getting into how to use the log readings, let us consider the workings

of the tool. Unlike all other nuclear tools (and, in fact, all other logging

measurements), it is completely passive. It emits no radiation. Instead, it

simply detects incoming gamma rays from the formation and (unfortunately)the borehole. Gamma rays are electromagnetic radiation, generally in the

energy range 0.1 to 100 MeV. As light, this would correspond to very short

wavelengths indeed. The difference between gamma rays and X-rays is largely

semantic because they overlap in energy.

Originally, the detector was a Geiger-Müeller tube, just as in the Geiger

counter. More recently, the detectors have been switched to solid-state









scintillation crystals such as NaI. When a gamma ray strikes such a crystal,

it may be absorbed. If it is, the crystal produces a flash of light. This light is

"seen" by a photomultiplier staring into the end of the crystal. The

photomultiplier shapes the light into an electrical pulse that is counted by the

tool. Hence, like all nuclear tools, the raw measured quantity in a gamma ray

log is counts. This means that the precision of gamma ray log measurements

is determined by Poisson statistics. The precision is the square root of the

total number of counts recorded at a given depth. Counts recorded are

basically proportional to the volume of the detector crystal times its density

(which determine the probability that a gamma ray will be captured within the

crystal) times the length of time counted. As with all nuclear-logging

measurements, the only part of this that the logger controls is the counting

time. Because log measurements are depth driven, the length of time the

logger counts is inversely proportional to the logging speed.

Historically, gamma ray sondes have recorded the total flux of gamma

radiation integrated over all energies emanating from a formation as a single

count rate, the gamma ray curve. Logging tools are not uniform in their energy

sensitivity. No detector responds to all the gamma rays that impinge on it.

Many pass through with no effect. The sizes of a detector, the solid angle it

subtends, and its thickness, as well as its composition (particularly its

density), all affect its efficiency for detecting gamma rays. The tool housing

around the detector, the casing, and even the density of the borehole fluid can

all filter the gamma rays coming from the formation. All these factors not only

lower the overall tool efficiency, they also lead to variations in efficiency for

gamma rays of different energies. In short, the count rate recorded in a

particular radioactive shale bed is not a unique property of the shale. It is a

complex function of tool design and borehole conditions as well as the actual

formation’s radioactivity.







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Common scale

Even though gamma ray readings are generally used only in a relative sense,

with reservoir (clean) and shale values determined in situ, there are

advantages to a common scale. In the US and most places outside the

former Soviet Union, gamma ray logs are scaled in American Petroleum

Institute (API) units. This harkens back to a desire to compare logs from tools

of different designs. Tools with different detector sizes and compositions willnot have the same efficiency and thus will not give the same count rate even

in the same hole over the same interval. To provide a common scale, API built

a calibration facility at the U. of Houston. It consists of a concrete-filled pit, 4

ft in diameter, with three 8-ft beds penetrated by a 5 1/2-in. hole cased with

17-lbm casing. The top and bottom beds are composed of extremely-low-

radioactivity concrete. The middle bed was made approximately twice as

radioactive as a typical midcontinent US shale, resulting in the zone

containing 13 ppm uranium, 24 ppm thorium, and 4% potassium. The gamma

ray API unit is defined as 1/200 of the difference between the count rate

recorded by a logging tool in the middle of the radioactive bed and that

recorded in the middle of the nonradioactive bed.

While it has served fairly well for more than 40 years, this is a poor way to

define a fundamental unit. Different combinations of isotopes, tool designs,

and hole conditions may give the same count rate, so the calibration does not

transfer very far from the calibration-pit conditions. In contrast, Russiangamma ray logs are typically scaled in microroentgens (μR)/hr, which does

correspond to a specific amount of radiation. Converting this to API units is a

bit vaguely defined, but it is often suggested that the conversion factor is 1

μR/hr = 10 API units for Geiger tube detectors, but 15 μR/hr = 10 API for

scintillation detectors. This falls in with the previous discussion of the many

factors that can affect gamma ray readings. The problem is further aggravated







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in logging-while-drilling (LWD) measurements. The API unit provides a degree

of standardization, but despite the best efforts of tool designers, one cannot

expect tools of different designs to read exactly the same under all

conditions. Fortunately, none of this is very important because gamma ray

measurements are generally used only in a relative way.

Factors affecting readings

Because we use gamma ray logs as relative measures, precise calibration is

not very important except as a visual log display feature. Environmental

effects are much more important. Consider a radioactive volume of rock

traversed by a borehole. Nuclear physics tells us that gamma rays are

absorbed as they pass through the formation. For typical formations, this

limits the depth of investigation to approximately 18 in. Considering only the

geometry, the count rate opposite a given rock type will be much lower in a

larger borehole in which the detector is effectively farther from the source ofgamma rays. In an open hole, borehole size almost always has the greatest

effect on the count-rate calibration. This problem can go well beyond changes

in bit size. Especially if shales or sands are selectively washed out, borehole

size can imprint itself of the expected gamma ray contrast between shales

and sands. If the borehole is large enough, the density of the fluid filling the

borehole can also impact the calibration by absorbing some of the gamma

rays before they get to the tool.

Barite in the mud is another complication, filtering the incoming gamma rays.

Thus, the gamma ray borehole size and fluid corrections are often very

important and should be made if at all possible. Obviously, casing absorbs a

large fraction of the gamma rays traversing it on their way to the borehole, so

if the tool is run in a cased hole, casing corrections are very important. Tool

design has a large impact on environmental corrections. The housing and





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location of the detectors all filter the incoming gamma rays. It is important to

use the right environmental corrections for the tool being run. This is

especially true for LWD tools that may consist of multiple detectors

embedded in large, heavy drill collars that filter the incoming gamma rays in

unique ways.

Interpreting gamma ray logs

Log analysis

Now that we know how the tools work, we are ready to discuss how gamma

ray logs are used in log analysis. While the gamma ray log traditionally has

been used primarily for well-to-well correlation, it also plays a role in

quantitative log analysis. As mentioned at the outset, gamma ray logs are

used primarily to define and quantify productive intervals. As discussed, above

there are only three naturally occurring radioactive elements-potassium,

uranium, and thorium (or K, U, and Th by their elemental symbols)—and all of

these tend to be associated with shales, not clean matrix minerals (e.g.,

quartz sand, SiO , limestone CaCO ).

The most common interpretation method is the simple bulk linear mixing law

presented previously.

....................(1)

Even though we know that the distribution of clays in shales and reservoir

rocks is quite complex, to first order, log analysts frequently simplify the

linear bulk mixing law to the determination of shale volume:

....................(2)

2 3





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Standard log analysis separates the log-analysis problem into a series of

sequential, independent steps. Because shale-volume determination is

usually the first step in the sequential process of formation evaluation from

logs, porosity and fluid volumes are not yet known. As a result, the equation

is further simplified to

....................(3)

Adding closure,

....................(4)

leads to the familiar formula for calculating shale volume from a borehole-

corrected gamma ray log:

....................(5)

where the "c lean" terms represent the lumped response to the matrix grains

and the fluids in the porosity. Further complications arise because the shale

values are taken from overlying shale beds. The clays distributed in the

reservoir rock are almost certainly not simply dispersed versions of the

shales, unless they occur as thin laminations. At the very least, there will bedifferences between shale, made up of clay minerals, c lay bound water, and

silt-size particles, and the clay minerals alone distributed in the matrix.

Worse, because of differences in the processes at work when the shales

were laid down vs. the shaly sands, the clay minerals in the sands may not

be the same as those in the matrix. To compensate for this, numerous

nonlinear relationships have been proposed. These have geologically












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significant-sounding names like Larinov older rocks but are simply empirical

and have no physical basis. They are used to improve the correlation

between gamma ray-derived shale volumes and other estimates of the shale

volume, especially from core. The equations all start with the linear gamma

ray index discussed above and reduce the intermediate values from there.

Fig. 4 lists a few of the more common equations. Fig. 5 illustrates the degree

of shale reduction that the various models afford. If one of these models must

be used, select the one that best fits other available estimates of clay volume.

Fig. 4 – A summary of various nonlinear shale-volume

models used to reduce the amount of shale below thelinear, bulk mixing-law prediction.

[4]







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Fig. 5 – Illustration of the amount of shale reduction

predicted by various nonlinear shale-volume models

listed in Fig 4.

One disadvantage of the various empirical, nonlinear models is that they

generally require core data for calibration or at least justification. This is a

generic problem with more complex models; they require more parameters to

characterize them. To set or calibrate those parameters in turn requires more

independent log or core measurements.

It is also assumed that the clean reservoir material (the sum of the pore fluids

and matrix minerals) has a fixed amount of radiation associated with it. As

long as the gamma ray reading associated with the clean reservoir material is

small compared to the shales, this assumption is safe. As the sands become

hotter (more radioactive), lumping the fluids and matrix together becomes

problematic, particularly if the porosity is large.

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Precision

Consider briefly some details of how a standard, gross-count-rate gamma ray

tool works. Most modern tools (in nuclear logging, "modern" means within the

past 25 years) use a solid-state scintillator crystal (most often sodium iodide,

NaI) to detect gamma rays. When a gamma ray strikes the crystal, there is

some probability that it will be captured. That probability is mostly

proportional to the size and density of the crystal. If it is captured, it gives offa flash of light. A photomultiplier mounted on one end of the crystal converts

that light to an electrical pulse, which is then fed to an electronic pulse

counter. To measure a count rate with a given precision in the laboratory, one

counts until enough counts are registered to give the desired level of precision

(see the discussion of counting statistics above). Then, one divides that

number of counts by the time it took to get that many to obtain a count rate.

Unfortunately, in a logging tool, all measurements are depth-based. To

measure a count rate, the tool counts for the length of time it takes the tool tomove 1/2 ft (or whatever the depth increment is), then divides by the length of

time it took the tool to move that distance. This means that the precision of a

nuclear-logging measurement in a given lithology is proportional to one over

the square root of the logging speed. Remember that the number of counts

received crossing a clean 1/2 ft will be much less than the number when

crossing a shaly 1/2 ft.

Environmental distortion

The simple consideration of the discussion of radiation transport helps clarify

which environmental effects most seriously distort the gamma ray log.

Imagine what happens as borehole size increases. There is less of the

radiating radioactive material near the detector, and the measured count rate

goes down, even though the actual level of radioactivity in the formation

remains the same Further imagine the rather typical case in which the





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remains the same. Further imagine the rather typical case in which the

shales are eroded and broken out while the sands remain in gauge. This

would suppress the apparent gamma ray count rate in the eroded shales

much more than in the sands, suppressing the gamma ray contrast between

eroded shales and sands. This is typically one of the largest environmental

effects on the gamma ray count rate. Again from the discussion of radiation

transport, heavier materials in the path that the gamma rays must follow from

the formation through the detector will absorb more gamma rays than lighter

materials (as will be seen in a later section, this is the basis for the bulk

density log, but that is another story and a different log). Worse yet, barite is

a big absorber of gamma rays. The lesson to carry away is that borehole size

and fluid corrections are almost always important when running the gamma

ray log.

Gamma ray interactions with formations

Gamma rays interact with formations in three different ways:

Compton scattering

Photoelectric absorption

Pair production (to a limited extent)

One of these will dominate depending on the energy of the gamma ray, as

Fig. 6 shows.







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....................(6)

where Z is the average atomic number of the formation. The attenuation law

for gamma ray intensity falloff is then

....................(7)

For Compton scattering to be a true measure of bulk density, ρ , Z / A must be

a constant. For almost all formation elements, Z / A = 1/2, and a measurement

of gamma ray attenuation in the 1- to 10-MeV range can indeed be calibrated

to bulk density. The notable exception is hydrogen, for which Z / A =1. Table 1

lists some density values for comparison.

Table 1

b











Photoelectric (PE) absorption

Not surprisingly, the PE log is based on the photoelectric absorption of

gamma rays, the scattering process that dominates at low energy. In this

process, the incoming gamma ray is absorbed by an atomic electron, giving

up all its energy to the electron in the process. If the gamma ray is energetic

enough, the added energy causes the electron to break free from its atom. As

another electron falls into the vacancy, a characteristic X-ray, generally less

than 100 keV, is emitted. These X-rays are too low in energy to contribute to

logging measurements.

The PE cross section falls off very strongly as the energy of the incoming

gamma ray increases. The cross section is proportional to

....................(8)

It is a significant factor in gamma ray scattering only for energies less than

100 keV. This means that it is easy to separate the effects of PE absorption

from those of Compton scattering by simply windowing the energies of the

gamma rays detected. The same tool can make both measurements

simultaneously. By examining the falloff of low-energy gamma ray flux, a

logging tool can be calibrated to measure the PE factor (PEF). The PEF, in

turn, is primarily sensitive to the average atomic number, Z , of the formation.

Because hydrocarbons and water have very low Z values, they contribute very

little to the average PE of a formation. Conversely, because the major rock

matrices have very different Z s, the PE factor is a nearly porosity-independent

lithology indicator.








primarily by formation material electron density and Compton scattering. This




p y y y p g

limits the depth of investigation to around 30 cm, although it will depend on

the energy levels. Because the radioactive decay is a statistical process,

slower logging rates produce better results. The low number of counts

resulting from logging too fast cannot be increased by logging rate correction

factors. Most tools are usually out of calibration if they are not centered in the

borehole. Heavy barite mud can also lower the overall count rate, particularly

for low-energy gamma rays.

Rather than merely measuring total gamma radiation, the energy levels can

be detected separately. This allows the concentrations of K, U, and Th to be

derived as independent parameters. Fig. 7 shows the energy windows used in

a Baker-Atlas tool. This would allow, for example, the feldspars in immature

sands to be separated from clays with adsorbed U or Th.

Fig. 7 – Gamma-ray energy windows used for spectral

gamma-ray logging (from Bigelow ).[2]

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Identifying shale volumes

The most common use of gamma ray logs is to estimate the shale "volume"

in rocks. It is important to remember that the tool measures radioactivity, and

the correlation to shale content is empirical. Shales are presumed to be

composed of clay minerals. Thus, the gamma ray level is assumed to be

correlated with grain size. In reality, shales may be composed of 30% or

more of quartz and other minerals. The clays within the shales may not be

radioactive, and the adjacent sands may contain radioactive isotopes.

However, radioactivity levels typically are related to grain size, as seen in Fig.

8. Here, core plugs were analyzed for median grain size and radioactivity level

measured directly; crosses are fine-grained sands, while dots are silts and

clay-rich rocks.








Fig. 8– Measured mean grain size vs. gamma-ray levels

(calibrated to API value) for clastic samples. The rough

correspondence of gamma ray value can be seen, butrelationship is not simple (data from Georgi et al . ).

To extract the shale content in rocks, a linear or near-linear relation is used to

convert a gamma ray index, I , to shale volume V . Because local sands

can contain radioactive components, and the shales may vary with depth,

local baseline levels are chosen near the zone of interest.

....................(9)

where R is the measured radiation level, R is the baseline level

through a reference sand, and R is the baseline through a representative

shale. Several relations have been developed to derive shale volume (Fig. 9).

A linear relation simply sets the shale content equal to the gamma ray index.

[5]

gr sh

cleansand

shale

....................(10)











....................(10)

Other proposed relations shown in Fig. 9 are defined in Table 3. Several

assumptions are made in these evaluations:

Compositions of sand and shale components are constant.

Baselines are chosen on representative "shales" and "clean" sands

(although these terms are very subjective).Simple mixture laws apply.

Fabric is not important.

Many of these assumptions may be poor approximations.

Fig. 9 – Reported gamma-ray index to shale volume

conversions (from Bigelow ).[2]











Table 3

A more likely presumption is that the radiation level is dependent on the

mixture densities and not volumes (Wahl and Katahara ). In this case, a

fabric analysis can also be performed. Katahara modeled the shale

component of shaly sands as existing in three forms:

Structural—an original depositional granular form.

Dispersed—clay distributed through the rock and pore space.

Laminated—thin layers of shale cutting the sand beds.

In Fig. 10, his results show a surprisingly simple form. The conclusion is that

in most cases, the simple linear relation is appropriate.

[6] [4]

[4]










Fig. 10 – Modeled gamma-ray response to different clay

distributions within a shaley sand series (modified from

Katahara ).

As an example of this process, the shale content of a zone in a Gulf of

Mexico well is estimated. In Fig.11, a sand-shale sequence gives a gamma

ray range of approximately 20 to 90 API units. A baseline of approximately 25

is chosen through the sand, and a baseline of approximately 98 is chosen for

the shale. Using the relations in Eqs. 9 and 10 result in the shale volume

estimates scaled at the bottom of the logged zone.

[4]










Fig. 11 – Typical shale volume extraction from a Gulf of

Mexico log. 100% “sand” and 100% “shale” lines are

locally established; then, shale content is a linear

interpolation between the two.

Correlating cores with logged depth

Gamma radiation levels can also be measured on core. This technique

provides a profile of levels along the length of the core. The primary use is to

correlate core depths to logged depths. An example is shown in Fig. 12. This

procedure can be used to identify log features or positioning of the cored

interval. Especially when core recovery is poor, this method is very useful in

tying the core fragments to true depths. Core plugs can also be measured,

although special equipment must be used to record the low levels of radiation

associated with the small samples. In general, property correlations to the

measured gamma ray levels are much better for cores than for the log

because of the depth averaging in the log. [5]









Fig. 12 – A measured core gamma-ray profile vs. logged

data in a carbonate section. Comparison of peaks shows

the offset in measured depth (adapted from Core Labs

data).

Nomenclature

A = atomic weight

E = gamma ray energy

N = Avogadro’s number = 6.02 × 10 23 molecules/gram molecular

weight

V = volume of clean formation

V = volume of fluid

GR

A

cn

f

V = volume of a particular constituent (mineral or fluid) of a

formation

i









formation

V = volume fraction of matrix mineral

V = volume of shale

Z = average atomic number

γ = gamma ray tool reading in API units

γ = gamma ray flux from 100% fluid

γ = gamma ray flux from 100% clean formation component

γ = gamma ray flux from 100% matrix

γ = gamma ray tool reading in nonshale

γ = gamma ray tool reading in 100% shale

ρ = bulk density

σ = Compton scattering cross section

Σ = capture cross section of i th formation component

Subscripts

GR = gamma ray

i = item count or index

References

1. ↑ Russell, W.L. 1944. The total gamma ray activity of

ma

sh

f

cn

ma

ns

sh

b

co

i

1.0 1.1

sedimentary rocks as indicated by Geiger counter determinations.

Geophysics 9 (2): 180 216 http://dx doi org/10 1190/1 1445076





http://dx.doi.org/10.1190/1.1445076




Geophysics 9 (2): 180-216. http://dx.doi.org/10.1190/1.1445076.

2. ↑ Bigelow, E.L. 1992. Introduction to Wireline Log Analysis.

Houston, Texas: Western Atlas International.

3. ↑ Tittmann, B.R., Clark, V.A., Richardson, J.M. et al. 1980. Possible

mechanism for seismic attenuation in rocks containing small amounts

of volatiles. Journal of Geophysical Research: Solid Earth 85 (B10):

5199-5208. http://dx.doi.org/10.1029/JB085iB10p05199.4. ↑ Katahara, K. 1995. Gamma Ray Log Response in

Shaly Sands. The Log Analyst 36 (4): 50.

5. ↑ Georgi, D.T., Bergren, P.A., and Devier, C.A. 1997. Plug

gamma ray: Key to formation evaluation. Poster presentation at the

1997 SCA International Symposium, Calgary, 8-10 September. SCA-

9732.

6. ↑ Wahl, J.S. 1983. Gamma-ray logging. Geophysics 48 (11): 1536-

1550. http://dx.doi.org/10.1190/1.1441436.

Noteworthy papers in OnePetro

Use this section to list papers in OnePetro that a reader who wants to learn

more should definitely read

External links

See also

Spectral gamma ray logs

Rock failure relationships

Nuclear log interpretation

2 .0 2 .1 2 .2

4.0 4 .1 4.2 4.3

5.0 5.1

Nuclear logging





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