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APPLICATION OF OLD ELECTRIC LOGS
IN THE ANALYSIS OF AUX VASES SANDSTONE
(MISSISSIPPIAN) RESERVOIRS IN ILLINOIS
Hannes E. Leetaru
Illinois Petroleum 134
1990
ILLINOIS STATE GEOLOGICAL SURVEY
Department of Energy and Natural Resources
Morris W. Leighton, Chief
ILLINOIS GEOLOGICAL
SU.xVE/ LIBRARY
ILLINOIS STATE GEOLOGICAL SURVEY
3 3051 00004 9159
APPLICATION OF OLD ELECTRIC LOGS
IN THE ANALYSIS OF AUX VASES SANDSTONE
(MISSISSIPPIAN) RESERVOIRS IN ILLINOIS
Hannes E. Leetaru
Illinois Petroleum 134
1990
ILLINOIS STATE GEOLOGICAL SURVEY
Department of Energy and Natural Resources
Morris W. Leighton, Chief
ILLINOIS GEOLOGICAL
SURVEY LIBRARY
Printed by authority of the State of Illinois/1990/750
CONTENTS
ABBREVIATIONS
ACKNOWLEDGMENTS
ABSTRACT
INTRODUCTION
BRIEF DESCRIPTION OF OLD ELECTRIC LOGS 4
STRATIGRAPHY 5
DATA ANALYSIS AND METHODOLOGY R
POROSITY 7
Short Normal Method 7
Rocky Mountain Method 7
Normalized Spontaneous Potential Method 8
PERMEABILITY
WATER SATURATION
SUMMARY
REFERENCES
APPENDIX
FIGURES
1
1
13
15
18
19
21
Generalized upper Valmeyeran and Chesterian geologic column of southern Illinois 1
2 Regional map showing study area and Aux Vases producing fields 2
3 Principal geologic structures of Illinois 3
4 Location of wells for which both core and electric logs are available in study area 6
5 Measured core porosity compared with porosity calculated from the short normal
[Rm taken from the log heading) 7
6 Measured core porosity compared with porosity calculated from the short normal
(Rm estimated using the Cypress sand) 8
7 Measured core porosity compared with porosity calculated using
the Rocky Mountain method 8
8 Electric log of the Cypress and Aux Vases interval showing the sand baseline
and the shale baseline 10
9 Electric log of the Cypress and Aux Vases interval showing SP baseline shift 1 1
10 Measured core porosity relative to NSP for all counties in study area 12
1 1 Measured core porosity relative to NSP for Jefferson County 12
12 Measured core porosity relative to NSP for Wayne County 12
13 Measured core porosity relative to NSP for Hamilton County 12
14 Measured core permeability relative to measured core porosity 13
15 Measured core permeability relative to NSP for all four counties 13
16 Measured core permeability relative to NSP for Jefferson County 13
17 Measured core permeability relative to NSP for Wayne County 14
18 Measured core permeability relative to NSP for Hamilton County 14
19 Pickett plot of estimated porosity relative to apparent FL from the short normal
for King Field, Jefferson County 16
ABBREVIATIONS
ACKNOWLEDGMENTS
F
m
n
NSP
r
"a
R
R~
SP
SP
SP,
SP.
log
formation factor
cementation exponent
number of wells
normalized spontaneous potential
porosity of the formation
Pearson correlation coefficient
apparent resistivity of the formation
resistivity of the invaded zone
resistivity of the mud
resistivity of the mud filtrate
resistivity of the formation 100 percent
saturated with formation water
resistivity of the formation
resistivity of the formation water
spontaneous potential
SP measurement from zone of interest
average SP at the shale baseline
average SP for a clean sandstone
water saturation
This research was done under U.S. Department of
Energy Grant DE-FG22-89BC14250 and the State
of Illinois through Department of Energy and
Natural Resources Grant AE-45. I thank Richard
Howard, Stephen Whitaker, and John Grube of the
ISGS and Daniel Hartmann of DJH Energy
Consulting for their comments and assistance with
this manuscript.
ABSTRACT
Old electric logs (pre-1960) are a valuable source
of information for the oil industry to use for im-
proved and enhanced oil recovery. In this study,
old electric logs were used effectively to estimate
porosity and water saturation. The empirical
methods described in this report are quick and
easy to use. Results of the analysis can be applied
to identifying passed-over pay in older wells and
as input into reservoir models.
Three methods for using old electric logs to esti-
mate the porosity of the Aux Vases Sandstone
(Mississippian) were tested for wells in Jefferson,
Wayne, Franklin, and Hamilton Counties in Illinois.
The empirical normalized spontaneous potential
method was significantly better at predicting poros-
ity than were the short normal or Rocky Mountain
methods.
Normalizing spontaneous potential values against
an internal standard can compensate for changes
in the scale of the log, the mud resistivity, and the
size of the borehole and allow direct comparisons
of spontaneous potential values between different
drill holes. The clean sandstones within the Cy-
press Formation, which occur about 200 feet
above the Aux Vases, were used in this investiga-
tion to normalize (or standardize) the spontaneous
potential.
Although on a regional scale values for permeabili-
ty from the normalized spontaneous potential are
commonly in the correct order of magnitude, they
are not considered accurate enough to use in
reservoir analysis. However, in local areas with
similar diagenetic and depositional facies, the
correlation can be strong enough to allow for
semiquantitative predictions of permeability. Pickett
plot analysis is a viable alternative to the Archie
equation in estimating water saturation in the Aux
Vases. The major advantage of Pickett plot analy-
sis is that neither the cementation exponent nor
the resistivity of the formation water has to be
known to calculate water saturation.
Digitized by the Internet Archive
in 2012 with funding from
University of Illinois Urbana-Champaign
http://archive.org/details/applicationofold134leet
INTRODUCTION
Techniques are presented for using old (generally
pre-1960) electric logs to characterize hydrocarbon
reservoirs of the Upper Valmeyeran (Mississippian)
Aux Vases Sandstone (fig. 1). Since many of the
Aux Vases oil fields were discovered before 1960,
an understanding of old electric logs is important
for detailed reservoir analysis. The better Aux
Vases oil fields were discovered between 1938
and 1955 and have produced more than 1 million
barrels of oil. Logging tools for measuring porosity
were rarely used. For example, in a typical field
such as King Field, Jefferson County, Illinois, less
than five neutron or micrologs were run out of the
163 wells drilled. One suite of modern logs was
run, but this well did not represent the reservoir
facies.
The study area includes Franklin, Hamilton, Jeffer-
son, and Wayne Counties (fig. 2). It lies in the
southern part of the Illinois Basin and is bounded
on the west, south, and southeast by the Du Quoin
Monocline, the Cottage Grove Fault System, and
the Wabash Valley Fault System (fig. 3). The Aux
Vases in the study area is 2,000 to 3,000 feet
deep.
Figure 1 Generalized upper Valmeyeran
and Chesterian geologic column of south-
ern Illinois (modified from fig. 3, prepared
by David Swann, from Bell et al. 1961).
Bullets indicate oil-producing intervals.
^^
GROVE CHURCH
KINKAID
• DEGONIA
• CLORE
• PALESTINE
MENARD
^
TTD
<■ 1 I "i ~* r.
i . .i ° i : i.
WALTERSBURG
VIENNA
TAR SPRINGS
GLEN DEAN
HARDINSBURG
HANEY
(Golconda lime)
FRAILEYS(Gol.sh)
Big Cliffy, Jackson
BEECH CREEK
(Barlow, basal Gol.)
CYPRESS
Weiler, Kirkwood,
Corlyle , Bellair 900,
Lmdley
RIDENHOWER(U P C )
Sample (P. Cr. Sd., E.III )
BETHEL
(Paint CrSd.,W.III.)
DOWNEYS BLUFF
(L. PC, U.Ren.)
YANKEETOWN
Benoist
RENAULT ( L.Ren.)
AUX VASES
STE GENEVIEVE
"Aux Vases lime
Ohara
Spar Mountain
( Rosiclore)
□
McClosky c
o
(Oblong) "°
L. McClosky £
Figure 2 Regional map showing study area and Aux Vases producing
fields (after Howard, in press).
-i —
50
60 mi
— h
100 km
Figure 3 Principal geologic structures of Illinois (after Buschbach and Kolata, in press).
3
BRIEF DESCRIPTION OF OLD ELECTRIC LOGS
Old electric logs are wireline logs that combine the
spontaneous potential (SP) and the normal and
lateral resistivity curves. By 1956, the induction log
began replacing the electric log as the primary
resistivity measurement tool (Hilchie 1979), al-
though in the Illinois Basin, electric logs continued
to be run during the early 1960s.
The SP measures the potential that has developed
opposite a permeable bed in a natural electro-
chemical cell composed of shale, freshwater, and
saltwater (Hilchie 1979). Griffiths (1952) showed
an inverse relationship between the amount of clay
and the magnitude of the SP. The SP-clay relation-
ship is the basis for the technique of estimating
porosity presented in this report. Although the SP
measures the amount of clay, not porosity and
permeability, an increase in clay implies a corre-
sponding decrease in porosity and permeability.
The normal refers to a log that was introduced by
Schlumberger in 1931 and became the primary
resistivity curve in the early electric log suite
(Hilchie 1979). The type of normal is defined by
the electrode spacing, usually referred to as the
AM spacing, which determines the depth of investi-
gation. In the Illinois Basin, many different elec-
trode spacings were used, of which the most com-
mon were the 16-inch short normal (AM = 16 in.)
and the 64-inch long normal (AM = 64 in.).
The depth of investigation of the normal is as-
sumed to be twice the AM spacing (Hilchie 1979).
At an AM spacing of 16 inches, resistivity is meas-
ured 32 inches from the borehole. At an AM
spacing of 64 inches, resistivity is measured 120
inches (-10 feet) from the borehole. The short
normal usually measures the average resistivity of
the invaded zone (R), which is saturated with a
mixture of mud filtrate and original formation fluid.
The long normal measures the apparent resistivity
(Ra) of the formation. Invasion and thin-bed effects
can still affect the long normal. Simply stated, the
long normal accurately measures formation resis-
tivity if beds are thicker than 1 0 feet and invasion
is less than 5 feet (Frank 1986).
The lateral, as a resistivity log, is of limited use in
analyzing the Aux Vases Sandstone because beds
must be thicker than 30 feet for the lateral to give
an accurate value for formation resistivity (Rt). The
Aux Vases in the study area is typically less than
30 feet thick and commonly less than 20 feet thick.
The lateral is asymmetrical; it does not peak
opposite the center of the bed, which complicates
interpretation.
STRATIGRAPHY
The Aux Vases Formation is the uppermost unit of
the Mississippian Valmeyeran Series (fig. 1). The
Aux Vases Sandstone in southern Illinois common-
ly is fine to medium grained, moderately to well-
sorted, and contains 81 to 98 percent quartz and
up to 13 percent feldspar (McKay 1980, Weimer et
al. 1982, Young 1983). Calcite, iron oxide, and
quartz are the main cementing agents. A typical
reservoir unit consists of a single porous, perme-
able lens, with a maximum thickness of 10 to 20
feet. Clean porous sandstone reservoirs grade into
silty or calcareous sandstones and shales. In parts
of the study area, the Aux Vases contains scat-
tered limestone lenses up to 10 feet thick.
Clay minerals have a major effect on log measure-
ments. The principal clay mineral groups repre-
sented in the Aux Vases are illite, mixed layer
(undifferentiated), and chlorite (Smoot 1960,
Wilson 1985, Seyler 1988). In addition to decreas-
ing the size of the pore throats, clays also increase
the surface area within the pores, thereby increas-
ing the amount of clay-bound (immobile) water.
The cation exchange capacity of these clays
causes lower resistivity values and increases the
calculated water saturation values.
The Aux Vases Formation is overlain by the
carbonate-dominated Renault Formation. The
Renault is relatively continuous in the eastern part
of the study area (fig. 2), but becomes more
discontinuous and difficult to correlate toward the
western edge of the study area, where it changes
to a sandstone-shale sequence and is indistin-
guishable from the Aux Vases. The resistivity of
the approximately 1 0-foot-thick carbonate facies
provides an excellent marker on electric logs.
Underlying the Aux Vases is the Ste. Genevieve
Formation, an oolitic or crinoidal limestone with a
fairly uniform electric log character. The Ste. Gene-
vieve can be a good marker that enhances correla-
tion, but differentiating the Ste. Genevieve from the
Aux Vases limestone facies can be difficult.
DATA ANALYSIS AND METHODOLOGY
The distribution of the 70 wells from which both
Aux Vases core data and electric log data were
collected is shown in figure 4. Within each well, the
log response of the Aux Vases was subdivided into
zones of similar electrical properties that were
calibrated with the core analyses. Most wells in
this study had core from only one zone. In total, 73
zones (or data points) were used in this study.
Thin-bed corrections to the long normal do not
need to be made if the zone is thicker than 1 0
feet. Beds thicker than 10 feet have minimal thin-
bed effects, simplifying log analysis and making it
more accurate. The assumptions made in thin-bed
corrections make the corrections difficult to use
(Hilchie 1982). In this investigation, no thin-bed
corrections were made to the normal. Beds adja-
o <
3
o
o
o o %*o
o
1
o
° <5b
I'
#
I
20
— r
30
Figure 4 Location of wells for which both core and
electric logs are available in study area.
cent to the Aux Vases Sandstone usually have a
resistivity greater than 10 ohm-m, which minimized
some effects of the adjacent bed.
Beds can be as thin as 5 feet before SP thin-bed
corrections need to be made. Thus, thinner beds
can be analyzed with the SP than with the normal.
If the SP curve shows a flat top, it can be an
indication that the SP is approaching static SP (the
true SP under ideal conditions).
Seventy-three zones from the 70 Aux Vases wells
were used to define the SP-resistivity-core relation-
ship. Although the average SP and short normal
were measured for each zone, the relation of the
short normal to porosity was determined in only 47
wells because not all of the wells had a measured
mud resistivity (Rm). For each zone, porosity and
permeability values were taken from commercial
core analyses. Core measurements are subject to
error, and different methods of porosity measure-
ment can yield different results (Corelab 1979). All
core analyses used in this report were done before
1960.
For purposes of log analysis, the resistivity of the
drilling mud (F?m) and the temperature at which the
Rm was measured are two of the most important
pieces of information required. Since the resistivity
of the mud changes with temperature, Rm must be
corrected to formation temperature before it can be
used in any log calculations. Almost 40 percent of
the 70 wells do not have the mud temperature
listed, and therefore, these wells have no usable
Rm. As will be discussed later, some wells may
also have had the Rm or the temperature meas-
ured incorrectly.
POROSITY
Three methods of predicting porosity from old
electric logs are discussed: short normal, Rocky
Mountain, and normalized SP (NSP). The first two
methods are commonly used in the industry, but
have several limitations. Of the three methods, the
NSP appears to provide the best results for the
Aux Vases in the study area.
Short Normal Method
Pirson (1957) and Hilchie (1979) describe proce-
dures and provide nomographs for estimating
porosity from the short normal. The techniques are
empirical and based on short normal measure-
ments of the resistivity of the invaded zone.
The calculation of porosity from the short normal
curve requires the following four conditions: (1)
invasion of drilling fluid into the formation is moder-
ate or deep; (2) porosity is less than 25 percent;
(3) the formation has intergranular porosity and
little shale; and (4) the Rm measurement is accu-
rate (Hilchie 1979). Of these conditions, the ac-
curate Rm measurement may be most critical,
because all of the methods used to derive porosity
from the short normal involve a ratio of the resistiv-
ity of the invaded zone to Rm. Aux Vases Sand-
stone porosities calculated using the short normal
generally correlate very poorly with the actual
measured porosities from core when Rm is taken
from the log heading (fig. 5). All calculated porosity
values greater than 30 percent were plotted at 30
percent porosity, because measured porosities for
the Aux Vases were never greater than that value.
An approximate Rm was calculated from the logs
to determine whether the measured Rm was a
major source of error. In this method, thetypress
sand (fig. 1) was used to estimate Rm. The thick
well-sorted clean sandstone of the Cypress dis-
plays a distinctive log character and has a relative-
ly uniform porosity of 16 to 22 percent. In this
study, the porosity of a clean Cypress sand was
defined as having an average porosity of 18
percent. An approximate value for Rm can be
estimated by reversing the regular Pirson method
(Pirson 1957) of calculating porosity from the short
normal. This reverse method requires that the
porosity of the Cypress remain relatively constant
from well to well.
30
r = .23
n = 47
<D
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E
p
g
o
°- 10
"D
CD
L.
CO
co
a>
E
• r: * t
• • ••
0
30
10 20
porosity from short normal (%)
Figure 5 Measured core porosity compared with
porosity calculated from the short normal (Rm in the
porosity calculation was taken from the log heading).
With the reverse Pirson method, variations in the
actual porosity of the Cypress cause errors in the
estimated Rm. The calculated porosity of the Aux
Vases using the estimated Rm is a somewhat
better approximation of the measured core porosity
(fig. 6) than the porosity calculated using the Rm
from the log heading (fig. 5). This observation
suggests that the Rm values on the log headings
are incorrect for a significant number of the evalu-
ated wells.
The parameter Rm is used in many critical log
interpretation calculations. For instance, it is an
intrinsic part of estimating resistivity of formation
water (flj from SP and of estimating porosity
using micrologs (Hilchie 1979). The measured Rm
from old electric logs in the Illinois Basin apparent
ly is not reliable; corresponding calculations using
the measured Rm are suspect.
Rocky Mountain Method
The Rocky Mountain (Tixier) method permits the
determination of water saturation and porosity
when only Rv resistivity of the invaded zone {R),
and SP are known (Schlumberger 1955, Tixier
1949). Use of this method is appropriate where
3U-
r =
.44
n =
= 64
•
•
g
•
CD
o
•
.'••.If:
g 20-
•
•• *•
o
f
. •
>.
I
• _•
•
•
in
O
• •
o
•
•
CL
•
•
| 10-
•
•
3
V)
m
CD
E
10 20
porosity from short normal (%)
30
Figure 6 Measured core porosity compared with
porosity calculated from the short normal (Rm in the
porosity calculation was estimated using the Cypress
sand).
moderate or deep invasion of the mud filtrate has
occurred (Hilchie 1979). The short normal is used
as a porosity indicator and the SP as an indicator
of f?w. The nomograph used in the calculations can
be found in the above references.
The Rocky Mountain method compares the resis-
tivity deflection of the shallow tool (short normal) to
the resistivity curve of the deep investigation tool
(long normal). The Rocky Mountain method has
three limitations that are similar to those of the
short normal method: (1) the invaded zone must
have a diameter large enough for the short normal
to read this zone; (2) the long normal must meas-
ure a value of fl; and not be overly affected by the
invaded zone; and (3) the beds must be thick
enough that bed thickness corrections are not
required (Pirson 1963).
The porosity values calculated from the Rocky
Mountain method were compared with core porosi-
ty measurements (fig. 7). Again, all porosity values
calculated at greater than 30 percent were plotted
at 30 percent porosity.
The Rocky Mountain method produces better
estimates of porosity than does the short normal
method. In the Rocky Mountain method, the
difference between the core porosity and the
calculated porosity is, in some instances, as high
as 10 percent, but the standard error of estimate
is 3.4 percent porosity.
3U
r=
.66
ii
n =
= 66
•
• II
Co"
I
o
CD
•
• •
•
:
•
:
8 20-
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E
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s
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•
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55
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T3
CD
• •
i_
3
w
co
CD
E
O-
i
i
0 10 20 30
porosity from Rocky Mountain method (%)
Figure 7 Measured core porosity compared with
porosity calculated using the Rocky Mountain method.
Because of the erratic results, the use of the
Rocky Mountain method in the evaluation of the
porosity in the Aux Vases Sandstone is not recom-
mended. The method probably is not effective
because the depth of invasion is different in the
various wells. The difference in the radius of
invasion could be due to changes in permeability
of the formation, changes in the mud characteris-
tics, and the length of time that the formation was
subjected to invasion (Hietala and Connolly 1984).
Normalized Spontaneous Potential Method
Because the actual value of SP on the log is not
an absolute number, SP values cannot be directly
compared among different wells. Normalizing SP
values against an internal standard can compen-
sate for changes in the scale of the log, the mud
resistivity, and the size of the borehole, and thus
allows direct comparisons of SP values between
different drill holes.
The Cypress Sandstone, which occurs some 200
feet above the Aux Vases, was used in this investi-
gation to normalize or standardize the SP curves.
The Cypress is commonly more than 1 00 feet thick
and consists of multiple sandstone bodies that can
each be more than 50 feet thick. Cypress sand-
stones are typically light gray to white, fine to
medium grained, angular, and friable. Analyses of
numerous Cypress cores reveal that porosity and
permeability values are relatively consistent.
Therefore, the Cypress appears to be especially
suitable as a standard for normalizing SP.
8
Wells drilled with freshwater exhibit positive SP
deflections in shales, and where shale is the
dominant lithology, tend to follow a straight line,
called the shale baseline (fig. 8). In permeable
sandstones, the SP response is negative and
approaches a constant value corresponding to a
response of a well-sorted sand containing almost
no clay matrix between the sand grains (the clean
sand baseline). Flattening of the SP response of a
sandstone to a nearly horizontal line across the log
chart indicates that the SP value at maximum
deflection is close to the static SP of the formation.
If the SP curve is not flat, then the bed is probably
too thin to permit determination of static SP.
The position of the shale baseline on an SP log is
arbitrary; the millivolt readings are not referenced
to an absolute value (Schlumberger 1972). The
scale (deflection from the shale baseline) of the SP
and the location of the shale baseline are set by
the logging engineer and vary from well to well.
The ratio of resistivity of the mud filtrate (/?ml) and
the Rw has a profound effect on the magnitude of
the SP and is different in each well. The greater
the contrast between the resistivity of the mud
filtrate and the formation water, the greater the
difference in the millivolt values between the shale
baseline and the clean sand baseline for the log
(Schlumberger 1972). Conversely, an increase in
hole diameter tends to reduce the amplitude of the
SP response across permeable beds (Frank 1986).
Normalization reduces the effects of both borehole
size and mud resistivities when SP values of
different wells are compared.
The first step to normalize the SP measurements
is to establish a shale baseline (SPmin) through the
average SP curve in a thick shale. Similarly a
clean sand baseline (SPmax) is established. For
this study, the sand baseline was defined from the
Cypress sand (fig. 8) with the largest negative
millivolt value. The millivolt values for the shale
baseline and the clean sand baseline established
for each log record were input with the SP for the
zone of interest in the normalizing equation. The
NSP values are unitless and range from 0 to 100.
where
SP„
max
SPmin =
SPlog =
average maximum SP reading (mV) for
a clean Cypress sandstone
average SP (mV) at the shale baseline
SP value (mV) for the zone of interest
In the area of investigation, each well was stan-
dardized using the value for the cleanest thick
Cypress sand encountered in the well (SPmax) as
a reference. Changes in the Cypress can be
monitored on the log by visually comparing it with
another clean thick sand, such as the Tar Springs,
200 feet above the Cypress interval.
The shale baseline is usually relatively easy to
determine on the SP curve, but as seen in figure
9, some wells in the study area have a baseline
shift occurring in the Cypress Formation. Two
explanations are possible. These baseline shifts
can occur when formation waters of different
salinities are separated by a shale bed that is not
a perfect cationic membrane (Pied and Poupon
1966). Another possibility is that the logging
engineer mechanically shifted the baseline in the
well. The normalization procedure is not valid in
these wells and they were not included in the
analysis.
The relation between NSP and measured core
porosity in 73 zones (all counties in this study
area) has a Pearson correlation coefficient (r ) of
0.83 (fig. 10). The equation of the least-squares
regression line relating porosity and NSP is
4> - .208(NSP) + 2.009
[2]
where $ = porosity measured from core (%)
The data exhibit considerable scatter or deviation
from the least-squares regression line. More than
a 5 percent porosity difference can occur between
the core analysis and the predicted porosity calcu-
lated using the best fit regression line. However,
most wells show a significantly smaller amount of
error. The calculated standard error of estimate is
2.6 percent porosity. As shown in figure 10, the
two lines drawn parallel to the regression line' at a
vertical distance equal to the standard error of
estimate will by definition include two-thirds of the
points from a given sample (Alder and Roessler
1960).
Modern porosity tools, such as density and neutron
logs, can also have errors of about the same
magnitude. Lang (1980) determined that 58 per-
cent of the wells in a 360-acre area in the San
Joaquin Valley of California needed correction. The
average correction was 3 percent porosity.
Although linear regression analyses were calculat-
ed separately for Jefferson, Wayne, and Hamilton
Counties, the results for these individual counties
John E. Carlson
S. J. Hicks #1
28-3S-3E
King Field
Jefferson County, Illinois
TD 2738
BHT not measured
Rm 2.4 ohm-m at 73°F
Completion date April 1954
completed for 110 barrels of oil
and 5 barrels of water per day
from Aux Vases Sandstone
AM 16 in.
Figure 8 Electric log of the Cypress and Aux Vases interval showing the sand
baseline and the shale baseline.
are not as valid as the combined analyses for all
four counties. For a single county with a low
number of wells, a single well can unduly influence
the regression results. If the measured values for
a single well were in error, then the regression line
could be in error.
The relationship between NSP and porosity in
Jefferson (fig. 11), Wayne (fig. 12), and Hamilton
(fig. 13) Counties appears to be comparable.
However, Hamilton County is of particular interest
because of the large number of data points that
form a vertical cluster where NSP = 100. Reasons
10
Edward T. Robinson
Omar Smith #2-A
21-3S-3E
King Field
Jefferson County, Illinois
TD 2750
BHT 98°F
Rm 1.8 ohm-m at 75°F
Completion date May 1955
completed for 20 barrels of oil
and 10 barrels of water per day
from Aux Vases Sandstone
AM 64 in.
Figure 9 Electric log of the Cypress and Aux Vases interval showing SP baseline
shift.
for the large number of such points in Hamilton
County are discussed later in Permeability.
Boundary effects also cause part of this vertical
clustering of points at NSP = 100. In the normal-
ization procedure, the SP is compared with the
clean Cypress sand. The NSP cannot be greater
than 100. Therefore, if the Aux Vases Sand has an
SP equal to or greater than the Cypress, it must
be equal to 100.
11
ILLINOIS GEOLOGICAL
SURVEY LIBRARY
standard error of estimate
best fit linear regression line
40
50
60 70
normalized SP
8cT
90 100
Figure 10 Measured core porosity relative to NSP for
al I counties i in study area. Two-thirds of data values wil
fall wrthin the bounds of the standard error of estimate
30
o
o
E 20
o
o
o
Q.
■o
0)
r=.87
n = 18
3
CO
03
E
10-
40
50
60 70 80
normalized SP
90
Figure 11 Measured core porosity relative to NSP for
Jefferson County.
The best fit line, equation 2, should be used with
some caution when porosity is estimated. If core
data from the field indicate an average porosity
hat is lower or higher than the predicted porosity
l?hct f inear/e9ression, core data should be
substituted on the plot and the curve modified The
determination of the Aux Vases porosity from the
bP log in this study is based on a local empirical
30
v>
o
k.
o
Q.
-a
2?
05
a>
E
20-
r = .74
n = 23
10
• •
40 50
60 70 80
normalized SP
-I
100
Figure 12 Measured core porosity relative
Wayne County.
90
to NSP for
30
8 20
E
o
r = .78
n = 28
• •
o
Q.
■o
c/>
CD
(1)
E
10-
40
~1 1 r— 1-
50 60 70 80
normalized SP
90
100
HamTon3CoMumySUred W POrOSi,y relatlVe t0 NSP ^
Somh"^- Thf eq.Uation definin9 this relationship
should be used only for the four-county area for
which it was derived. The technique should not be
used with another formation or lithology without
Z« IT "t?10" °f the SP resP°nse to measured
core data. The analysis was done on Aux Vases
sandstones, and the results are not valid for
limestones.
12
PERMEABILITY
A logarithmic relationship can be seen between
average core porosity and core permeability (fig.
14). This relationship is linearized by using the log
of the permeability value. A direct correlation also
exists between the NSP and log of the permeabili-
ty (fig. 15). Kolodzie (1980) found a general rela-
tionship between permeability and NSP, and
estimated permeability by using the NSP.
Unlike the NSP-porosity relationship, the NSP-
permeability relationship is not linear. Measured
permeability values for the Aux Vases plotted
against NSP show a wide range. Therefore, this
method cannot be used in general reservoir stud-
ies to predict permeabilities. For example, in figure
15 for an NSP value in the mid-60s, measured
permeability ranges from <10 md to >100 md. Aux
Vases sandstone wells with permeabilities <10 md
are not commercial, whereas those at 100 md can
be prolific producers.
In local areas such as Jefferson County, the NSP-
permeability method may be useful (fig. 16). The
NSP cross plots may work here because all of the
Aux Vases was formed in a similar diagenetic and
depositional environment. Subsequent work may
document a relationship between NSP and perme-
ability, which would allow semiquantitative predic-
tions of some reservoir characteristics.
Least-squares regression analysis of permeability
and NSP data from Jefferson County show a
IUUU.U
r=
.74
t
E,
n =
73
•
•1
§ 100.0-
• •
•
•.«•
II
o
E
•
•
II
ii
II
permeability
o
b
•
•
• •
• "
measured
b
i
•
•
•
•
•
0.1-
i
i
i
i
40 50 60 70 80
normalized SP
90
100
Figure 15 Measured core permeability relative to NSP
for all four counties.
1000.0
10 20
measured porosity from core (%)
Figure 14 Measured core permeability relative to
measured core porosity.
30
1000.0
■o
E
2 100.0
o
o
E
o
= 10.0
-Q
03
CD
E
CD
Q.
T3
CD
C/5
co
CD
E
LO-
OM-
r = .91
n = 18
1 1 1 1—
40 50 60 70 80
normalized SP
90
100
Figure 16 Measured core permeability relative to NSP
for Jefferson County.
13
1000.0
1000.0-
40
50
60 70 80
normalized SP
90
100
40
50
Figure 17 Measured core permeability relative to NSP
for Wayne County.
correlation of 0.91 (fig. 16). This strong correlation
results from Jefferson County having the fewest
number of wells with NSP = 100. Wayne County
(fig. 17) and Hamilton County (fig. 18) have large
percentages of wells with NSP = 100. The high
number of wells with values of NSP = 100 for the
Aux Vases Sandstone in Hamilton County may be
due to differences in the nature and amount of
matrix in the Aux Vases in Hamilton County. The
inferred source of the Aux Vases Sandstone is
from the west and northwest of the study area
(Swann and Bell 1958). Of the three counties
studied, Hamilton is the farthest from the source
area, and it should exhibit the highest calcite
content and the lowest clay content. This relation-
ship is partly confirmed by Wilson (1985), whose
60 70~~ 80
normalized SP
100
Figure 18 Measured core permeability relative to
for Hamilton County.
NSP
data indicate a decrease in the clay matrix of Aux
Vases reservoir rock in Hamilton County compared
with that of the other counties in the study area.
An inverse correlation exists between the magni-
tude of the SP and the percentage of clay. High
NSP values for the sands in Hamilton County may
be due to their relatively low clay content. Although
these sands appear "clean" on the SP, their
permeability may have been reduced by calcite
cement.
An approximation for permeability when NSP =
100 could be obtained in Hamilton and Wayne
Counties by using the average permeability at NSP
= 100. Here, both counties have an average
permeability of 100 md.
14
WATER SATURATION
Calculating accurate values of water saturation
(Sw) for Aux Vases Sandstone from the data
available in Illinois has been a problem for years.
Water saturation values, including those calculated
from modern log suites, can be as high as 60 to
80 percent for wells in the Aux Vases Sandstone
that produce little or no water (Seyler 1988). On
the other hand, some Aux Vases wells have high
water saturations and produce water. This great
variability of Sw values in producing wells compli-
cates the well evaluation process.
The high Sw values in producing wells are proba-
bly caused by two factors: (1) the cementation
exponent used in the formation factor relationship
of the Archie equation was too high (Archie 1942),
and (2) clay was present in the formation.
The most common method used to calculate water
saturation in rocks that contain little clay in the
matrix is the basic Archie equation (Archie 1942):
\
ft
[3]
where
Sw =
ftw =
ftt =
F =
water saturation (%)
resistivity of formation water (ohm-m)
resistivity of the formation (ohm-m)
formation factor
In the Archie equation 3,
F-_L
(J)m
[4]
where
m = cementation exponent
<b = porosity (%)
The cementation exponent (m) is the most difficult
of the variables in the Archie equation to deter-
mine. The value of m is dependent on pore geom-
etry and equals 2 in sandstones that contain no
clay matrix. In sandstones with a substantial
amount of clay, m can be as low as 1.7 (D. Hart-
mann, personal communication 1990). A common
method of compensating for the effects of clay on
old electric logs was to vary the cementation
exponent. In some cases, a value of m as low as
1.5 was used (Hilchie 1979). These low m values
are not actual values measured from the rock;
however, low cementation exponent values can
produce realistic water saturations in shaly forma-
tions. This method of using artificially low m values
is basically a simplified version of the modern
shaly sand calculations. The Aux Vases at King
Field, which will be discussed latter, has clay in its
rock matrix. For this reason, the cementation
exponent of the Aux Vases at King Field was
assigned a value of 1 .7.
Winsauer et al. (1952) showed that the cementa-
tion exponent has lower values for better sorted,
slightly cemented sands than for those that are
heavily cemented. Doveton (1986) also found the
cementation exponent to be sensitive to the depo-
sitional fabric or bedding of the rock. On a regional
scale, the Aux Vases will have significant varia-
tions in both the clay content and distribution of the
clay in the pore throat, which will cause corre-
sponding variations in m.
Pessimistic Sw values result from using m = 2 for
clean sandstone in the Archie equation when an m
= 1 .7 better reflects the clay percentage. Constant
m values should not be used on a regional basis
for calculating Sw from the Archie method or any
analytical method that uses the cementation
exponent. On a local scale, m should not vary
significantly, and reasonable water saturation
values can be calculated using a constant value
for m.
If the value of m is assumed to remain relatively
constant over an area, yet its value is unknown, a
Pickett plot or log-log plot of resistivity relative to
porosity values can be effectively used to estimate
water saturation (Pickett 1973, Lang 1973). The
Pickett plot is a graphic derivation of the Archie
equation. The initial step in analyzing well logs
using the Pickett plot method is to define the 100
percent Sw zones on a log and use these zones in
defining resistivity of a formation 100 percent
saturated with formation water (ftj. The R0 values
when plotted relative to porosity establish the ft0
line. All other water saturation percentages are
calculated from the initial R0 line. The slope of the
ft0 line on the Pickett plot reflects the value of m.
15
Note that the Pickett plot will work only if m stays
constant throughout the study area and the resis-
tivity tool has the same depth of investigation. The
long normal (AM64) was used in this study. Meas-
urements made with different types of tools cannot
be mixed together on a Pickett plot. For example,
values of resistivity from the induction tool cannot
be used together with values from a long normal
tool.
A Pickett plot analysis was used to determine the
water saturation of King Field, which has produced
more than 4 million barrels of oil from the Aux
Vases sand. All of the wells that had usable logs
were plotted on the Pickett plot (fig. 19). The
porosity was calculated using the NSP method;
resistivity was measured from the long normal.
When m is constant, porosity and resistivity from
those wells that either tested water or were drilled
below the oil-water contact should ideally plot
along a straight line on log-log graph paper (Lang
1973). At King Field, the oil-water contact is not
well defined, and some of the wells that have been
interpreted as wet may contain oil. All of the wells
drilled into the postulated water zone plot below Sw
>50 percent. The data are more scattered than on
modern logs. This scatter probably resulted from
error in using estimated porosity from the SP. Con-
stant water saturation lines are plotted to the right
of the R0 line and parallel to it. Hydrocarbon-
bearing zones occur to the right of the R0 line. The
equation (Hilchie 1982) used to calculate the
position of the Sw lines is
/*-
R
(SJ<
[5]
where
Sw =
resistivity of the formation (ohm-m)
resistivity of the formation 100 percent
saturated with formation water (ohm-m)
water saturation (%)
To use this equation, a porosity value must first be
determined. The RQ value corresponds to a partic-
ular resistivity value at the selected porosity. With
the Pickett plot of King Field used as an example,
the corresponding value of f?0 for a porosity of 25
percent is 2.2 ohm-m (fig. 19). For Sw = 50 per-
cent, the calculated /?, value is 8.8 ohm-m at 25
percent porosity. For all different porosity values,
an Sw = 50 percent defines a linear trend of
resistivity values that is parallel to the R0 line, with
resistivities four times higher than the R0 line. The
100
55 10
o
o
Q.
25% ^\ \ ^\
• produces oil
A below or at oil water contact
i
2.2
8.8
i
0.1
1.0 10.0
apparent resistivity (ohm-m)
100.0
Figure 19 Pickett plot of estimated porosity relative to apparent Rt from the short normal
for King Field, Jefferson County. The slope of the RQ line is equal to a cementation exponent
of approximately 1.7.
16
same principle is used to establish any other Sw
percentage.
The long normal can be used for the Pickett plot
analysis, since an actual ft, value is not necessary
and the long normal response commonly was
obtained from deep enough in the formation to
approximate fl,. If different wells are to be com-
pared, then the resistivity tools must have a similar
electrode spacing and measure approximately the
same distance into the formation so that the
Pickett plot method will be valid. That the long
normal response may be from part of the invaded
zone is ignored in the Pickett plot. Therefore, the
actual long normal values can usually be plotted
without having to take the invasion profile into
account.
In theory, the intercept of the RQ line at 100 per-
cent porosity should be the value of f?w. If the
resistivity log is not measuring a true* ft,, the
intercept will not be flw but instead will be a value
between R„ and Rmi. For King Field, the long
normal tool is not an accurate R{ measuring device
but is actually measuring part of the invaded zone.
Because multiple wells have diverse Rmi values,
the resistivity intercept at 100 percent porosity is
not a true Rw value.
17
SUMMARY
In Hamilton, Wayne, Franklin, and Jefferson
Counties, the NSP technique was significantly
better than were the short normal and Rocky
Mountain methods in predicting porosity in the Aux
Vases Sandstone. The NSP in relation to core
porosity had a correlation coefficient of 0.83. The
short normal Rm from the log heading, short
normal Rm calculated, and Rocky Mountain meth-
ods had correlation coefficients of 0.23, 0.44, and
0.66, respectively. The measured Rm reported on
old electric logs in the Illinois Basin is not a reliable
value, so calculations using Rm may be in error.
The NSP cannot be used to accurately predict
permeability. Although calculated values commonly
are the correct order of magnitude, but they usual-
ly are not accurate enough for detailed reservoir
analysis.
Water saturations can be estimated by using
Pickett plot analysis. The major advantage of
Pickett plots over the basic Archie equation is that
Pickett plots do not need the cementation expo-
nent or the resistivity of the formation water to be
predefined.
18
REFERENCES
Alder, H. L, and E. B. Roessler, 1960, Introduction
to Probability and Statistics: W. H. Freeman &
Company, San Francisco, California, 252 p.
Archie, G. E., 1942, The electrical resistivity log as
an aid in determining some reservoir charac-
teristics: Transactions of the American Insti-
tute of Mechanical Engineers, v. 146, p.
54-62.
Bell, A. H., M. G. Oros, J. Van Den Berg, C. W.
Sherman, and R. F. Mast, 1961, Petroleum
industry in Illinois, 1 960: Illinois State Geologi-
cal Survey, Illinois Petroleum 75, 121 p.
Buschbach, T. C, and D. R. Kolata, in press,
Regional setting of Illinois Basin, in M. W.
Leighton, D. R. Kolata, D. F. Oltz, and J. J.
Eidel, editors, Interior Cratonic Basins (World
Petroleum Basins series): The American
Association of Petroleum Geologists, Tulsa,
Oklahoma.
Corelab, 1979, Fundamentals of Core Analysis:
Core Laboratories, Inc., 70 p.
Doveton, J. H., 1986, Log Analysis of Subsurface
Geology Concepts and Computer Methods:
John Wiley & Sons, New York, 273 p.
Frank, R. W., 1986, Prospecting with Old E-Logs:
Schlumberger Educational Services, Houston,
Texas, 161 p.
Griffiths, J. C, 1952, Grain-size distribution and
reservoir-rock characteristics: American Asso-
ciation of Petroleum Geologists Bulletin, v. 36,
no. 2, p. 205-229.
Hietala, R. W., and E. T. Connolly, 1984, Well log
analysis methods and techniques in J. A.
Masters, editor, Elmworth, Case Study of a
Deep Basin Gas Field: American Association
of Petroleum Geologists Memoir 38, p.
215-242.
Hilchie, D. W., 1979, Old Electric Log Interpreta-
tion: Institute for Energy Development, Tulsa,
Oklahoma, 161 p.
Hilchie, D. W., 1982, Advanced Well Log Interpre-
tation: Douglas W. Hilchie, Inc., Golden,
Colorado, 208 p.
Howard, R. H., in press, Hydrocarbon reservoir
distribution, in M. W. Leighton, D. R. Kolata,
D. F. Oltz, and J. J. Eidel, editors, Interior
Cratonic Basins (World Petroleum Basins
series): The American Association of Petro-
leum Geologists, Tulsa, Oklahoma.
Kolodzie, S., 1980, Analysis of pore throat size
and use of the Waxman-Smits equation to
determine OOIP in Spindle Field, Colorado:
presented at Society of Petroleum Engineers
meeting, Dallas, Texas, September 1980,
SPE paper 9382.
Lang, W. H., 1973, Porosity-resistivity cross-plot-
ting: The Log Analyst, January-February, v.
14, no. 1., p. 16-20.
Lang, W. H., 1980, Porosity log calibrations: The
Log Analyst, March-April, v. 21, no. 2, p.
14-18.
McKay, R. H., 1980, A Depositional Model for the
Aux Vases Formation and the Joppa Member
of the Ste. Genevieve Formation (Mississippi-
an) in Southwestern Illinois and Southeastern
Missouri: M.S. thesis, Southern Illinois Univer-
sity, Carbondale, 184 p.
Pickett, G. R., 1973, Pattern recognition as a
means of formation evaluation: The Log
Analyst, July-August, v. 14, no. 4, p. 3-11.
Pied, B., and A. Poupon, 1966, SP base line shifts
in Algeria: Seventh Annual Society of Profes-
sional Well Log Analysts Symposium, Society
of Professional Well Log Analysts, Tulsa,
Oklahoma, p. 1H-12H.
Pirson, S. J., 1957, Formation evaluation by log
interpretation: World Oil, April, May, June.
Pirson, S. J., 1963, Handbook of Well Log Analy-
sis for Oil and Gas Formation Evaluation:
Prentice-Hall, Inc., Englewood Cliffs, New
Jersey, 326 p.
Schlumberger, 1955, Log Interpretation Charts:
Schlumberger Limited, Houston, Texas, p.
D7-D8.
Schlumberger, 1972, Schlumberger log interpreta-
tion, Volume 1— Principles: Schlumberger
Limited, Houston, Texas, 113 pp.
Seyler, B. J., 1988, Role of clay mineralogy in
water saturation; drilling, completion, and
recovery techniques, in C. W. Zuppann, B. D.
Keith, and S. J. Keller, editors, Geology and
Petroleum Production of the Illinois Basin.
Volume 2: Indiana-Kentucky and Illinois Geo-
logical Societies Joint Publication, p. 150.
Smoot, T. W., 1960, Clay mineralogy of pre-Penn-
sylvanian sandstones and shales of the Illinois
Basin. Part III. Clay minerals of various facies
of some Chester formations: Illinois State
Geological Survey, Circular 293, 19 p.
Swann, D. H., and A. H. Bell, 1958, Habitat of oil
19
in the Illinois Basin, in L. G. Weeks, editor,
Habitat of Oil: The American Association of
Petroleum Geologists, Tulsa, Oklahoma, p.
447-472.
Tixier, M. P., 1949, Electric log analysis in the
Rocky Mountains: Oil and Gas Journal, June
23, p. 143-147, 217-219.
Weimer, R. J., J. D. Howard, and D. R. Lindsey,
1982, Tidal flats and associated tidal chan-
nels, in P. A. Scholle and D. Spearing, edi-
tors, Sandstone Depositional Environments:
American Association of Petroleum Geologists
Memoir 31, 410 p.
Wilson, B., 1985, Depositional Environments and
Diagenesis of Sandstone Facies in the Aux
Vases Formation (Mississippian), Illinois
Basin: M.S. thesis, Southern Illinois Universi-
ty, Carbondale, 130 p.
Winsauer, W. O., H. M. Shearin, Jr., P. H. Mas-
son, and M. Williams, 1952, Resistivity of
brine saturated sands in relation to pore
geometry: American Association of Petroleum
Geologists Bulletin, v. 36, no. 2, p. 253-277.
Young, V. R., 1983, Permeable Sand Body Trends
in the Aux Vases Formation, Buckner-Sesser-
Valier Fields, Franklin County, Illinois: M.S.
thesis, Southern Illinois University, Carbon-
dale, 79 p.
20
APPENDIX
The following example is a step-by-step log analy-
sis of the Aux Vases Sandstone in King Field,
Jefferson County, Illinois. Figure 8 is the sample
well log for which the analysis will be done.
Step 1
Calculate the NSP from the log:
SPma, - -126
SPn
SP
log
I -1001 -I -161
1-1261- 1-161
- -16
- -100
x 100 - NSP - 76
Step 2
Plot on figure 10 the value for NSP. Using the best
fit line, determine the porosity of the well. With this
method, porosity = 18 percent. The alternative
method is to input the NSP value into the equation:
<() = 0.208(NSP) + 2.009
18.0 - 0.208(76) + 2.009
Step 3
Read the apparent resistivity of the AM64 long
normal curve:
ft, = 15 ohm-m
Step 4
Use the porosity calculated from step 1 and the
apparent resistivity from step 4 in the Pickett plot
(fig. 19) to estimate a Sw = 55 percent.
Summary
This well was an oil producer with an initial poten-
tial of 1 1 0 barrels of oil per day and 5 barrels of
water per day. This oil production confirms that the
well has a low S„. This Sw value is quite accept-
able, especially since no bed thickness corrections
were made to the SP or the AM64.
In this example, the true SP (or static SP) is
probably higher than the SP curve shows. The SP
curve does not have the flattening usually indica-
tive of a static SP value. The bed is nearly 10 feet
thick; therefore, the AM64 is certainly not reading
a true Rx value.
Most of the King Field wells encounter an Aux
Vases that is 10 to 15 feet thick. So long as the
beds adjacent to the Aux Vases have similar
resistivity, the Pickett plot, because it is a pattern
recognition method, ignores the error caused by
thin-bed effect. All of the wells would have approxi-
mately the same resistivity correction, and the
relative Rt would be the same after a thin-bed
correction.
21
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