Seth2013

SPE 165880 Saturation Height Function in a Field Under Imbibition: A Case Study K. Seth, V. Beales, A. Kawasaki, T. Namba : Inpex Operations Australia Pty Ltd

Copyright 2013, Society of Petroleum Engineers This paper was prepared for presentation at the SPE Asia Pacific Oil & Gas Conference and Exhibition held in Jakarta, Indonesia, 22–24 October 2013. 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 have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material does not necessarily reflect any position of the Society of Petroleum Engineers, its officers, or members. Electronic reproduction, distribution, or storage of any part of this paper without the written consent of the Society of Petroleum Engineers is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of SPE copyright.

Abstract This paper presents a case study on the reconciliation of the water saturation computed using electrical logs and a saturation height function when the field is under imbibition. It is noted that wireline log evaluations suggest that the reservoir system cannot be adequately described using primary drainage capillary pressure in the field, and structure restoration study supports that the reservoir is under the imbibition process. Gas in place (GIIP) has the largest impact on the development planning of this offshore gas field. GIIP is computed using the gas saturation, area and thickness of the reservoir making gas saturation a critical evaluation parameter. To compute the gas saturation accurately, typically, two sources of data, wireline logs and core measurements are integrated and reconciled. Wireline log based saturation is computed by using density, neutron porosity, resistivity as well as dedicated electrical core measurements, Archie’s exponents m and n. In addition, core based saturation is computed using saturation height functions established from capillary pressure measurements acquired using various techniques: Mercury Injection, Centrifuge and Porous Plate experiments. For imbibition conditions, special spontaneous and forced imbibition measurements were acquired on the core samples. These data sets represent two independent evaluations of the gas saturations. In this paper, an imbibition function is computed from drainage capillary pressure data from core measurements and reconciled with wireline log estimates in a systematic workflow. This workflow has been applied to the Ichthys field, Browse Basin, on the NW shelf of Australia for generating the pre-development drilling base case model. Overall, a good match is obtained between the saturation computed by the imbibition function and the wireline log interpretations, however mismatch is observed across some zones. Methods are proposed to clarify the origin of the mismatch and validate the resultant saturation whilst also serving as a guide for establishing a robust workflow to achieve these results. Introduction The Ichthys field is located approximately 200 km offshore on the NW shelf of Australia in water depths of 260-280 m1. The reservoir is a thick sequence of clean, high NTG sands, which are interpreted to have been deposited by poorly confined, sand rich, mid-slope grain flows or high density turbidity currents in a deep water ramp setting. Two thick sandstones are separated by a field wide mudstone interval of varying thickness. This mudstone is named as the Mudstone Break with the sands below and above named the Lower Sandstone and Upper Sandstone respectively. Associated with the sandstones are thin, interbedded mudstones deposited by the waning energy portion of the turbidity currents and subsequent hemipelagic sedimentation. These and the paucity of ichnological features – particularly those indicative of shallow water are considered evidence of deeper water depositional environment. The Brewster Member represents an extensive submarine lobe complex which prograded from the east and southeast across the field area. The sequence thins and pinches out to the west and northwest. The sediment is interpreted to be supplied by slumping and reworking from the more proximal shallow marine Yampi Shelf. The Brewster trap is a broad drape feature, 41km by 18km, with a structural crest at a depth of about 3900m. It is mainly dip closed except to the north where there is a minor fault component. The trap contains a wet gas column of about 200m, and is interpreted to be full to spill. The reservoir quality of these high net to gross (NTG) sandstones, ~95%+/-, is variable due to a complex diagenetic overprint, quartz overgrowths being a particular feature which significantly alters the primary porosity and permeability both laterally but more importantly vertically as regards to the saturation profile. Furthermore, due to the high NTG and associated low clay volumes bound water volumes are small. Similarly the difference between total porosity and effective porosity is interpreted to be very little. Irreducible water volumes (Swirr) are consistent with analogous reservoirs (which may be classified as the clean low permeability reservoirs) and are quite low compared to standard shaly-sand reservoirs due to the

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lower clay bound water volume. Figure 1-1 is taken from SPE 603042 which shows that even at permeabilities of 0.001 mD, water saturation of the order of 50-60% are expected in Medina and Mesaverde-Frontier tight gas sands.

Figure 1-1 Behavior of water saturation in a clean tight gas reservoir (taken from SPE-60304).

Log Based Water Saturation Nine wells were drilled into this formation within the field. As a minimum, triple combo wireline logs were acquired in the wells, with gamma spectroscopy in many wells along with NMR in one well. Extensive conventional core was cut with 759 m recovered and over 2100 routine core analysis plugs analyzed. Given this extensive data set, it is believed that the core is representative of the formation. A multi-mineral10, simultaneous solver approach was adopted to evaluate the reservoir. Response equations are defined which predict each measurement in the logging suite as a function of all the volumes of minerals and fluids influencing that sensor from a defined mineral reference composition. The mineral composition volumes were adjusted to give the optimum match of the measured and predicted readings across the suite of measurements being modeled. In this approach volumes of minerals and fluids are derived simultaneously as opposed to sequentially in deterministic evaluations. Mainly linear equations were used except for the resistivity where the Dual Water7 non-linear equation was employed. In case of poor hole conditions, the density/neutron logs were dropped from the solver, hence the main driver for porosity was the sonic log 9 . The following static parameters also affect the evaluation of saturation. Connate Water Salinity: A ramp profile was finally used in the evaluation with values ranging from 13,000 ppm, at the top, to 8,000 ppm NaCl equivalent, at the base of the reservoir respectively. This was based on a fluid inclusion salinity study, the results of which validated with those measured from Dean Stark extraction of water from gas bearing zones as well as water isotope analysis. Archie cementation exponent "m": A simple regression based method of estimating “m” from permeability was established. The regression was for the Upper and Lower Sandstone separately based on core data as illustrated in Figure 1-2. Continuous permeability estimates have been generated using a clustering technique independent of the porosity and fluid saturations.

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“m” v/s Permeability

Figure 1-2 Regression between permeability and “m” for the Upper and Lower sandstones

Archie cementation exponent “n”: No trend of “n” with core porosity or permeability was evident. This is a Gas-Water system, there is little expectation of wettability alteration and corresponding change in "n" through the reservoir, hence an average value of “n” based on the core measurements was assigned for the Upper and Lower Sandstone respectively. Log Based Evaluation Results As expected, high gas saturations are generally observed high above the Free Water Level (FWL). However there are a number of observations of interest: A clear gas bearing zone was present immediately below the FWL in some of the wells, but not all the wells. The FWL was established by extensive pressure tests recorded in all the wells in the field. In clean zones, which lay on a single water gradient (seen on the formation pressure plot), significant gas saturations are interpreted. This is illustrated in Figure 1-3 where the input logs and interpreted results of two nearby wells are presented. The thick blue line is the FWL, as defined by the formation pressure gradients intercept.

Well A

Well B

Figure 1-3 Input wireline logs and interpreted results on two nearby wells. The thick blue line is the Free Water Level (FWL) as

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interpreted from formation pressure data.

No clear water zone/transition zone is visible in Well A (drilled with Water based muds). Conversely a clear water bearing zone and transition is visible in Well B (drilled with Oil based muds). In both the wells, the core porosity and permeability match well with the log interpreted porosity and permeability validating the interpretation, further Dean Stark measurements were acquired in Well B (plotted as red dots on the Saturation track) which match well with the log interpreted saturations. However, the FWL interpreted from the formations pressures is 25m TVD higher than where calculated gas saturations approach zero. A conventional drill stem test was run below the FWL in Well A, which did not flow any fluids or gas, whereas the second test in the same well above the free water level produced gas. Imbibition Concept As already outlined, the phenomenon of high gas saturations below the FWL occurs in a few of the wells in the field. This discrepancy cannot be explained by a drainage process. One of the possible explanations for this is the fact that the field was filled to a deeper spill point and there has been a breach or some structural movement post primary migration. Either mechanism could put areas of the reservoir in imbibition as gas re-migrated to re-establish equilibrium. The North West Shelf of Australia has been tectonically active; with the Australia Plate colliding with the Eurasian Plate along the edge of Timor and Indonesia. This is a well-documented process, active since the Cretaceous, resulting in downward tilting to the NW4. This process has been prior thought responsible to explain residual hydrocarbon columns in reservoirs3. A structure restoration study was performed to investigate this concept and concluded this was a possible mechanism. From this and other studies, a Paleo-Free Water Level (PFWL) was established, deeper than the present FWL across the field with a dip consistent with above described processes Core Based Drainage Modeling In order to model drainage in the reservoir extensive centrifuge and mercury injection experiments were conducted on core plugs. In total there are 84 capillary pressure experiments available. Of the 84 measurements, 48 have been acquired using the centrifuge with Air-Brine fluids, whereas the remainder have been acquired using the Mercury-Air fluids. Three forced imbibition measurements using the centrifuge were acquired using Decane-Brine fluids. All measurements were conducted at ambient conditions. The lab data requires corrections for various effects to be compatible and comparable with the reservoir and these corrections can be classified by measurement type. Mercury Injection Capillary Pressure Data (MICP): In general the MICP data requires three corrections to be done in an additive manner on the lab measurement. First are the closure corrections, usually done by the service provider, which correct for the false increase in mercury saturation while it conforms to the surface of the sample. Incorrectly corrected data can be identified by an abrupt change in slope of the capillary pressure curve. The high surface tension of mercury causes it to destroy fine clay structures as it invades pore spaces in the core sample. These clay structures often control the pore throat diameters and hence their destruction can significantly impact permeability. The destruction of these fine clay structures would be result in lower irreducible water saturation in the core measurement as compared to the reservoir. All these affects are compensated by applying the Clay Bound water correction based on the work of Hill et. al.5(1979) after applying the closure corrections. Finally, the stress corrections need to be applied in order to convert the measurement from lab conditions to the reservoir conditions. This is also based on the work of Hill et. al.5(1979). The impact of these additive corrections is illustrated in Figure 1-4 where the blue curve is the lab measurement, the pink curve is closure corrected, the green curve is closure and clay bound corrected and the purple curve is stress (at net overburden pressure NOBP), clay bound and closure corrected data. Note that every correction increases the water saturation with respect to capillary pressure.

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2500.000

2000.000

Uncorrected Sw and Pc (0.048 mD @NOBP) Closure corrected Sw and Pc (0.048 mD @NOBP) Closure & Clay-bound water corrected (0.048 mD @NOBP) Stress, Closure & Clay-bound water corrected (0.048 mD @NOBP)

Pc

1500.000

1000.000

500.000

0.000 0.000

0.200

0.400

Swt

0.600

0.800

1.000

Figure 1-4 Plot illustrating the impact of closure, clay-bound water and stress corrections on the MICP measurements

After applying corrections, this data needs to be converted into Height above Free Water Level (HaFWL) to facilitate comparison with the reservoir or any other capillary pressure measurements, which is done via Equation 1. At this stage lab interfacial tension measurements are required.

h=(

σ cos θ res σ cos θ la b

) /( ∆wat − ∆gas )

----

Equation 1

Where: h is the Height above Free Water level (σcosӨ)res is the surface tension multiplied by the appropriate contact angle for the reservoir conditions. (σcosӨ)lab is the surface tension multiplied by the appropriate contact angle for the lab conditions. Δwat is the water gradient (psi/m) Δgas is the gas gradient (psi/m) Centrifuge Capillary Pressure Data: The centrifuge data require only stress corrections to be comparable to the reservoir conditions. These corrections are the same as the ones applied to the MICP data and are based on the work of Hill et. al.5(1979). The impact of this correction is illustrated in Figure 1-5 where the blue curve is the lab measurement and the pink curve is stress corrected. Subsequently, the data needs to be converted into height above free water level which is done, as above, via Equation 1 using the appropriate parameters.

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900

800 Uncorrected Swt and Pc (274 mD KINF@NOBP) Stress corrected Swt and Pc (274 mD KINF@NOBP)

700

600

Pc

500

400

300

200

100

0 0.000

0.100

0.200

0.300

0.400

0.500 Swt

0.600

0.700

0.800

0.900

1.000

Figure 1-5 Impact of stress correction on the centrifuge data

Comparing MICP and Centrifuge Data: Twelve co-located measurements of Centrifuge and MICP data were available in the data set. After applying the relevant corrections outlined above, both the data sets have common measurement denominators, HaFWL and Swt at reservoir conditions; and hence are comparable. A plot of a reduced set of four of the twelve measurements is presented in Figure 1-6 in order to enhance clarity of the comparison. From the plot it is observed that the two measurements form different clusters rather than a single group and the MICP measurements have lower irreducible water saturation as well as a different shape, when compared to the centrifuge measurements. It was concluded that the MICP analysis was not as reliable as the centrifuge analysis for the following reasons: • Clay bound water correction was based on Cation Exchange Capacity (CEC) measured on pulverized core plug trim ends. Pulverizing the core often over-emphasizes the clay impact. • MICP was conducted on core chips which are physically small and may not be as representative as a 1 ½” core plug used in the centrifuge experiment. • And finally, in MICP, the wetting phase saturation trends to zero at high pressures. 500 450 Air-Brine1.58 Hg-Air1.58

400

Air-Brine4.83 Hg-Air4.83

350

Air-Brine8.75 Hg-Air8.75 Air-Brine225

HaFWL

300

Hg-Air225

250 200 150 100 50 0 0.000

0.100

0.200

0.300

0.400

0.500 Swt 0.600

0.700

0.800

0.900

1.000

Figure 1-6 Comparison of MICP and Centrifuge data. Measurement type and permeability is reflected in the curve name

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Quality Control: This essential process was carried out with the aid of two sets of plots. Two sets of plots are required because both permeability and HaFWL impact the water saturation independently. In the first set of plots the permeability is fixed by grouping the data in classes, and in the second set of plots the HaFWL is fixed. This way, consistent behavior of the input data can be checked with each variable separately. In the first set of plots, the measurements were grouped into various permeability classes and plotted together to identify any obvious outliers. These plots are presented in Figure 1-7. If the data is “well behaved” and self-consistent, the curves should not cross each other (within measurement error) and the water saturation should be inversely proportional to the permeability across all the permeability classes. Two measurements, marked a & b, appear to be out of trend with respect to permeability from the plots in Figure 1-7. 500.00

500.00

500.00

0.1 md>Perm>0.01 md

0.01 md>Perm

1 md>Perm>0.1 md

450.00

450.00

450.00

0.1

400.00

400.00

400.00

0.075 0.074

0.00797

350.00

0.055

300.00

0.00385

0.429

300.00

0.339

0.0479

HaFWL

0.00336 HaFWL

0.767

a

0.0558

0.00397

0.00265

250.00

0.918

350.00

0.065

0.00583

300.00

0.00161

HaFWL

350.00

0.0369

250.00

0.0356

0.33 0.321

250.00

0.117

0.034

0.001

200.00

200.00

0.321 (ID) 200.00

0.027 0.0218

150.00

100.00

50.00

0.00 0.000

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Sw (Uncorrected)

Sw

Sw

500.00

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500.00

100 md>Perm>10 md

10 md>Perm>1 md 450.00

400.00

450.00

450.00

400.00

400.00

Perm>100 md

b

9.83 8.75

350.00

350.00

8.26 8.07

300.00 HaFWL

HaFWL

3.99 3.28

234

32.9 12.1

250.00

249

300.00

93.2

4.83 250.00

274

97.7

5.46

300.00

HaFWL

350.00

225 250.00

155

2.62 1.66

200.00

200.00

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150.00

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100.00

50.00

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1.58

0.00 0.000

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0.00 0.000

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1.000

0.00 0.000

0.100

Sw

0.200

0.300

0.400

0.500

0.600

0.700

Sw

Figure 1-7 Plots of the corrected centrifuge drainage measurements grouped by permeability classes

In the second set of plots, permeability verses saturation at constant HaFWL were plotted. These plots are presented in Figure 1-8 at multiple HaFWL. If the data is “well behaved” and self-consistent, then the saturation and permeability should be proportional and behave in a monotonic way. From this set of plots it is easy to establish that point a has questionable quality; however point b is masked. Hence both sets of plots are essential to perform a diligent quality control of the input data.

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1.000

1.000

0.900

0.900

1.000

0.900

HaFWL= 1 m

0.700

0.500

0.400

Sw (linear interpolated)

0.600

0.600

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0.400

b

0.600

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1 Perm

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a

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Pow er (HaFWL= 250 m)

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a

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100

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10

HaFWL= 250 m

Sw (linear interpolated)

Sw (linear interpolated)

0.500

10

1 Perm

0.800

0.700

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1 Perm

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0.900

Pow er (HaFWL= 100 m)

0.800

0.700

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0.01

HaFWL= 100 m

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0.01

b

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HaFWL= 30 m 0.800

Pow er (HaFWL= 10 m)

0.800

0.700

Sw (linear interpolated)

Sw (linear interpolated)

Pow er (HaFWL= 3 m)

0.800

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Sw (linear interpolated)

HaFWL= 10 m

HaFWL= 3 m

Pow er (HaFWL= 1 m)

0.800

0.000 0.001

0.01

0.1

1 Perm

10

Figure 1-8 Centrifuge saturation vs permeability plots at multiple HaFWL.

Using these quality control plots, both the points a and b were identified as inconsistent with the rest of the data. They were removed from the data set for computing a drainage curve using the Lambda function11 (Equation 2). Quality control plots of the Lambda function are presented in Figure 1-9. These plots were used to check firstly that all the input data was honored and secondly that the function behaved in a logical manner, viz. both permeability and HaFWL are inversely proportional to the water saturation.

Sw = a * HaFWL− λ + b Where:

…… Equation 2

a, b & λ are a fitting functions computed from permeability

1

300

0.9 0.01

250

0.8

0.1 1

0.7

10 200

100 1000

HaFWL

Sw Reservoir

0.6

0.5

150

0.4 100

0.3

0.2 50

0.1

0 0.000

0.100

0.200

0.300

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0.500 Sw Lam da

0.600

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1.000

0 0.000

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0.900

1.000

Sw

Figure1-9 Quality check plots of the Lambda drainage function. The plot on the left checks that all the input data is honored by the function and the plot on the right checks that the function conforms to expected behavior of decreasing saturations with increasing permeability.

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Comparison of Drainage Function with Log Evaluation Saturation In the reservoir, high gas volumes are interpreted below the FWL as seen in Figure 1-3. The presence of a smaller than expected transition zone is observed in Figure 1-10 where a comparison of the drainage function based water saturation and log based water saturation is presented from Well-B. In this well, core based Dean Stark measurements were also acquired to confirm the log interpreted water saturations and have been plotted on the saturation track as red dots. They line up with the log based water saturations confirming the shorter than expected transition zone as well as the presence of substantial gas saturations below the FWL. In Figure 1-10 it can be seen that the log-evaluation based gas saturations are much higher than the Sw-Lambda function based gas saturations in zone a. This zone has been cored and the log evaluation based gas saturations compare well with the Dean Stark saturations (red dots on the saturation track) measured on the core plugs. Gas is also seen below the FWL in zone b. This gas saturation is also confirmed from the Dean Stark measurements taken on core plugs. This phenomenon can be explained by the reservoir being in imbibition. As noted earlier, this phenomenon has been observed in various fields in the NW shelf of Australia. Hence an imbibition capillary pressure function needs to be derived from the core data in order to be compatible with the observed log based saturations.

a

Sharp build-up of multimin gas saturation (red shaded area ) when compared with the sw-lamda function

FWL

Gas below FWL

b

Figure 1-10 Illustration of the sharp buildup of Gas saturations and gas below the FWL in Well – B.

Modeling Imbibition on the Core Data Imbibition is a complicated process as imbibition saturation curves are not only a function of the HaFWL and permeability (akin to the drainage curve) but also a function of the Height above the Paleo-FWL (HaPFWL). Thus the same rock taken to a different HaPFWL will exhibit different imbibition saturation curves as illustrated in Figure 1-11. In this figure, the water

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saturations from the same rock are plotted with different HaPFWL and they exhibit different imbibition functions (SwI10, SwI20, etc.) originating from different starting points from the same drainage function (SwD).

Figure 1-11 Illustration of various imbibition functions originating from the same rock

For the imbibition modeling on the core data, the Adams Imbibition From Drainage (IFD) method was selected6. In this method, the imbibition function is derived from the drainage functions after calibrating the results of the drainage to log based saturations on an aggregate basis. The Adams IFD method is an accepted technique honoring all the log data in an aggregate manner and the resultant imbibition function can be checked for consistent and reasonable behavior. However, the technique has the limitation of been selectively calibrated to the well logs; viz. well log based saturations beyond the drainage function curves (from FWL and PFWL) results in the imbibition function being clipped to the maximum and minimum drainage saturations respectively. The Imbibition function takes the form:

SwI = SwD − ∆Sw ∆Sw = s * SwD + int

---- Equation-3

int = a + b log 10( k ) + cSwD min Where: a, b, c, and s are fitting variables K is permeability SwI is the imbibition saturation SwD is the drainage saturation at that HaFWL SwDmin is the minimum drainage saturation observed using the HaPFWL

Adams IFD Saturation Height Function Quality Check As implied by the number of fitting parameters, the function is a non-unique solution and many results can be generated from the single data set. Hence it is imperative that the imbibition function selected be checked for expected behavior. However, as there are 3 variables, this visualization can be achieved by fixing one of the three variables to a constant value and then plotting and checking the relationship between the other two for any inconsistencies. In the left hand plot of Figure 1-12, the permeability is fixed and the HaFWL is varied along with the HaPFWL. These heights are related by 120 m, which is the average difference between these heights at the well locations. When permeability is less than 1 mD, the imbibition function has an impact only when HaFWL is less than 50 m, otherwise the imbibition function traces the drainage function. However, at high permeability (>10 mD) the imbibition function preserves more gas in the rock than the drainage function even at low values of HaFWLs. Hence the imbibition function is similar to an ideal function depicted in Figure 1-10. The plot on the right confirms monotonicity of the function by ensuring that the family of curves do not cross each other.

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1.2 Swi_LamdaHaFWL0.5 Swi_LamdaHaFWL25

1

Swi_LamdaHaFWL50 Swi_LamdaHaFWL75 Swi_LamdaHaFWL100

0.8

Swi_LamdaHaFWL150

Swt_Imb

Swi_LamdaHaFWL200 Swi_LamdaHaFWL250

0.6

0.4

0.2

0 0.001

0.01

0.1

1

10

100

1000

Perm

Figure 1-12 Visualization of the imbibition saturation function with HaFWL.

A further quality check was to compare the resultant saturations with imbibition saturations from other techniques. A limited number of counter current imbibition measurements as well as forced imbibition measurements were conducted on core plugs. The counter current measurements were conducted using toluene and the forced imbibition measurements were conducted using the Mercury-Air system. These measurements are comparable to the imbibition function at spontaneous conditions. The plot of predicted fluid saturation (computed at 0.5 m HaFWL) and the spontaneous measurements are presented in Figure 1-13. Most of the data is close to the 1:1 line on the plot; however there are a few outliers which are the measurements with high permeability. In the reservoir, low permeability is typically seen close to the FWL; hence high permeability is not encountered in the log data set which was used to compute the imbibition saturation function. Hence, these points are not expected to be on the 1:1 line. 1.000

0.900

0.800

Swt_imb_measured

0.700

0.600

0.500 0.041 80.1 0.400

51.5 2.3

0.300

1:1 0.061 103.3

0.200

67.7 4.4 0.100

0.000 0.000

0.100

0.200

0.300

0.400

0.500

0.600

0.700

0.800

0.900

1.000

Sw t_im b_m odel

Figure 1-13 Predicted imbibition saturation plotted against spontaneous imbibition measurements obtained from Counter Current and MICP tests.

Comparison between the Imbibition Function and Log Based Evaluation The imbibition function was calibrated to the log evaluation saturation in an aggregate manner while developing it, as the purpose of the exercise was to reconcile both methods satisfactorily to build realistic static and dynamic reservoir models.

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Although minor differences remain in the saturation values calculated using the two methods, and within the uncertainty of the measurements, it is critical to investigate these to aid in understanding the limitations of the respective methods. A comparison plot between the log based saturation, the drainage saturation and the imbibition saturations is presented in Figure 1-14.

Well C

Well A Interpreted Porosity, & Core Data

Permeability , Mobility & Core Data

Zone 1 Log and Drainage Saturation

Log and Imbibition Saturation

Well B

FWL Figure 1-14 Comparison of the log based saturations with drainage and imbibition saturations in three wells.

Well A: In this well, there is a good match between the drainage saturations and the log based saturations above the Mudstome Break. Below the shale break the drainage saturations go through a transition zone which is not seen on the logs. The imbibition saturations do not have a transition zone and match the log based saturations well. Well B: The drainage saturations do not match the log based and Dean-Stark saturations both above and below the free water level whereas the imbibition saturations match the log based and Dean Stark saturations well. Well C: This well presents an interesting case. The FWL is below the bottom of the reservoir sand. Hence the drainage saturations are quite comparable to the imbibition saturations. However there is a discrepancy at Zone 1 where the drainage saturations read much higher gas volume than the log based saturations. This discrepancy can be resolved considering the uncertainties in the log based saturation. As illustrated in Table 1-1 a porosity difference of 1% (0.01 p.u.) results in a saturation change of 17%, and a change of m from 2 to 2.2, impacts the saturation by 24%.

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Table 1-1 Impact of the Archie parameters and porosity on computed Sw using the Archie equation.

Rt 116

PHIT 0.05

m 2.2

n 2

Rw 0.132

Sw 91.0%

Comment Baseline

116 116 116

0.05 0.06 0.06

2 2.2 2.2

2 2 1.8

0.132 0.132 0.132

67.5% 74.5% 72.1%

m changed PHIT changed n changed

Validation of the Imbibition Saturation In total 173 Dean stark measurements are available in the field. Of these, 48 samples are with an ambient-air permeability of less than 1 mD and confirm that very low permeability rock has a Sw, at ambient conditions, in the order of 45%. Further validation of the imbibition saturation function can be obtained by comparing the trend of the log, imbibition and the core based saturations (Figure 1-15). These plots are overlaid by an identical hand drawn trend. It must be noted that even though all the plots follow the same trend; strictly speaking, these plots do not account for the variable HaFWL hence making this comparison a gross comparison only. Log interpreted Saturation

Imbibition Saturation

Core Dean Stark BM Dean Stark Sw NOBP 100 90 S w

80 70

(

S w

S w

)

S w

N 60 O B 50 P 40

( )

v 30 / v 20 10 0 0.001

Log based Perm

0.01

Log based Perm

0.1

1

10

100

1000

Kinf (800psi) (mD)

Core Perm

Figure 1-15 Comparison of the trend of log, imbibition and the core based saturations.

Conclusions Mercury capillary pressure data was not found compatible with the centrifuge data despite applying all relevant corrections. As a result, the MICP data was not used in preference to the centrifuge data to estimate a saturation height drainage function. The mismatch between the log evaluation and the drainage saturation height function; and the observation of significant gas saturations below the FWL indicates that the field is in imbibition. Adopting the imbibition function improved the log to function correlation but discrepancies still persist in certain intervals. Such discrepancies can be explained by the computation uncertainty in the log based evaluation. The imbibition function was validated using Dean Stark measurements in the field. Acknowledgements The authors would like to thank all the JV partners of the Ichthys Project for the permission to publish the data; viz. Inpex, Total, Tokyo Gas, Osaka Gas, Chubu Electric Power and Toho Gas. Also, the authors would like to acknowledge all the personnel in the subsurface department of Inpex whose constant encouragement and critical review made this project possible.

References 1. Ban, S. & Pitt, G. : The Ichthys Giant Gas Condensate Field, AAPG 2006, Perth, Australia 2.

Byrnes, A.P. & Castle, J W. 2000: Comparison of Core Petrophysical Properties Between Low-Permeability Sandstone Reservoirs: Eastern U.S. Medina Group and Western U.S. Mesaverde Group and Frontier Formation, SPE-60304, Rocky Mountain Regional/Low Permeability Reservoirs Symposium and Exhibition (Denver,

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SPE 165880

Colorado) 3.

Beales, V. & Howell, E.A. 1992. Tanami-1 Oil Discovery: Barrow Sub-Basin. Australian Petroleum Exploration Association Ltd. Journal 32 part 1, 86-93.

4.

Bradshaw, M.T., Yeates, A.N., Beynon, R.M., Brakel, A.T., Langford, R.P., Totterdale, J.M., and Yeung, M. 1988. Palaeogeographic Evolution of the North West Shelf Region. In Purcell, P.G. & R.R. (Eds), The North West Shelf, Australia, Proceedings of Petroleum Exploration Society of Australia Symposium, Perth, W.A., 1988: 29-54.

5.

Hill, H.J., Shirley, O.J., Klein, G.E. 1979. Bound water in Shaly sands-its relation to Qv and other formation properties. Log Analyst

6.

Adams, S.J. 2003, Modeling Imbibition Capillary Pressure Curves, SPE 84298, Denver, Colorado.

7.

Clavier, C, Coates, G & Dumanoir, J. 1977 : Theoretical and experimental bases for dual water model for interpretation of shaley sands. SPE-6895, Society of Petroleum Engineers, 52nd Annual meeting (Denver)

8.

Juhasz, I 1986: Assessment of the distribution of shale, porosity and hydrocarbon saturation in shaley sands. Paper AA, in the 10th European formation evaluation symposium transactions, Society of Professional Well Log Analyst, Aberdeen chapter.

9.

Raymer, L.L. , Hunt, E.R. & Gardner, J.S. 1980: An improved sonic transit time to porosity transform.

10. Schlumberger, 1991: Log interpretation Principles/Applications, Schlumberger Educational Services 11. Corey, A.T, 1954: The Interrelation between Gas and Oil Relative Permeabilities.