Well Logging Lectures (Prepared by Dr. Fadhil S.
Kadhim)
Clay Volume and Clay Distribution
1. Clay Volume
One of the most controversial problems in the formation evaluation is the clay effect to
reservoir rocks. Shale is usually more radioactive than sand or carbonate. Therefore gamma ray
log and other logs can be used to calculate the volume of shale in a porous medium. The volume of
shale expressed as a decimal fraction or percentage is called Vshale. The volume of clay can be
calculated by two sets of well-logging indicators which are Single Clay Indicators (SCI) and
Double Clay Indicators (DCI). The minimum value of Vclay is the closest to the truth.
Single Clay Indicators
The spectral gamma ray (SGR) provides the measure of the total natural radioactivity of the
formation. The spectral gamma ray tool detects the naturally occurring gamma rays and defines
the energy spectrum of the radiations. Since Potassium (K), Thorium (Th) and Uranium (UR) are
responsible for the energy spectrum observed by the tool, their respective elemental concentrations
can be calculated by the following equations:
Well Logging Lectures (Prepared by Dr. Fadhil S. Kadhim)
SGR SGRmin
Vclay
SGRmax SGRmin
UR URmin
(Vclay )UR
URmax URmin
K K min
(Vclay ) K .
K max K min
Th Thmin
(Vclay ) Th
Thmax Thmin
Since the Uranium is associated with radioactive minerals other than those found in clay
(i.e. Organic materials), so it is generally not a reliable clay indicator. By eliminating the
uranium contribution from the total gamma ray response and defining the Corrected Gamma
Ray GRC (i.e., sum of thorium and potassium only) therefore the shale volume can be
calculated by the following equation:
GRC GRC min
Vsh
GRC max GRC min
Where: CGR: Corrected gamma ray logs reading in the zone of interest (API units), CGRmin: Corrected
gamma ray logs reading in a 100 % clean zone (API units), CGRmax: Corrected gamma ray logs reading in
100% shale (API units).
Well Logging Lectures (Prepared by Dr. Fadhil S. Kadhim)
Neutron log reading provides correlation that often used to calculate the shale volume as
shown in the following equation.
NPHI NPHI NPHI clay
Vsh
NPHI NPHI NPHI
clay clay clean
From the Spontaneous Potential (SP) log reading in water-bearing sands of low to moderate
resistivity containing laminated clay, the following relation is used to calculate clay volume:
PSP
Vcla y 1
SP
The above equation is used when the SP log reading taken depending on shalebase line. A straight
interpolation is used to get the following relationship for computerized calculation if the value of
SP reading is taken from the SP log directly without reference to shalebase line:
SP SPclean
Vsh
SPclay SPclean
Well Logging Lectures (Prepared by Dr. Fadhil S. Kadhim)
The resistivity of a mixture of clay with some non – conductive mineral (quartz for example)
will depend on clay resistivity and clay content. If the mixture has no porosity, then it can be
expressed by the following an Archie – type formula:
Rcla y
Rt
(Vcla y ) b
In case of low porosity, some formation water will exist, and so the resistivity will be lower also.
Therefore shale volume can be calculated by the following equation:
Rt 1b
Vsh ( )
Rclay
The above equation is used in case of high to moderated values of porosities, but in general
form the following formula will be used:
Rclay Rmax Rt
1/ b
Vsh
Rt ( R max Rclay )
Where: Rmax is the maximum resistivity reading in the clean hydrocarbon bearing interval, 1/b is equal
to one when (Rt/Rclay) ≥ 0.5 or equal to {0.5/(1- Rt/Rclay)} when Rt/Rclay< 0.5 .
Well Logging Lectures (Prepared by Dr. Fadhil S. Kadhim)
Double Clay Indicators
The Density – Neutron cross plot is almost the best technique to determine clay content
due it is less dependent on lithology, less dependent on fluid type in porous media and badly
washed out well bores. It is better to use it in gauge boreholes. The uncertainty came from the
:highly under-compacted formation.
The density – neutron method can be used to calculate the clay volume as the distance, the
input data falls between the clay point, and the clean line as illustrated in the following Figure
and equation:
( C1 C 2 )( N N 1 ) ( C1 )( N 2 NC1 )
Vsh
( C 2 C1 )( Nclay N 1 ) ( clay C1 )( NC1 NC 2 )
Where:-
ρC1 & ρC: Clean density readings @ point 1&2.
ρclay: Clay density.
ΦNC1 & ΦNC1: Clean neutron readings @ point 1&2.
ΦNclay: Neutron @ clay point.
Well Logging Lectures (Prepared by Dr. Fadhil S. Kadhim)
Neutron – density cross-plot (Schlumberger, 2008)
Well Logging Lectures (Prepared by Dr. Fadhil S. Kadhim)
Density – Acoustic cross-plot technique is also can be used to get Vclay, which is characterized
by less dependent on Lithology and less dependent on fluid type in porous media. It is better to
use this method in gauge boreholes. The uncertainty came from badly washed out wellbores and
highly under-compacted formation (shallow overpressures). The following Equation can be used
to calculate clay volume by neutron – acoustic method:
( C1 C 2 )( son son1 ) ( C1 )( sonC 2 sonC1 )
Vsh
C 2
( C1 )( sonclay sonC1 ) ( clay C1 )( sonC1 son )
C2
Where:-
Sonc1 & Sonc2 : Clean sonic readings @ point 1&2.
Sonclay : Sonic reading @clay point.
The results are shown from the following figure, from which we can made the decision that the
best method to calculate clay volume in the studied oil field is by the corrected reading of gamma
ray tool.
It is the better one due to high washout intervals along the formations which affect on the
calculations of clay volume by the other methods especially in shally formations, from other side
gamma ray had been measured by spectral gamma ray tool which discount the effect of Uranium
and give natural gamma reading.
Well Logging Lectures (Prepared by Dr. Fadhil S. Kadhim)
Well Logging Lectures (Prepared by Dr. Fadhil S. Kadhim)
Well Logging Lectures (Prepared by Dr. Fadhil S. Kadhim)
Well Logging Lectures (Prepared by Dr. Fadhil S. Kadhim)
Clay Types Distribution
Shaliness is known by its effect on the characteristic of the logging tools and on the
computation of the most important factor of well logging interpretation process i.e. effective
porosity. So the occurrence of shale in reservoir rocks can result in erroneous of water saturation
values that have been carried out from the interpretation of well logging data .
Structural, laminated, dispersed, and any combination of these models can represent the main
types of clay distribution. The effect of the first one is where the shale grains replace some of the
sand grains, in this case the matrix density will be change but the porosity doesn’t change. The
effect of the second one is as thin layers of shale in the matrix which replace both the matrix and
porosity, so there are changes in matrix density and porosity value. The third one has dispersed clay
minerals which fill in the intergranular pore space i.e. it reduce the value of effective porosity and
doesn’t change the matrix. The following figure shows the physical effects of shale minerals
distribution on porosity
Well Logging Lectures (Prepared by Dr. Fadhil S. Kadhim)
Influence of clay-mineral distribution on effective porosity
Well Logging Lectures (Prepared by Dr. Fadhil S. Kadhim)
The most common types of clay minerals that have been found in sedimentary rocks are kaolinite,
chlorite, illite and smectite, the following figure shows the typical Scanning Electron Microscopy
(SEM) image of these clays minerals. Each type has its own unique features and can create specific
problem for formation evaluation. Several effects of clays presence reservoir are:
1. Reduction of effective porosity and permeability.
2. Migration of fines whenever clay minerals turn loose, migrate and plug the pore throat that
cause further reduction in permeability.
3. Water sensitivity whenever clays start to hydrate and swell after contact with water (mud
filtrate) which in turn cause reduction in effective porosity and permeability.
4. Acid sensitivity whenever acid reacts with iron-bearing clays to form a gelatinous precipitate
that clogs pore throat and reduce permeability.
5. Influencing logging tools response.
Well Logging Lectures (Prepared by Dr. Fadhil S. Kadhim)
SEM image of four types of clays minerals common found in reservoir rock
Well Logging Lectures (Prepared by Dr. Fadhil S. Kadhim)
Thomas and Stieber (1975) proposed a shale distribution model that included shale configurations,
sand fraction and sand porosity based on data from gamma ray and porosity. The following Figure
shows the general distribution of shale in sands. Knowing shale distribution can improve the
characterization and interpretation of shaly sand reservoirs because it dictates which approach or
application is suitable for a particular reservoir
Shale distribution model based on volume of shale (Vsh) calculated from gamma ray and porosity logs data
Well Logging Lectures (Prepared by Dr. Fadhil S. Kadhim)
Vclay = Vdis + Vlam + Vstr = 1
Where:-
Vlam = (Фmax – Фe)/Фmax
Above Equation had used with two conditions:
1. If Vlam < Vclay , then the model dispersed/laminated had used and :
Vlam = (Vclay + Фe - Фmax) / (1-Фmax).
Vstr = 0
Vdis = Vclay - Vlam
1. If Vlam > Vclay the laminated/structural model had used and :
Vdis = o
Vstr = Vclay - Vlam
Where:-
Vlam: Laminated clay volume.
Vstr: Structural clay volume.
Vdis: Dispersed clay volume.
Well Logging Lectures (Prepared by Dr. Fadhil S. Kadhim)
