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Copyright 2001, Society of Petroleum Engineers Inc.
This paper was prepared for presentation at the SPE Latin American and Caribbean PetroleumEngineering Conference held in Buenos Aires, Argentina, 25–28 March 2001.
This paper was selected for presentation by an SPE Program Committee following review ofinformation contained in an abstract submitted by the author(s). Contents of the paper, aspresented, have not been reviewed by the Society of Petroleum Engineers and are subject tocorrection by the author(s). The material, as presented, does not necessarily reflect anyposition of the Society of Petroleum Engineers, its officers, or members. Papers presented atSPE meetings are subject to publication review by Editorial Committees of the Society ofPetroleum Engineers. Electronic reproduction, distribution, or storage of any part of this paperfor commercial purposes without the written consent of the Society of Petroleum Engineers isprohibited. Permission to reproduce in print is restricted to an abstract of not more than 300words; illustrations may not be copied. The abstract must contain conspicuousacknowledgment of where and by whom the paper was presented. Write Librarian, SPE, P.O.Box 833836, Richardson, TX 75083-3836, U.S.A., fax 01-972-952-9435.
AbstractThe Santa Barbara Field is located in the North MonagasArea, Eastern Venezuela Basin. Reservoirs in the area arecharacterized by high initial temperature and pressure, andhigh initial production rates. The drive mechanism is solutiongas drive and fluid expansion, with reservoir pressuredeclining rapidly. The hydrocarbon column varies from a gas-condensate cap at the top of the structure to heavy oil at thebottom. A detailed petrophysical model was necessary tooptimize the secondary recovery processes implemented in thefield.
The petrophysical characterization incorporated theanalysis of the complex variations in pore and pore throatgeometry that control initial and residual fluid distribution andfluid flow through the reservoirs. Conventional porosity andpermeability, mercury injection capillary pressure, relativepermeability, and mineralogical data were used to characterizethe reservoir pore systems into rock types having similar flowand storage capacity. Water Saturation, all of which isconsidered immobile, was found to be dependent on rock type,with pore throat being the dominant control on the flowcharacteristics of the reservoirs.
Mercury injection capillary pressure data provided usefulinformation about effective pore throat radii, which weresemi-quantitatively related to several reservoir responses, suchas permeability, porosity, irreducible water saturation, and acapillary pressure profile or pore throat type curve. Plots ofpore throat obtained from empirical equations versus porethroat estimated from capillary pressure tests showed that thedominant interconnected pore system that controls flow in thereservoirs is best represented by the pore throat on a capillarypressure curve corresponding to 45% mercury saturation.
Rock types were considered for the definition of injectionintervals, and were also used to construct stratigraphic flowprofiles, which were validated with production logs. Groupingsimilar rock types was found to be an excellent method fordefining simulation layers. Rock type areal distribution mapswere constructed to help delineate the best reservoir areas.
The characterization of a reservoir into rock types in orderto determine flow units effectively integrates geological,petrophysical and production data into descriptions of zoneswith similar flow characteristics, and is fundamental for thedevelopment of secondary recovery processes.
IntroductionThe Santa Barbara Field is located in the North MonagasArea, Eastern Venezuela Basin (Fig. 1). The complex poresystem present in the area made necessary a detailedpetrophysical model based on the study of pore and porethroat geometry, for tertiary and cretaceous formations.
Fig. 1-Relative location map of the Santa Barbara Field
Pore throat size may be estimated from routine coreporosity and permeability data (at ambient conditions).Combining these data with mercury injection capillarypressure results, Winland (1972) developed an empiricalrelationship between porosity, air permeability and poreaperture corresponding to a mercury saturation of 35% (R35).The Winland equation was used and published by Kolodzie(1980) and is given below:
SPE 69458
Rock Typing: A Key Approach for Petrophysical Characterization and Definition of FlowUnits, Santa Barbara Field, Eastern Venezuela BasinJ. C. Porras, PDVSA EPM, and O. Campos, PDVSA-Intevep
SANTA BARBARA
CARITO MULATA
U C 1 E
F UC 13
F N-9 1
FUL 1
F UL 1
F UL 2
FUL 1 0
F U 1
MU C 4 5
F UL 1 6
F UL 2 1
M
1 1M UC 3
S BC 1 9
C-22 E
1
SB 3S BC 1 8
S BC 4
S BC 1
PI C1 E
CASUPALTONORO
EL FURRIAL
BUC A RE D
B U C R E E
B
OSQ U D
PIC E
BOS E-F BO SQUE-
B
E
PI C 5E C 2 E
PI C 3 E
T C TN OR T E
TACAT
PIRITAL
ΝΝΝΝ
MonagasMonagas
2 J.C.PORRAS, O.CAMPOS SPE 69458
Log(R35) = 0.732+0.588Log(kair)-0.864Log(φ)
Where: R35 is the pore aperture radius (microns)corresponding to the 35th percentile, kair is uncorrected airpermeability (md), and φ is porosity (%).
R35 pore throat radius is defined as the pore throat sizefrom mercury injection capillary pressure data where the non-wetting fluid (mercury) saturates 35% of the porosity. R35pore throat radii is a function of entry size and pore throatsorting, and is a good measure of the largest connected porethroats in a rock with intergranular porosity (Hartmann andCoalson, 1990).
In 1992, Pitmann, based on Winland’s work, developedR35-type equations for pore throats corresponding to mercurysaturations from 10% to 75% (Fig. 2).
Fig. 2-Pitmann’s equations for mercury saturations of 10% to 75%
In the present study, conventional core porosity andpermeability data from 17 key wells, and mercury injectioncapillary pressure data from 11 of them, were used todetermine the pore throat model.
Pore Throat Radius AnalysisIn order to determine the most appropriate equation forestimating pore throat size in the study area, plots of porethroat radius from capillary pressure data versus pore throatradius obtained from Pitmann’s equations were constructed(Fig. 3). As shown in the figure, the R45 equation best honorsand reproduces core capillary pressure data, and was thereforeselected to estimate pore throat radius in the area. Pitmann’sR45 equation is given below:
Log(R45) = 0.609+0.608Log(kair)-0.974Log(φ)
Where: R45 is the pore aperture radius (microns)corresponding to the 45th percentile, kair is uncorrected airpermeability (md), and φ is porosity (%). R45 pore throatradius can then be defined as the pore throat size from
capillary pressure data where the non-wetting fluid (mercury)saturates 45% of the porosity.
Fig. 3-Plots of pore throat radii estimated from capillary pressuredata versus pore throat radii calculated using Pitmann’s R45equation
Once the equation to be used in the area was determined,R45 pore throat values were calculated for data at bothambient and reservoir conditions. Crossplots were constructedto obtain the corresponding relationships (Fig. 4).
Fig. 4-Pore throat radius at reservoir conditions versus porethroat radius at ambient conditions, for Tertiary and CretaceousFormations
Pore Throat Radius Versus Water SaturationThe absence of an active aquifer in the area, as well as theenormous size of the hydrocarbon column, make the water inthe reservoirs immobile. Water saturation variations, as shownin resistivity logs, are then dependent on rock type and notdependent on changes in fluid volume. Based on this premise,R45 values were plotted against water saturation (Fig. 5), inorder to determine a possible relationship between bothproperties.
The results shown in figure 5 indicate that water saturationvalues are directly associated to the geometry of the poresystem, and can be used in areas like the Santa Barbara Field,
LogR10 = 0.459 + 0.500*LogKair - 0.385*LogΦLogR15 = 0.333 + 0.509*LogKair - 0.344*LogΦLogR20 = 0.218 + 0.519*LogKair - 0.303*LogΦLogR25 = 0.204 + 0.531*LogKair - 0.350*LogΦLogR30 = 0.215 + 0.547*LogKair - 0.420*LogΦLogR35 = 0.255 + 0.565*LogKair - 0.523*LogΦLogR40 = 0.360 + 0.582*LogKair - 0.680*LogΦLogR45 = 0.609 + 0.608*LogKair - 0.974*LogΦLogR50 = 0.778 + 0.626*LogKair - 1.205*LogΦLogR55 = 0.948 + 0.632*LogKair - 1.426*LogΦLogR60 = 1.096 + 0.648*LogKair - 1.666*LogΦLogR65 = 1.372 + 0.643*LogKair - 1.979*LogΦLogR70 = 1.664 + 0.627*LogKair - 2.314*LogΦLogR75 = 1.880 + 0.609*LogKair - 2.626*LogΦ
R35-Pc Vs. R35-Pitmann
0
2
4
6
8
10
0 2 4 6 8 10
R35-Pc
R35
-Pitm
ann
R40-Pc Vs. R40-Pitmann
0
2
4
6
8
10
0 2 4 6 8 10
R40-Pc
R40
-Pitm
ann
R45-Pc Vs. R45-Pitmann
0
2
4
6
8
10
0 2 4 6 8 10
R45-Pc
R45
-Pitm
ann
R50-Pc Vs. R50-Pitmann
0
5
10
15
20
25
30
0 5 10 15 20 25 30
R50-Pc
R50
-Pitm
ann
1e-01
1e+00
1e+01
1e+02
R45
(ft
)
SBC-21 SBC-24 SBC-29 SBC-33 SBC-35 SBC-44 SBC-50 SBC-51 SBC-56 SBC-57 SBC-7 SBC-96
1e-01
1e+00
1e+01
1e+02
R45
(ft
)
1e-02 1e-01 1e+00 1e+01 1e+02R 45 (f t )
1e-02
0.0 2.9 5.7 8.6 11.4 14.3
1e-02
1e-02 1e-01 1e+00 1e+01 1e+02R 45 (f t )
0.02.44.87.19.5
11.9
1e-01
1e+00
1e+01
1e+02
R45
(ft
)
SBC-21 SBC-24 SBC-50 SBC-57 SBC-70 SBC-90 SBC-96
1e-01
1e+00
1e+01
1e+02
R45
(ft)
1e-02 1e-01 1e+00 1e+01 1e+02R45 (f t)
1e-02
0.0 1.7 3.3 5.0 6.6 8.3
1e-02
1e-02 1e-01 1e+00 1e+01 1e+02R45 (f t)
0.01.83.65.47.29.0
Tertiary Cretaceous
SPE 69458 ROCK TYPING: A KEY APPROACH FOR PETROPHYSICAL CHARACTERIZATION 3
where the mobile fluid is hydrocarbon, and the water existentin the formation can be considered to be irreducible.Irreducible water saturation was obtained from mercuryinjection capillary pressure data (Fig. 6).
Fig. 5-Plots of pore throat radius (y-axis) vs. water saturation (x-axis), showing the relation between both properties
Fig. 6-Mercury injection capillary pressure data from a key well inthe Santa Barbara Field
Spectral Gamma Ray AnalysisClay type played an important role in the definition of rocktypes. Two main clay types were present in the area and theirdifferentiation was based in the analysis of spectral gamma raylogs run to the cores. Thorium versus Potassium crossplotswere constructed (Fig. 7), which showed the changes in claytype. High thorium/potassium values indicate Kaolinite-typeclays, while low thorium/potassium values indicate Illite-typeclays.
Fig. 7-Plot of Thorium (ppm) versus Potassium (%) showingdifferent trends for kaolinite and illite-type clays
Once calibrated with cores, Spectral Gamma Ray Logswere used to determine clay types and to detect possibleformation changes (Fig. 8).
Fig. 8-Spectral Gamma Ray log showing mineralogical changebetween Tertiary and Cretaceous formations
Determination of PorosityCompressibility tests performed on cores indicate thatconfining pressure has a minor effect on porosity (Fig. 9).Porosity core data at reservoir conditions were available, andused in the core-log correlation. Porosity was calculated fromlogs and calibrated with core data.
Fig. 9-Data from compressibility tests in a key well of the SantaBarbara Field. Note the little decrease in porosity as pressureincreases
Determination of Rock TypesReservoir rock was classified based on R45 pore throat radius,which is a dominant control on the permeability and flowcharacteristics of the reservoirs. The reservoir rock wasdivided into five petrophysical categories:
Megaporous, defined by a pore throat radius > 10 micronsMacroporous, defined by a pore throat radius between 2.5
and 10 micronsMesoporous, defined by a pore throat radius between 0.5
and 2.5 micronsMicroporous, defined by a pore throat radius between 0.2
and 0.5 microns (microporous)Nannoporous, defined by a pore throat radius < 0.2
microns
Areas 1/3/5 Areas 2/4
1
10
100
1000
10000
0.010.020.030.040.050.060.070.080.090.0100.0Mercury Saturation, % Pore Space
Inje
ctio
n Pr
essu
re, p
si
POTA (%)
THO
R (p
pm)
Kaolinite
Illite
15800
15750
15700
15650
15600
15550
TPRA
1 100TPRA
( )
0.1 100TURA
( )
0.01 100UPRA
( )
lgp_Area_18_
lgp_Area_22_
URANIO
TORIO
-6 6POTA ( % )
MD1 : 600ft0 150CGR
( gAPI )
0 150SGR
( gAPI )
6 16CALI( in )
PossibleCretaceous
PossibleTertiary
8.0
8.5
9.0
9.5
10.0
10.5
11.0
11.5
12.0
000 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000
Confining Pressure (psi)
Por
osity
(%)
4 J.C.PORRAS, O.CAMPOS SPE 69458
Pore throat radii lines obtained using Pitmann’s R45equation were superimposed on porosity versus permeabilityplots and used in the the recognition of rock types (Fig. 10).
Fig. 10-Porosity versus permeability plot showing R45 pore throatlines, and rock type classification
Sedimentological analysis from thin sections and ScanningElectronic Microscope were used to help visualize thedifferent rock types. (Fig. 11).
Fig. 11-Thin section and SEM photographs for different rock types
Rock types can be semi-quantitatively related to severalreservoir response characteristics useful in formationevaluation, such as permeability to porosity ratio, immobilewater saturation, initial production rates, and a capillarypressure profile (Fig. 12).
Fig. 12-Capillary pressure profile for different rock types
Determination of PermeabilityOnce porosity was estimated, and R45 pore throat radius wasobtained from water saturation, permeabilty was calculatedusing Pitmann’s R45 equation and calibrated with core data.
Five different equations to estimate permeability in thearea were obtained from the porosity versus permeabilityplots, by rock type, at reservoir conditions (Fig. 13).
Fig. 13-Porosity versus permeability plots, by rock type
Based on these equations, a sensitivity analysis wasperformed in order to observe the variation of permeabilitywith efective porosity by rock type (Fig. 14).
Fig. 14-Effective porosity versus permeability relations fordifferent rock types
Definition of Reservoir Flow UnitsA petrophysical flow unit is defined as an interval of sedimentwith similar petrophysical properties such as porosity,permeability, water saturation, pore throat radius, storage andflow capacity, that are different from the intervals immediatelyabove and below. Petrophysical flow units are usually groupedto define containers. Rock types having similar flow capacitywere grouped and used in the detemination of reservoir flowunits (Fig. 15).
A detailed sedimentological study had been previouslydone in the study area, and the integration of these results withthe petrophysical analysis proved to be a valuable tool in thedefinition of simulation layers.
0.001
0.01
0.1
1.
10.
100.
1000.
10000.
0 0.05 0.1 0.15 0.2 0.25 0.3
Porosity
Perm
eabi
lity
(md)
0.1
0.5
2.5
5
10
30
Meg
aM
acro
Mes
oN
anno
Mic
ro
Pore
Thr
oat r
adiu
s (m
icro
ns)
0.2
1
Mercury Saturation, %
Cap
illar
y Pr
essu
re, p
si
1
10
100
1000
10000
0102030405060708090100
21 3 4
1: Megaporous 2: Macroporous3: Mesoporous 4: Microporous
Mesoporous
Megaporous
Microporous
Macroporous
Megaporous
NannoporousMicroporous
MesoporousMacroporous
0.00
0.01
0.10
1.00
10.00
100.00
1000.00
10000.00
0.00 0.05 0.10 0.15 0.20 0.25PHIE (fraction)
K (m
d)
MEGAMACROMESOMICRONANNO
SPE 69458 ROCK TYPING: A KEY APPROACH FOR PETROPHYSICAL CHARACTERIZATION 5
Fig. 15-Sample well showing the adjustment of flow units 9,10,11into flow units 12,13,14 after regrouping by rock types
A total of 21 layers were defined in the sedimentologicalstudy (14 for Tertiary, and 7 for Cretaceous formations). Withthe introduction of the rock type concept, the tops of thesimulation layers were re-adjusted to obtain a total 12 units(10 for Tertiary, and 2 for Cretaceous formations), improvingsimulation results (Fig. 16).
Fig. 16-Comparison between previous and adjusted simulationflow units after grouping by rock types, for both Tertiary andCretaceous formations
Rock Type Distribution MapsRock type distribution maps (Fig. 17) were construted usinginformation from cored wells and from wells evaluated usingthe core-log correlation determined in this study. Figure 17shows the occurence of the different rock types, in percentage,for simulation flow unit 6. Best reservoir areas are circled,where the highest frequency of megaporous and macroporousrock types occur.
Fig. 17-Areal rock type distribution maps for simulation unit 6,showing best reservoir areas (circled)
Conclusions 1. Reservoir rock was classified in five petrophysical
rock types, based on pore throat radius. 2. Different rock types have different quality in terms of
flow capacity and recovery efficiency. 3. A definite relation between water saturation, all of
which is immobile, and pore throat radius, was found for bothTertiary and Cretaceous formations
4. Rock types are an important parameter to be used inthe definition of simulation layers and reservoir flow units.
5. Rock type areal distribution maps are an excellent toolto help delineate the best reservoir areas.
12
14
1310
9
11
1
2
4
109
5
76
3
8
12
17
11
1918
21
151413
16
20
1
2
4
10
9
5
76
3
8
12
11
Tert
iary
Cre
tace
ous
PREVIOUSFLOWUNITS
ADJUSTEDFLOWUNITS
416000 418000 420000 422000 424000 426000 428000
1064000
1066000
1068000
0 2000 4000
0
70
Rock Type: Megaporous
416000 418000 420000 422000 424000 426000 428000
1064000
1066000
1068000
0 2000 4000
Rock Type: Macroporous
0
84
416000 418000 420000 422000 424000 426000 428000
1064000
1066000
1068000
0 2000 4000
Rock Type: Mesoporous
0
70
416000 418000 420000 422000 424000 426000 428000
1064000
1066000
1068000
0 2000 4000
Rock Type: Microporous
0
65
416000 418000 420000 422000 424000 426000 428000
1064000
1066000
1068000
0 2000 4000
Rock Type: Nannoporous
0
70
6 J.C.PORRAS, O.CAMPOS SPE 69458
Nomenclature kair = uncorrected air permeability, md==========φ=== core porosity, %========φe = effective porosity, fraction R35 = pore aperture radius (35th percentile), µ R45 = pore aperture radius (45th percentile), µ
AcknowledgmentsThe authors would like to thank PDVSA EPM for permissionto publish this paper.
References1. Coalson, E. B., Hartmann, D. J., and Thomas, J. B., 1985,
Productive Characteristics of Common Reservoir PorosityTypes: S. Texas Geol. Soc. Bull., v. 25, n. 6, pp. 35-51.
2. Gunter, G.W., Finneran, J.M., Hartmann, D.J. and Miller J.D.,Early Determination of Reservoir Flow Units Using anIntegrated Petrophysical Method, SPE 38679, Annual TechnicalConference and Exhibition, pp. 373-380.
3. Hartmann, D. J. And Thomas J. B., Basic PetrophysicalMethods, Petrophysics XXVIII, Amoco Production Company,Tulsa, Oklahoma.
4. Hartmann, D. J. and Coalson, E. B., 1990, "Evaluation of theMorrow Sandstone in Sorrento Field, Cheyenne County,Colorado”, in S. A. Sonnenberg, L. T. Shannon, K. Rader, W. F.Von Drehl, y G. W. Martin (Editors), Morrow Sandstones ofSoutheast Colorado and Adjacent Areas, The Rocky MountainAssociation of Geologists, Denver, Colorado, pp. 91 - 100.
5. Kolodzie, S., Jr., 1980, Analysis of Pore Throat Size and Use ofthe Waxman-Smits Equation to determine OOIP in SpindleField, Colorado: Society of Petroleum Engineers, 55th AnnualFall Technology Conference, SPE-9382, 10 pp.
6. Pittman, E. D., 1992, Relationship of Porosity and Permeabilityto Various Parameters Derived from Mercury InjectionCapillary Pressure Curves for Sandstone: AAPG Bulletin, v. 76,No. 2, pp. 191 - 198.
7. Porras, J.C., 1996, Caracterización Petrofísica del Campo CaritoNorte, Corpoven S.A.
8. Porras, J.C., 1998, Determination of Rock Types from PoreThroat Radius and Bulk Volume Water, and their Relations toLithofacies, Carito Norte Field, Eastern Venezuela Basin, 39th
SPWLA Annual Symposium, Paper OO.9. Winland, H. D., 1972, "Oil Accumulation in Response to Pore
Size Changes, Weyburn Field, Saskatchewan," AmocoProduction Research Report No. F72-G-25.