Dolomite Perspectives on a Perplexing Mineral

Stratigraphic Traps I. Tulsa: 
American Association of Petroleum Geologists,
AAPG Treatise of Petroleum Geology, Atlas of Oil and 
Gas Fields (1990): 1–37.
39. Land LS: “Failure to Precipitate Dolomite at 25°C from 
Dilute Solution Despite 1000-Fold Oversaturation
After 32 Years,” 
Aquatic Geochemistry 4, nos. 3–4 
(September 1998): 361–368.
40. Vasconcelos C and McKenzie JA: “Microbial Mediation 
of Modern Dolomite Precipitation and Diagenesis Under 
Anoxic Conditions (Lagoa Vermelha, Rio de Janeiro, 
Brazil),” 
Journal of Sedimentary Research 67, no. 3 
(May 1997): 378–390.
41. Sánchez-Román M, Vasconcelos C, Schmid T, Dittrich M,
McKenzie JA, Zenobi R and Rivadeneyra MA: “Aerobic 
Microbial Dolomite at the Nanometer Scale: Implications 
for the Geologic Record,” 
Geology 36, no. 11 
(November 2008): 879–882.
42. Vasconcelos C, McKenzie JA, Warthmann R and
Bernasconi SM: “Calibration of the 
δ
18
O Paleo-
thermometer for Dolomite Precipitated in Microbial 
Cultures and Natural Environments,” 
Geology 33, no. 4 
(April 2005): 317–320.
43. Roberts JA, Bennett PC, González LA, Macpherson GL 
and Milliken KL: “Microbial Precipitation of Dolomite in 
Methanogenic Groundwater,” 
Geology 32, no. 4 
(April 2004): 277–280.
44. Ramamoorthy R, Boyd A, Neville TJ, Seleznev N, Sun H, 
Flaum C and Ma J: “A New Workflow for Petrophysical 
and Textural Evaluation of Carbonate Reservoirs,” 
Transactions of the SPWLA 49th Annual Logging 
Symposium, Edinburgh, Scotland, May 25–28, 2008, 
paper B.
>
Carbonate Advisor sequential workflow. The first step incorporates results 
from tools that provide lithology and porosity information: spectroscopy, 
density, thermal neutron, epithermal neutron, photoelectric factor, NMR and 
gamma ray. The data are examined by petrophysicists and serve as inputs to 
the next step, which involves evaluation of the pore system and permeability 
using NMR 
T
2
distribution or image logs. Next, relative permeability and 
saturation are obtained from array laterolog or array induction resistivity 
measurements. Also, core data, such as grain density, porosity and 
permeability, can be added to the analysis.
MattV_ORAUT09_Fig_12
Total porosity, vol %
10
5
10
4
10
3
10
2
10
1
r= 0.99
r= 0.99
10
0
10
-1
Permeability
, md
10
5
10
4
10
3
10
2
10
1
10
0
10
-1
0
5
10
15
20
25
30
Permeability
, md
r= 0.99
A
Planar-s dolomite
Planar-e dolomite
B
Nonplanar dolomite
Spectroscopy
Density
Thermal neutron
Epithermal neutron
Photoelectric factor
NMR
Gamma ray
Lithology
and porosity
Core data
NMR 
T
2 
distribution
Image log
Laterolog resistivity
Induction resistivity
Grain density
Porosity
Permeability
Pore system
and permeability
Relative permeability
and saturation
26678schD5R1.indd 10
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42
Oilfield Review
and dolomite, can be a rather convoluted pro-
cess. Neutron porosity measurements must be 
corrected for the rock matrix. If the matrix con-
tains only dolomite or only calcite, the porosity 
transform is fairly simple. But if the rock
contains a mixture of both minerals, then the cor-
rect proportions of each must be determined to
accurately calculate porosity values. 
Matrix complexity also affects the computa-
tion of density porosity because the equation 
used to convert porosity from bulk density mea-
surements requires matrix density as an input. 
Should the rock be a mix of dolomite and calcite, 
the porosity calculations will be incorrect unless 
an accurate matrix density is obtained. Thus, 
underestimating or ignoring the presence of 
dolomite can lead to low computed porosity val-
ues that mask potentially productive zones. 
In some cases, calcite and dolomite can be 
readily distinguished using PEF data from a 
Litho-Density tool.
45
The PEF matrix value for 
pure sandstone is 1.81; for dolomite it is 3.14 and 
for limestone it is 5.08. From the PEF measure-
ment, the percentage of dolomite can be directly 
calculated if the matrix contains only two miner-
als; unfortunately, rocks often contain a mixture 
of minerals. Adding to the complexity is the fact 
that even small concentrations of relatively com-
mon minerals, such as siderite (with a PEF of 
14.7), pyrite (with its PEF of 16.97) or anhydrite 
(with a PEF of 5.03), distort the measured PEF 
values and shift the value toward calcite. There 
are too many unknowns in this case to determine 
the matrix type and the matrix porosity from a 
standard logging suite. 
An additional problem with using PEF for 
lithology determination is the effect of barite, 
which is commonly added as a weighting material 
to drilling mud systems. Barite, with its PEF of 
266.82, overwhelms other PEF measurements in 
these mud systems. 
The ECS elemental capture spectroscopy tool 
can help to fill some of the gaps in the interpreta-
tion process. Neutron capture spectroscopy mea-
sures elemental yields of minerals found in the 
formation. Recent advances in elemental capture 
spectroscopy have resulted in improved magne-
sium yield measurements to help petrophysicists 
quantify the amount of dolomite and other miner-
als contained in reservoir rocks. ECS measure-
ments also provide yields of calcium and sulfur, 
which are critical for most carbonate lithology 
determination. In addition, ECS spectroscopy 
data provide relative yields of elements such as 
iron, silicon, barium, hydrogen and chlorine. ECS 
data thus reduce uncertainty in porosity mea-
surements derived from basic logging suites.
Pore geometry comes into play when evaluat-
ing reservoir quality and fluid-flow properties. For 
the Carbonate Advisor system, the pores are parti-
tioned into different types based on pore-throat 
size. Partitioning is based on NMR transverse 
relaxation time (T
2
) distributions augmented by 
borehole images. Even though NMR is sensitive to 
pore-body size distribution, the Carbonate Advisor 
system calibrates the results to appear as pore- 
throat size distribution. Two cutoffs are applied to 
T
2
distributions relating relaxation time to pore- 
size distribution 
(above left)
. 
The short cutoff defines the microporosity
fraction, and the long cutoff defines the macropo-
rosity fraction, while the mesoporosity fraction 
falls between the two. The macroporosity compo-
nent is also determined from borehole images by 
converting the resistivity image into a porosity 
image and extracting the fraction of large pores 
present. From the three porosity partitions, eight 
petrophysical pore system classes are identified. 
Matrix permeability is also estimated using
transforms optimized for each pore class. 
Permeability estimates can be validated or cali-
brated using data from formation testing tools or 
core measurements.
Simultaneous solutions of saturation and rel-
ative permeability are obtained through forward 
modeling. The full model accounts for radial vari-
ations in resistivity caused by the distribution of 
drilling fluids that invaded the formation, which 
influences resistivity tool response. Both array 
induction and array laterolog measurements can 
be used for the analysis. With their multiple 
depths of investigation, the resistivity tools can 
accurately characterize the invasion front, which 
is inverted to determine imbibition relative- 
permeability curves. The saturation front and 
salinity front are simultaneously solved to deter-
mine fractional flow, relative permeability versus
saturation and true formation resistivity. 
The Carbonate Advisor system was recently 
put to the test in a reservoir in northern Kuwait. 
Reservoir evaluation in this area can be compli-
cated by drilling fluids weighted with barite, used 
to increase drilling safety in fields known for high 
concentrations of hydrogen sulfide and high res-
ervoir pressures.
46
Geoscientists with the opera-
tor Kuwait Oil Company (KOC) found that zones 
of improved porosity and permeability were asso-
ciated with dolomitization in this field. The quan-
tification of dolomite content was therefore 
important in classifying reservoir quality. 
However, the estimation of dolomite content 
from conventional measurements can be hindered 
by a variety of factors, such as barite mud effects, 
complex lithologies and sensitivity of logging tool 
measurements to dolomite, as well as differences 
in each tool’s vertical resolution and depth of 
investigation. To overcome these formation evalua-
tion challenges, an ECS tool was used to obtain 
elemental relative yields for mineralogy computa-
tion. Magnesium measured by this tool was a key 
element for dolomite quantification in this com-
plex reservoir. The CMR combinable magnetic 
resonance tool was also run to obtain pore geome-
try information. The Carbonate Advisor system 
provided formation evaluation results that closely 
agree with core data 
(next page)
.
>
Pore geometries. Total porosity (
top) can be 
divided into different types of pores based on 
NMR and image log data. Micropores, with 
pore-throat diameters less than 0.5 μm, usually 
contain mostly irreducible water and little 
hydrocarbon. Mesopores, with pore-throat 
diameters between 0.5 and 5 μm, may contain 
significant amounts of oil or gas in pores above 
the free-water level (FWL). Macropores, with 
throats measuring more than 5 μm in diameter, 
are responsible for prolific production rates in 
many carbonate reservoirs but often provide 
pathways for early water breakthrough, leaving 
considerable gas and oil behind in the mesopores 
above the FWL. The three different types of pores 
can be further divided into eight pore system 
classes (
bottom).
MattV_ORAUT09_Fig_13
Total porosity
Micro-
porosity
All pores
< 50 to 100 
µm
have the same 
T
2
Blind to pores
smaller than
tool buttons
100%
macroporosity
100%
microporosity
100%
mesoporosity
Image
response
Nonvug porosity
Vug
porosity
NMR
response
φ for
distribution
< short