SPE-95760-MS-P

Copyright 2005, Society of Petroleum Engineers, Inc. This paper was prepared for presentation at the 2005 SPE Annual Technical Conference and Exhibition held in Dallas, Texas, U.S.A., 9-12 October 2005. This paper was selected for presentation by an SPE Program Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material, as presented, does not necessarily reflect any position of the Society of Petroleum Engineers, its officers, or members. Papers presented at SPE meetings are subject to publication review by Editorial Committees of the Society of Petroleum Engineers. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of the Society of Petroleum Engineers is prohibited. Permission to reproduce in print is restricted to a proposal of not more than 300 words. Illustrations may not be copied. The abstract should contain conspicuous acknowledgment 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.

Abstract The phenomenon of variation of fluid properties with depth was investigated in many of the Gulf of Suez and Western Desert fields of Egypt. This phenomenon primarily exists in reservoirs with large closures (large thickness or high dip angle, even for thin formations) where the gravitational forces have a significant effect on the overall composition of the system over the geological time.1,2,3 The phenomenon often exists also in high shrinkage oils, volatile oils4 and rich gas condensates as well as in black oils. Such compositional grading can have significant influences on various aspects of reservoir development. This must be taken into account during estimation of the stock-tank oil initially in place of such fields and well/reservoir behavior evaluation. This paper presents an engineering evaluation for validating PVT lab analyses of many fluid samples collected at different depths from several reservoirs of different fields. As a result of this evaluation, the valid samples were supporting fluid property variation with depth where its properties can be correlated as a linear function of depth. Two methods have been used for correlating the fluid properties with depth. The first method relies only on the experimental PVT data provided by the laboratories while the second method uses an equation of state to predict the fluid properties from the experimentally determined compositional analyses. The second method make use from the advantage that in this particular case the equation of state parameters assigned to each hydrocarbon and pseudo-hydrocarbon component within the oil column should be constant for all valid samples. In this method, the most accurate reservoir fluid composition for one of the valid samples was used to predict the reservoir fluid composition and its corresponding PVT properties at different bottomhole locations. The

prediction procedure is a combination of stream blending and flash liberation processes to estimate the reservoir fluid properties at shallower and deeper depths from the depth of the selected sample. Once the fluid properties of the compositional gradient are developed, the engineer can proceed using either black oil or compositional model to match the history and predict the performance of the reservoir under the acting drive mechanism.

Introduction Compositional variations in reservoir fluid with depth have been observed in many reservoirs within a single oil pool in different places of the world. In light oils (API > 35o), strong compositional grading will occur if the reservoir fluid is near critical. The saturation pressure gradient may be interpreted as the result of gravity-induced fluid component migration that occurs to obtain equilibrium between the chemical and gravity forces.2,5,6 The time necessary to achieve compositional equilibrium (10 million to 1 billion years) is comparable to the geologic lifetime of a typical reservoir.7 Many of the Southern Gulf of Suez fields such as Hilal, Sidki, and GS-365 fields are related to this category. When considering gas injection, one must be aware that compositional effects (such as the development of miscibility) change with depth. In heavier oils, moderately heavy (20 to 30o API), compositional grading is caused by the segregation of asphaltenes, resulting in variation in oil viscosity and the possibility of tar-mat formation. Compositional variation in this case may also influence field development. The presence of highly viscous oil near the oil/water contact has forced production from updip and would be a serious handicap for downdip water injection.7 This is most likely the case of main October Nubia reservoir which is located in the northern part of the Gulf of Suez . In shallow reservoirs and for heavy oils (< 20o API), compositional variation with depth often result from a loss of light ends or from bio-degradation.8,9 Such effects can be inferred from geologic data.7

SPE 95760

Methodology of Investigating the Compositional Gradient Within the Hydrocarbon Column H.H. Hanafy, SPE, and I.S. Mahgoub, SPE, Khalda Petroleum Co.

2 SPE 95760

Two cases of compositional gradient in hydrocarbon column can be exist:

1. Compositional gradient in the light and intermediate fractions (Cl-C6) while the heavy fractions (C7+) remain constant with depth as in the case of Hilal Field.

2. Compositional gradient in both the light and heavy fractions as in the case of Waly field. An accurate history match for reservoirs having such phenomenon are best dealt with 3D black oil or compositional models. The black oil model should be used only for the reservoir fluids which do not or slightly vary in its heavy ends with depth. The compositional model should be used when the heavy ends are significantly vary with depth, or when the light or normal oils are underlain by heavy oil, or when simulating a miscible gas injection process. However, Hanafy proposed several methods for averaging the PVT data for the use in conventional reservoir engineering calculations.10,11 He also approached a method to simplify and approximate the history match in this case using a zero dimensional model.12

Evidences of Compositional Gradient Several evidences supported a compositional gradient within the hydrocarbon column of different reservoirs in different fields. Those evidences will be highlighted in the following field cases.

Hilal Field Case: 1- Gravity Forces. The structural model of both Nukhul and Nubia reservoirs (Figure 1) shows that they are high relief reservoirs. The formations dip angles are in the range of 20 to 30 degrees. The topmost of Nukhul and Nubia formations are 9250 ft and 9700 ft subsea, respectively. These are 1450 ft and 1000 ft above the common field oil-water contact (OWOC) at 10700 ft subsea. However, the Nukhul and Nubia formations have a moderate average thickness of only 120 ft and 320 ft, respectively. 2- Reservoir Fluid Type. The reservoir fluid type is typical of high shrinkage to volatile oils. This can be indicated from the lab analyses of fluid samples collected from both formations. The measured fluid properties are in the following ranges: Oil formation-volume factor, (βob): 1.86 - 2.43 BBL/STB Solution gas-oil ratio, (Rsi): 1280 - 2250 SCF/STB Oil viscosity, (µob): 0.12 - 0.45 cp Bubble-point pressure, (Pb): 3725 -5000 psi Stock tank oil gravity, (API): 33 - 38 Degrees Based on hundreds of laboratory studies, McCain suggested, cutoffs between black and volatile oils. He mentioned that the presence of a volatile oil should be suspected whenever the initial producing gas-oil ratio exceeds about 1750 SCF/STB, or when the stock tank oil gravity is more than 40 API Degree.13,14,15 An oil formation volume factor of 2.0 BBL/STB or greater suggests a volatile oil.14 Laboratory determined compositions of volatile oils will have 12.5 to 30

mole percent heptanes plus. The laboratory analyses of Hilal field samples indicated a heptanes plus fraction in the range 19 to 29 mole percent. Also, volatile oils contain relatively more intermediates (defined as ethane through hexanes) than black oils.13 3- Initial Producing Gas-Oil Ratio. A plot of initial producing GOR versus the mid perfs depth of primary Nukhul and Nubia producers (Figure 2) indicates GOR decreasing with depth which reflects a vertical fluid composition variation. Waly Field Case: 1- Drillstem Test Results. The discovery well was drillstem tested in the Kareem formation at two different sets of perforations that are 100 ft apart where the DST#2 tested interval is shallower than the DST#1 tested interval. The GOR and API gravity tested during the DST'#2 were 1113 scf/stb and 36.3 degree, respectively versus 756 scf/stb and 34..3 degree from the DST#1. This should reflect lighter crude against at the shallower depth.

2- RFT Data. The RFT data in the discovery well shows increase in the oil gradient with depth from 0.26 psi/ft to 0.32 psi/ft (Figure 3).

3- Field Ambient Temperature Pb. The Pb measured at the field ambient temperature of 58 oF during the transferring of two bottom hole samples collected from the DST#1 and DST#2 were 2550 and 2650 psi, respectively. The higher Pb reflects a lighter crude oil for the DST#2 sample.

4- Laboratory PVT Analyses. The PVT analyses for the two bottom hole samples showed that the DST#2 sample has higher βo, Rsi and API gravity than the DST#1 sample while it has lower C7+ molecular weight, C7+ mole percent, oil density and oil viscosity (Table 1). This should reflect lighter crude for the DST#2 sample.

5- Openhole Logs. An original gas oil contact at depth of -6775'ss was predicted from the bubble point pressure versus depth correlation. The depth of this contact was verified by open hole logs and RFT data (Figures 4 & 5). The openhole logs for the Waly well #3 is showing larger separation between the neutron and density logs above the gas-oil contact depth due to the gas effect. October Field Case: 1- Reservoir Thickness. The Nubia formation in the October field has a large thickness of 1000 feet or more but its dip angle is small within the average of 10 degrees. Compositional grading in this case is caused by the segregation of asphaltenes, resulting in variation in oil viscosity and the possibility of tarmat formation. By reviewing the PVT data, an heavy oil contact was detected at depth of 11520 feet subsea. 2- Geological Features Effect. The degree of asphaltenes segregation may be affected by some geological events exist over the geological time and consequently led to different

SPE 95760 3

fluid properties at same depth in different parts of the field. The geological events are such as: a- Vertical isolation due to shale barriers (i.e M-ΙΙ shale). b- Lateral isolation due to faulting. c- Lateral communication due to juxtaposition through fault

planes. d- Communication with offset fields through the aquifer.

Laboratory PVT Data Validation The way to validate the PVT data before using it in establishing a compositional gradient will be covered in this paper through the Hilal field case. The consistency of the laboratory measurements of reservoir fluid properties and its composition versus depth are the main bases of this validation. Three bottomhole samples and ten separator recombined samples have been collected from four wells (A1, A2A, A4, and A6A) at different times and different depths from Nukhul and Nubia formations of the Hilal field. The locations of the sampled wells are referred to on the top Nubia structure contour map presented in Figure 1. Wells A1 and A2A were recompleted to Nukhul after the Nubia wateredout. Well A4 was shut-in in the Nukhul due to high water cut. Well A6A was recompleted to Nubia after the Nukhul gassedout. The differential vaporization analyses (DVA) data of the oil formation volume factor (βo) and solution gas-oil ratio (Rs) versus reservoir pressure depletion are shown in Figures 6 and 7. By reviewing this data, two groups of curves related to two different labs can be investigated. A comperhensive study10 was performed to define valid samples that can be used in developing correlations of fluid property with depth. Procedures for experimental data validation and quality check are discussed below: 1- Fluid Property Analysis. For fluid samples related to one origin where a compositional variation within the hydrocarbon column exists, the PVT curves for any oil property should be parallel above the Pb due to change in the light components and almost identical below the Pb due to similar heavy ends characterization. If this data is related to depth, the Pb, βo, and Rs data would decrease with depth while oil density (ρo) and oil viscosity (µo) would increase with depth. It is clearly shown from Figures 6 & 7 that the lab 2 group of curves are consistent depth wise and indicate the above mentioned feature. In contrast, the lab 1 curves are inconsistent and intersect each other. In spite of the good lab analysis for well A6A sample (group 2), the sample was considered non-representative and eliminated from correlations of fluid property with depth. When the separator gas and liquid samples for this well recombined to the producing GOR and heated to the reservoir temperature, the mixture was a gas phase at a pressure higher than the reservoir pressure. When the mixture was equilibrated at the reservoir pressure, there was an accumulation of 42.4 volume percent of condensate at this

pressure. The standard PVT analysis was then completed on this mixture at the reservoir pressure. So, the Pb of this sample and the corresponding fluid properties might be non-representative at its sampling depth. 2-Compositional Analysis. The available chromatograms of heavy ends extended analyses (Figure 8) indicate lower concentration of components in the C7 to C11 range with increasing depth. This is an indication for some change in the heavy ends characterization with depth. However, the identical concentration of heavier components ranging from C12 to C39 reflects one common oil source origin in both Nukhul and Nubia reservoirs and in turn reflect a good chromatographic analysis. For a vertical variation in the hydrocarbon column, fluid composition updip in the reservoir increased in the light components and decreased in the heavy components. This can be shown from the heptanes plus mole percent and methane mole percent correlations with depth which are presented in Figure 9. The lab 2 samples (except the A6A sample) were qualitatively considered valid samples because of the consistency of its PVT data. A further quality check for these samples was performed quantitatively by using a computer program which uses the Redlick-Kwong equation of state (RKEOS). The function of this program is to predict the fluid properties at both reservoir and separator conditions from the experimental compositional analysis. It is worth to mention that the RKEOS, as any other equation of state, is composition dependant. Therefore, the degree of match between the predicted properties and the lab measurements depends mainly on the accuracy of the experimentally determined composition, However, obtaining a good match means good lab analysis but doesn't mean the sample is representative. To visualize the degree of match between the RKEOS predicted properties and the lab measurements, a plot for each property at the bubble point pressure was developed and a unit slope line between the two values was drawn to indicate how the RKEOS results are deviated from the lab analysis. The comparison plots for the Pb, βo, and Rs obtained from the DVA are presented in Figures 10 through 12 while the plots of βo and Rs obtained from the flash liberation are presented in Figures 13 & 14. Generally, these plots show a close agreement between the predicted properties and most of the lab analyses. The well A1 bottomhole sample at depth 9732' subsea shows the best match. So, this sample will be selected as a datum (reference) sample to predict both composition and fluid properties gradients at any bottomhole location at both reservoir and field separator conditions.

4 SPE 95760

Prediction of Reservoir Fluid Gradient To establish a reliable reservoir fluid gradient, a representative sample depth should be defined. A representative sample depth depends mainly on the sample type as follows: Sample Type RSD B.H Mid perfs below sampling depth S.S Mid perfs RFT & MDT Sampling point Two methods have been used for correlating the fluid properties with depth and then predict it at any bottomhole location. The first method relies only on the experimental data provided by the laboratories for the use in a black oil model. The second method uses the equation of state (RKEOS) to predict the compositions and the fluid properties from the experimentally determined compositional analysis for the datum valid sample to be used in a compositional model. Procedures for doing these predictions are discussed below: 1- Property Prediction (Graphical Method). A bubble point pressure correlation with depth (Figure 15) was developed by obtaining the best fit line for the experimentally determined Pb values for the lab 2 valid samples (six samples). By slightly extrapolating the line to the depth of Nukhul crest at 9250' subsea, the corresponding Pb would be 5065 psi. By interpolating the correlation with the depth of Nubia crest at 9700' subsea, the corresponding Pb would be 4420 psi. For each fluid property, an average curve through the valid samples DVA data was taken. Then the average curve was extrapolated to the Nukhul Pb at crest and interpolated to the Nubia Pb at crest. So, one common DVA curve for each property was developed for both Nukhul and Nubia reservoirs. The βo and Rs common curves are presented in Figures 16 & 17. The interpolation process can then be repeated to predict the Pb and its corresponding properties at any bottomhole location. 2- Composition Prediction (EOS Method). The experimentally determined reservoir fluid composition for the datum sample at depth 9732' subsea was used to predict the reservoir fluid composition at different bottomhole locations using the RKEOS program. The gravity-induced fluid component migration is proportional to the equilibrium gas composition at any point in the oil column.16 An approximate compositional distribution below the datum sample depth can be developed by successively subtracting equilibrium gas from the undersaturated datum oil sample16 (subsequent flash liberation process). The compositional distribution at higher levels above the datum sample can be obtained by successively adding equilibrium gas to the datum oil sample (subsequent stream

blending process). In this process the datum reservoir oil is subjected to flash at its saturation pressure. Then, the resulting vapor is blended with the resulting liquid by different ratios using the stream blending option of the EOS program until the required Pb is obtained. The predicted compositional gradient was then used to predict the fluid properties at the bottomhole location of the valid samples using the DVA calculation option of RKEOS program. To have more accurate fluid property predictions, the slight change in the heavy ends characteristics with depth was taken into account. The heptanes plus molecular weight and specific gravity correlations with depth are presented in Figures 18 and 19. Theory indicates that the natural temperature gradient (increase of temperature with depth) will enhance compositional grading.17 the temperature gradient in the Hilal field (Figure 20) was also taken into account when predicting the fluid properties at different bottomhole locations. However, in the Hilal field case, both changes in the heavy ends characteristics and reservoir temperature with depth have minor effects on the predicted fluid property. The predicted Pb, βo, and Rs values for the valid samples were plotted along with the experimentally determined values (Figures 15, 21, and 22). As shown from these plots, the predicted values are more close to the fitting gradient than the experimental values which reflect a fairly good prediction by using the RKEOS program.

Necessity of 3D Model Due to the crude oil volatility and its variation with depth, the direct use of a conventional material balance method (zero dimensional model) for matching the reservoir history and predicting the future performance would be incorrect for the following reason: The most serious assumption involved in the conventional material balance method results from the necessity of treating the produced oil and gas as separate fluids, independent of each other in their behavior. In other words, PVT data considers that the reservoir hydrocarbon is made up of two components, gas and oil, and that the composition of each remains essentially the same at any reservoir pressure. This approach is acceptable for black oil reservoirs. However, for a volatile oil reservoirs, the gas and oil compositions change so much during pressure depletion that normal PVT data are not accurate enough for material balance calculations.18 In fact, in a volatile oil reservoir, the gas phase in the reservoir becomes very rich, much like a condensate fluid. As a result, the produced gas yields considerable liquid volumes at the lower pressure and temperature of the surface production equipment. This liquid may amount to 25 to 50 percent of the total oil recovered in the stock tank for high volatile cruds. In such cases recovery of stock tank oil per unit of pressure

SPE 95760 5

decline can be predicted only from a detailed knowledge of the separator conditions and overall composition of the fluid entering the wellbore at each stage of depletion.19 However, this problem is not such serious in the Hilal field case. This is due to water influx driving mechanism in both reservoirs where the reservoirs pressures were maintained flat at certain levels of production. In other words, the water influx balances the withdrawal rates so the secondary gas cap stop growing and the enriching of the gas cap also stops. For the above mentioned problem, it was decided to use either a 3D black oil or a compositional model to accurately represent the produced fluids through history matching and performance predictions.

Conclusions In light oils (API > 35o), the saturation pressure gradient may be interpreted as the result of gravity-induced fluid component migration that occurs to obtain equilibrium between the chemical and gravity forces. In heavier oils, moderately heavy (20 to 30o API), compositional grading is caused by the segregation of asphaltenes, resulting in variation in oil viscosity and the possibility of tar-mat formation. Evidences of compositional gradient within the hydrocarbon column can be detected from several geological and engineering data such as: geological model, reservoir fluid type, production data, drillstem tests, RFT data, and openhole logs. For a vertical variation in the hydrocarbon column, fluid composition updip in the reservoir increased in the light components and decreased in the heavy components. In most cases, for fluid samples related to one origin where a compositional variation within the hydrocarbon column exists, the PVT curves for any oil property should be parallel above the Pb due to change in the light components and almost identical below the Pb due to similar heavy ends characterization. However, in some other cases, a compositional variation in the heavy ends can also exist. The degree of match between the predicted fluid properties using an equation of state and the lab measurements depends mainly on the accuracy of the experimentally determined composition, however, obtaining a good match means good lab analysis but doesn't mean the sample is representative. The procedure to predict a compositional gradient is a combination of stream blending and flash liberation processes to estimate the reservoir fluid composition at shallower and deeper depths from the depth of a datum sample. The direct use of conventional material balance for matching the reservoir history and predicting the future performance of composition variation with depth cases would be incorrect. A 3D black oil model or a compositional model should be used instead.

Nomenclature βo = Differential liberation oil formation volume

factor, BBL/STB. Pb = Bubble point pressure, psi. Rs = Differential liberation gas-oil-ratio, SCF/STB.

ρo = Oil density, gm/cc. µo = Oil viscosity, cp.

API = Stock tank oil gravity, degrees OWOC

= Original water/oil/contact, ft.

DVA = Differential liberation analysis.

Acknowledgment The authors wish to thank Khalda Petroleum Company for permission to publish this paper.

References 1. Sage, B.H., and Lacey, W.N.: "Gravitational Concentration

Gradients in Static Columns of Hydrocarbon Fluids," Trans., AIME (1939) 132, 121-131.

2. Schulte, A.M.: "Compositional Variation within a Hydrocarbon

Column Due to Gravity," paper SPE 9235, ATCE, Dallas, TX, (Sept. 21-24, 1980).

3. Creek, J.L. and Schrader, M.L.: "East Painter Reservoir : An

Example of a compositional Gradient from a Gravitational Field," paper SPE 14411, the 60th ATCE, Las Vegas, NV, (Sept. 22-25, 1985).

4. Metcalfe, R.S., Vogel, J.L. and Morris, R.W.: "Compositional

Gradient in the Anschutz Ranch East Field," paper SPE 14412, Las Vegas, NV, (Sept. 22-25, 1985).

5. Schulte, A.M., Riemens, W.G., and de Jong, L.N.J.: "Birba Field

PVT Variations Along the Hydrocarbon Column and Confir.matory Field Tests," JPT (Jan. 1988), 83.

6. Bath, P.G.H., Fowler, W.N., and Russell, M.P.M.: "The Brent

Field, A Reservoir Engineering Review," paper EUR 164, SPE European Offshore Petroleum Conference and Exhibition, London, (Oct. 21-24, 1980).

7. Hirschberg, A.: "Role of Asphaltenes in Compositional Grading

of a Reservoir's Fluid Column," JPT (Jan. 1988), 89-94. 8. Tissot, B.P. and Welte, D.H.: Petroleum Formation and

Occurrence, Springer-Verlag, Berlin (1978). 9. Hunt, J.M.: Petroleum Geochemistry and Geology, W.H. Freeman

and Co., San Francisco (1979). 10. Hanafy, H.H.: "Predicting and Averaging of Fluid Properties for

a Volatile Crude," the 9th EGPC Exploration and Production Conference, Cairo, (Nov. 20-23, 1988).

11. Hanafy, H.H.: "A Compositional Gradient within the

Hydrocarbon Column in the Kareem Formation of Waly Field," the 11th EGPC Exploration and Production Conference, Cairo, (Nov. 7-11, 1992).

6 SPE 95760

12. Hanafy, H.H.: "Applying Zero Dimensional Water Influx Model to Volatile Oil Reservoirs," the 3ed MPM Conference, Cairo university, (Feb. 2-6, 1992).

13. McCain, W.D., Jr.: The Properties of Production Fluids, Second

Edition, Pennwell oks,Tulsa, Okla. (1991). 14. McCain, W.D., Jr. and Bridges, B.: "Black Oils and Volatile Oils

- What's the Differences?," Petroleum Engineering International, (Nov. 1993) 24-27.

15. Moses, P.L., "Engineering Application of Phase Behaviour of

Crude Oil and Condensate Systems," JPT (July 1986) 716, 722, 723.

16. Paul A. Fjerstad, Svein A. Flaate, Jens Hugen, and Steinar pollen:

"Long-Term Production Testing Improves Reservoir characterization in the Oseberg Field," JPT (April 1992) 478, 479.

17. Holt, T., Lindeberg, E., Ratkje, S.K.: "The Effect of Gravity and

Temperature Gradients on Methane Distribution in Oil Reservoirs," paper SPE 11761 available at SPE headquarters, Richardson, Tx.

18. Reudelhuber, F.O., and Hinds, R.F. : "Compositional Material

Balance Method for Prediction of Recovery from Volatile Oil

Depletion Drive Reservoirs," JPT (January 1957) 19-26, Trans., AIME, 210.

19. Jacoby, R.H. and Berry, V.J.Jr.: "A Method for Predicting

Depletion Performance of a Reservoir Producing Volatile Crude Oil," JPT, (Jan. 1957) 27-33; Trans., AIME, 210.

TABLE 1 - PVT Data for Kareem Formation – Waly Field

DST # 1 DST # 2

Sampling Depth, ft (s.s) -6844 (6900 RKB) -6744 (6800 RKB)

Mid Perf. Depth, ft (s.s) -6927 (6983 RKB) -6795 (6851 RKB)

Pb, psi 3251 3258

βo, BBL / STB 1.635 1.774

Rs, SCF / STB 1067 1267

ρo, gm / cc 0.6729 0.6467

µo, cp 0.57 0.393

API, degrees 31.4 32.8

C7+ MWT 240 221

C7+ Mole percent 28.56 27.68

SPE 95760 7

OCTOBER

EL MORGAN

BADRI

RAMADAN

JULY

SIDKISHOAB

ALI

HILAL

GULF OF SUEZ FIELDS

FIG. 1 : Hilal Field - Top Nubia Structure MapFIG. 1 : Hilal Field - Top Nubia Structure Map

9900

10300

10100

10500

A4

oowc

30o

x

A2Ax

A11

10700

101001030010500 A14

10300

10100

10300A3B

oowc

10300

10500

22o

A7B

9900

A1x

A9

x

10100

9900

A6A

10300

10100

A10A

A5

10100

9900

97009500

23o A8

A12

A9A

A12A

x

NUBIA WELLSNUKHUL WELLSSAMPLED WELLS

9800

10000

10200

10400

DE

PTH

, F t

S.S

500 600 700 800 900 1000

Producing GOR, SCF/STB

A-1 Nub @ -9861'A4 NUK @ -10031'A2A NUB @ -10344'

Fig. 2: Initial Producing Gas Oil Ratio Correlation with DepthFig. 2: Initial Producing Gas Oil Ratio Correlation with Depth

6700

6800

6900

7000

7100

7200

73003320 3340 3360 3380 3400 3420 3440 3460 3480 3500 3520

OWOC @ - 7100 FT S.S.)

OIL GRAD.= 0.320 PSI / FT.

WATER GRAD.= 0.44 PSI / FT.


PI @ DATUM (-6930 FT S.S.)=3407 PSI

S.S.

DEP

TH

X

Fig. 3 : Waly Field RFT For Well # A1 Dated : jan. 25,82Fig. 3 : Waly Field RFT For Well # A1 Dated : jan. 25,82

8 SPE 95760

7400

7300

7200

7100

7000

6900

6800

6700

6600

3200 3250 3300 3350 3400 3450 3500 3550 3600

X X

S.S.

DEP

TH PI @ DATUM (-6930 FT S.S.)=3326 PSI

OWOC @ - 7100 FT S.S.) WATER GRAD.= 0.44 PSI / FT.



GAS GRAD.= 0.05 PSI / FT.

GOC @ - 6775 FT S.S.

Fig 4 : Waly Field RFT For Well # A3 Dated : Dec. 31,84Fig 4 : Waly Field RFT For Well # A3 Dated : Dec. 31,84

PRESSURE PSI

Fig. 5: Waly Well # A3

Fig. 6 : Oil Formation Volume Factor Curves From DVAFig. 6 : Oil Formation Volume Factor Curves From DVA

0 1000 2000 3000 4000 5000 6000PRESSURE, PSI

1.0

1.2

1.4

1.6

1.8

2.0

2.2

2.4

Oil

F orm

atio

n Vo

lum

e Fa

ctor

, B

BL /

STB

A-1 SS LAB-2 @ -9293'A-1 SS LAB-1 @ -9293'A-6A SS LAB-2 @ -9536'A-6A SS LAB-1 @ -9536'A-1 BHS LAB-2 @ -9732'A-1 SS LAB-2 @ -9861'A-1 SS LAB-1 @ -9861'A-1 BHS LAB-2 @ -9971'A-4 SS LAB-2 @ -10031'A-4 SS LAB-1 @ -10031'A-2A SS LAB-2 @ -10344'A-2A SS LAB-1 @ -10344'A-2A BHS LAB-1 @ -10469'

LAB-2

LAB-1

1.95 2.45 2.95

45 15 - 15 7200’

7250’

7300’

7350’

7400’

7450’

OGOC @ 7286’ RKB (- 6775’ S.S.)

DENSITY LOG

NEUTRON LOG

SPE 95760 9

0 1000 2000 3000 4000 5000 6000

PRESSURE, PSI

0

500

1000

1500

2000

2500

GO

R,

SCF/

STB

A1 SS LAB-2 @ -9293'A1 SS LAB-1 @ -9293'A6A SS LAB-2 @ -9536'A6A SS LAB-1 @ -9536'A1 BHS LAB-2 @ -9732'A1 SS LAB-2 @ -9861'A1 SS LAB-1 @ -9861'A1 BHS LAB-2 @ -9971'A4 SS LAB-2 @ -10031'A4 SS LAB-1 @ -10031'A2A SS LAB-2 @ -10344'A2A SS LAB-1 @ -10344'A2A BHS LAB-1 @ -10469'

LAB-2

LAB-1

Fig. 7 : Gas Oil Ratio Curves From DVAFig. 7 : Gas Oil Ratio Curves From DVA

0 5 10 15 20 25 30 35 40

CARBON NUMBER

0

2

4

6

8

10

12

14

MO

LE %

A-6 Nuk @ -9536'A-1 Nub @ -9861'A-4 Nuk @ -10031'A-2A Nub @ -10344'

Fig. 8 : Heptanes Plus Extended Analysis - Carbon No. Vs. Mole % Fig. 8 : Heptanes Plus Extended Analysis - Carbon No. Vs. Mole %

9200

9400

9600

9800

10000

10200

10400

DEP

TH,

Ft S

.S

10 20 30 40 50 60Mole, %

C1 Mole%C7+ Mole%

Fig. 9 : Heptanes Plus and Methane Mole% Versus Depth Fig. 9 : Heptanes Plus and Methane Mole% Versus Depth

10 SPE 95760

3600 3800 4000 4200 4400 4600 4800 5000 5200

LAB

3600

3800

4000

4200

4400

4600

4800

5000

5200

E O

S

A-1 Nuk SS @ -9293'A-1 Nub BHS @ -9732'A-1 Nub SS @ -9861'A-1 Nub BHS @ -9971'A-4 Nuk SS @ -10031'A-2A Nub SS @ -10344'

Fig. 10 : Bubble Point Pressure - Lab Vs. EOSFig. 10 : Bubble Point Pressure - Lab Vs. EOS

1.7 1.9 2.1 2.3 2.5

LAB

1.7

1.9

2.1

2.3

2.5

E O

S


Fig. 11 : Oil Formation Volume Factor - Lab Vs. EOSFig. 11 : Oil Formation Volume Factor - Lab Vs. EOS

1000 1250 1500 1750 2000 2250 2500LAB

1000

1250

1500

1750

2000

2250

2500

E O

S


Fig. 12 : Solution Gas Oil Ratio - Lab Vs. EOSFig. 12 : Solution Gas Oil Ratio - Lab Vs. EOS

SPE 95760 11

1.5 1.6 1.7 1.8 1.9 2.0

Lab

1.5

1.6

1.7

1.8

1.9

2.0

EOS

A1 NUK SS @ -9293'A1 NUB BHS @ -9732'A1 NUB SS @ -9861'A1 NUB BHS @ -9971'A-4 NUK SS @ -10031'A-2A Nub SS@ -10344'

Fig. 13 : Separator Oil Formation Volume Factor - Lab Vs. EOSFig. 13 : Separator Oil Formation Volume Factor - Lab Vs. EOS

750 1000 1250 1500 1750

Lab

750

1000

1250

1500

1750

EOS

A1 NUK SS @ -9293'A1 NUB BHS @ -9732'A1 NUB SS @ -9861'A1 NUB BHS @ -9971'A-4 NUK SS @ -10031'A-2A Nub SS @ -10344'

Fig. 14 : Separator Gas-Oil Ratio - Lab Vs. EOSFig. 14 : Separator Gas-Oil Ratio - Lab Vs. EOS

9000

9200

9400

9600

9800

10000

10200

10400

DEP

TH,

Ft S

.S

3000 3500 4000 4500 5000 5500

Bubble Point Pressure, PSI

A-1 Nuk SS @ -9293'A-1 Nub BHS @ -9732'A-1 Nub SS @ -9861'A-1 Nub BHS @ -9971'A-4 Nuk SS @ -10031'A-2A Nub SS @ -10344'Predicted

-1.44 Psi/Ft

Fig. 15 : Bubble Point Pressure Correlation With DepthFig. 15 : Bubble Point Pressure Correlation With Depth

12 SPE 95760

9000

9200

9400

9600

9800

10000

10200

10400

DEP

TH,

F t S

.S

1.6 1.7 1.8 1.9 2 2.1 2.2 2.3 2.4 2.5

Oil Formation Volume Factor, BBL/STB


Fig. 16 : Oil Formation Volume Factor Correlation With DepthFig. 16 : Oil Formation Volume Factor Correlation With Depth

9000

9200

9400

9600

9800

10000

10200

10400

DEP

TH,

Ft S

.S

1000 1200 1400 1600 1800 2000 2200 2400

Solution Gas-Oil Ratio , SCF/STB


Fig. 17 : Solution Gas-Oil Ratio Correlation With DepthFig. 17 : Solution Gas-Oil Ratio Correlation With Depth

9000

9200

9400

9600

9800

10000

10200

10400

DE

PTH

, Ft

S.S

230 240 250 260

Molecular Weight


Fig. 18 : Heptanes Plus Molecular Weight Correlation With DepthFig. 18 : Heptanes Plus Molecular Weight Correlation With Depth

SPE 95760 13

9000

9200

9400

9600

9800

10000

10200

10400

DE

PTH

, Ft

S.S

0.86 0.87 0.88 0.89

Specific Gravity


Fig. 19 : Heptanes Plus Specific Gravity Correlation With DepthFig. 19 : Heptanes Plus Specific Gravity Correlation With Depth

9000

9200

9400

9600

9800

10000

10200

10400

DE

PTH

, F t

S.S

250 260 270 280 290

Temperature, F


o

Fig. 20 : Reservoir Temperature GradientFig. 20 : Reservoir Temperature Gradient

0 1000 2000 3000 4000 5000 6000

PRESSURE, PSI

1.0

1.3

1.6

1.9

2.2

2.5

Bo,

BBL/

STB

Fig. 21 : Oil Volume Factor common curve @ CrestFig. 21 : Oil Volume Factor common curve @ Crest

14 SPE 95760

Fig. 22 : Gas-Oil Ratio Common Curve @ CrestFig. 22 : Gas-Oil Ratio Common Curve @ Crest

0 1000 2000 3000 4000 5000 6000PRESSURE, PSI

0

500

1000

1500

2000

2500

GO

R, S

CF/

STB

Documents

SPE-95760-MS-P