Numerical Simulation of CO2 Injectivity in Kingfish Field, Gippsland Basin, SE

AustraliaYildiray Cinar

CO2CRC Report Number: RPT05-0107

Numerical Simulation of CO2 Injectivity in Kingfish Field, Gippsland Basin, SE Australia

Yildiray Cinar

September 2005

CO2CRC Report No: RPT05-0107

Cooperative Research Centre for Greenhouse Gas Technologies (CO2CRC) GPO Box 463 Level 3, 24 Marcus Clarke Street CANBERRA ACT 2601 Phone: +61 2 6200 3366 Fax: +61 2 6230 0448 Email: pjcook@co2crc.com.au Web: www.co2crc.com.au

Reference: Cinar Y, 2005. Numerical Simulation of CO2 Injectivity in Kingfish Field, Gippsland Basin, SE Australia. The University of New South Wales. CO2CRC Report No. RPT05-0107.

© CO2CRC 2005

Unless otherwise specified, the Cooperative Research Centre for Greenhouse Gas Technologies (CO2CRC) retains copyright over this publication through its commercial arm, Innovative Carbon Technologies Pty Ltd. You must not reproduce, distribute, publish, copy, transfer or commercially exploit any information contained in this publication that would be an infringement of any copyright, patent, trademark, design or other intellectual property right.

Requests and inquiries concerning copyright should be addressed to the Communication Manager, CO2CRC, GPO Box 463, CANBERRA, ACT, 2601. Telephone: +61 2 6200 3366.

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Table of Contents

Executive Summary ................................................................................................................. 1

1. Introduction ........................................................................................................................ 2

2. Modelling Approach .......................................................................................................... 2 2.1. Reservoir Description............................................................................................... 2

2.2. Fluid Properties ........................................................................................................ 3

2.3. Capillary Pressure and Relative Permeability.......................................................... 3

2.4. Numerical Model...................................................................................................... 4

3. Results ................................................................................................................................. 5 3.1. Three-Dimensional Model of Kingfish Field........................................................... 5

3.1.1. Model Description........................................................................................ 5

3.1.2. History Match............................................................................................... 5

3.1.3. Sensitivity Study for CO2 Injectivity ........................................................... 6

3.2. Two-Dimensional Model for Latrobe Group Formations........................................ 7

3.2.1. Model Description........................................................................................ 7

3.2.2. Numerical Results ........................................................................................ 7

3.3. Three-Dimensional Model for Latrobe Group Formations...................................... 8

3.3.1. Model Description........................................................................................ 8

3.3.2. Numerical Results ........................................................................................ 8

3.3.2.1. Vertical Wells.............................................................................................. 8

3.3.2.2. Horizontal Wells ......................................................................................... 9

4. Conclusions ......................................................................................................................... 9 Acknowledgements ............................................................................................................. 9

References ......................................................................................................................... 10

Figures ............................................................................................................................... 11

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List of Figures

Figure 1: LVCSA study areas in Gippsland Basin for numerical simulation (Gibson-Poole and Svendsen, 2005). ............................................................................................. 11

Figure 2: Depth structure maps and cross-section of the Kingfish and West Kingfish Fields (Malek and Mehin, 1998)....................................................................................... 12

Figure 3: Continuous and non-continuous shale layers in the Kingfish Area (Gibson-Poole and Svendsen, 2005). ............................................................................................. 13

Figure 4: Porosity-permeability correlation of core-plug data for all formations within the southern oil field study area (Gibson-Poole and Svendsen, 2005). ....................... 14

Figure 5: Areal view of 3-D Model of the Kingfish Field. ..................................................... 15

Figure 6: Enlarged 3-D Model for the Kingfish Simulation Area. ......................................... 16

Figure 7: History match between the oil production from the Kingfish Field and the numerical model. .................................................................................................... 17

Figure 8: Numerical results for water-cut and average reservoir pressure for the Kingfish Field........................................................................................................................ 18

Figure 9: Predicted oil saturation distribution in the Kingfish Oil Field in 2005. .................. 19

Figure 10: Injection locations in the Kingfish simulation area. .............................................. 20

Figure 11: Simulation results of CO2 migration during injection and post-injection periods (Case 7 in Table 4). ................................................................................................ 21

Figure 12: Simplified 2-D model for the Latrobe Formations in the Kingfish Simulation Area. ....................................................................................................................... 22

Figure 13: Variation of maximum injection rate as a function of injection period (Case 1). . 23

Figure 14: Schematic of grid scheme of the reservoir. ........................................................... 24

Figure 15: Various scenarios of vertical wells for 15 Mt/y with different injection pressures................................................................................................................................. 25

Figure 16: Number of vertical wells required for 15 Mt/y as a function of injection pressure................................................................................................................................. 26

Figure 17: A relation between formation permeability and no of injection wells required for 15 Mt/y. .................................................................................................................. 27

Figure 18: Schematic of the placement of horizontal injectors for 15 Mt/y. .......................... 28

1

Executive Summary The simulation study area of Kingfish Field has been studied by numerical reservoir simulation for the injectivity of CO2. Three different reservoir models were constructed for the simulations: (1) A three-dimensional (3-D) history-matched model that describes the layer in which the Kingfish Oil Field lies, (2) a 2-D vertical cross-section model of four principal layers in the Latrobe Group Formation, and (3) a simplified 3-D model that covers all layers in the Latrobe Group Formation. The simulations were performed for two proposed injection rates, 2 and 15 Mt/y, and two injection periods, 25 and 40 years.

The first model for the Kingfish Oil Field was successfully history-matched with the about 30-year production history of the field. The numerical simulation of CO2 injection with the history-matched model indicates that the formation permeability and the maximum bottomhole pressure, allowed based on the formation fracture gradient, control the injectivity of CO2.

The simulations with the 2-D model demonstrate that injection downdip seems to be an optimum solution for the Kingfish area. But, one disadvantage of injecting downdip is that all layers under the Kingfish Field have substantially lower permeability than the Top Latrobe reservoirs, which restrict the injectivity considerably. The results show that the injection of CO2 at 2 Mt/y ‘C’ seems to be applicable under all circumstances. The injection at 15 Mt/y is, however, constrained with the formation permeability and the maximum bottomhole pressure allowed, which suggests additional injection wells to be located in the formation. A sensitivity analysis with the same model shows that the duration of CO2 injection affects the injectivity, especially in the late stage. The number of wells required depends on the permeability and bottomhole pressure.

The numerical results of the third model show that multiple wells are required for the proposed injection rate of 15 Mt/y. The lower the maximum bottomhole pressure allowed as well as the formation permeability the higher the number of the injection wells is required. Drilling horizontal wells instead of vertical ones reduces the number of the wells required.

The conclusions of this numerical study are as follows: (1) The proposed rates of 2 Mt/y and 15 Mt/y seem to be applicable for the Kingfish study area, (2) the number of wells required for the proposed injection rates is very sensitive to the formation permeability, maximum bottomhole pressure allowed, and the duration of injection, and (3) the horizontal wells are advantageous over vertical wells in terms of the number of injection wells required.

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1. Introduction Numerical simulation of CO2 sequestration is of critical importance since it provides forecasts either for injectivity of CO2 in early stage of geological storage or for tracking migration of CO2 in post-injection period until it gets trapped in the reservoir. In this study, we present numerical results that delineate the injectivity of CO2 in the Kingfish Oilfield and surrounding aquifers in Gippsland Basin, Southeast Australia for an injection period of 25 and 40 years (Fig. 11). The aim was to check whether we could inject CO2 at the proposed rates of 2 and 15 Mt/y in the Kingfish Area.

2. Modelling Approach

2.1. Reservoir Description The Kingfish and West Kingfish Fields are located in the Gippsland Basin at the southeastern margin of Australia. These fields have been producing oil and gas for about 35 years. The Kingfish-West Kingfish structure is an eroded, unfaulted, westerly plunging anticline. The reservoir is 6 km wide and 17 km long and contains a maximum gross oil column of 83 m in the Kingfish Oil Field. The West-Kingfish Field is a separate combination trap preserved on the western flank of the Kingfish Field. Fig. 2 shows the depth structure map and cross-section of these fields. The primary reservoirs in the Kingfish Field occur within the Latrobe Group and are designated the Kingfish M-1.4, M-1.5 and M-1.7 reservoirs. The West Kingfish original oil-water-contact (OWC), intersected in the M-1.3 reservoir at -2314 m is 8 m deeper than the Kingfish original OWC at -2306 m with the shaley M-1.4 reservoir unit separating the two fields (Mudge and Thomson, 1990, Mudge and Curry, 1992, Malek and Mehin, 1998).

Table 1 gives characteristics of corresponding layers, which indicate that the Kingfish M-1.5/M-1.7 reservoirs have relatively high-permeability sands deposited in fluvial/estuarine to upper shoreface depositional environments.

Table 1: Characteristics of the Kingfish and West Kingfish reservoirs (Mudge and Curry, 1992).

Reservoir Average porosity

Average permeability (md)

Average oil saturation

Depositional Environment

M-1.3 0.19 1500 0.63 Lower Shoreface M-1.4 0.19 1500 0.72 Coastal Plain M-1.5 0.21 4800 0.84 Upper Shoreface M-1.7 0.22 4800 0.77 Fluvial/Estuarine

Fig. 3 shows all formations that lie below Kingfish Area, which are considered for CO2 injection. The structural trend suggests injecting CO2 downdip, for example, in interval ‘C’ under Kingfish 4 to the east of the Kingfish Field to maximize the storage capacity of CO2 by allowing it to contact with formation brine. Letting CO2 migrate through the formation brine will leave a trapped amount of CO2 in the formation and moreover allow CO2 to dissolve in the formation brine. Fig. 3 also shows continuous and non-continuous shale layers that may control the upwards movement of CO2 and trap some residual CO2 as well. The porosity-permeability data taken from the core-plug data for all formations within the southern oilfield study area are presented in Fig. 4. A statistical analysis of these data gives a mean of about 400 md and a 1 The figures are at the end of the report.

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median of 52 md. This permeability is about one magnitude of order lower than that of the Kingfish oil-bearing formations (compare with the values given in Table 1), which restricts the injectivity of CO2 considerably when injected downdip.

2.2. Fluid Properties For the numerical simulation of CO2 injection in this study, it was assumed that there was only water in the reservoir initially with the amount of residual oil neglected. Before the simulation of CO2 injection, an attempt was made to history match the oil production from the Kingfish Field by using a three-phase black oil model. The necessary fluid and rock properties for this history matching study were taken from the study of Malek and Mehin (1998). The fluid properties of CO2 and brine were obtained using the GEODISC website calculator for corresponding reservoir pressure and temperature. It was assumed that the brine had a salinity of 2%. Table 2 gives PVT properties used in the simulation.

Table 2: PVT properties used in the simulation of CO2 injection.

Pressure (MPa)

Gas compressibility factor

Gas viscosity (cP)

Gas formation volume factor (m3/sm3)

0.101 0.997 0.0171 1.192 2.76 0.912 0.0174 0.040 10.74 0.639 0.0239 0.007 21.38 0.506 0.0555 0.003 32.02 0.625 0.0726 0.002 40.00 0.727 0.0823 0.002 50.00 0.750 0.0928 0.002 Water salinity 20000 ppm μw 1.03 mPa.s Bw 1.00214 m3/m3

2.3. Capillary Pressure and Relative Permeability Since experimental data on multiphase flow properties such as relative permeability and capillary pressure for this field are lacking, the van Genuchten (VG) model proposed by Preuss et al. (2002) for CO2/water system was used with the parameters tabulated in Table 3. This physically represents the drainage of brine by CO2. The VG model reads for relative permeability:

Table 3: Parameters for the Van Genuchten model.

Parameters Value Swr 0.2 Sgr 0.05 λ 0.4 po 3.58 kPa for Sands

4

( )[ ] 2111

⎭⎬⎫

⎩⎨⎧ −−=

λλ/*g,w

*g,wrg,rw SSk (1)

where,

wr

wrw*w S

SSS−−

=1

(2)

gr

grg*g S

SSS

−

−=

1 (3)

and for capillary pressure of CO2/brine system,

( )[ ] λλ −−−=

11 1/*wcec Spp (4)

where Sw and Sg are water and gas saturations, Swr and Sgr are water and gas residual saturations, krw and krg are water and gas relative permeability, respectively, pce is the entry capillary pressure, and λ is a matching parameter.

2.4. Numerical Model A two-phase GASWATER option of commercial IMEX Black Oil Simulator™ (Computer Modelling Group, Canada) was used to model an immiscible displacement of reservoir brine with CO2. The licence for this simulator was limited to 10,000 grid blocks. Dissolution effects of CO2 in brine, as well as chemical reactions of CO2 with the solid phase (rock matrix) were not considered in this study. Simulations of 25 and 40 years were run as the aim was to examine the CO2 injectivity until the injection ceased. Injection wells in the simulations were constrained with the maximum bottomhole pressure allowed, which was based on the fracture pressure gradient of 15.5 MPa/km (0.69 psi/ft) evaluated at the top depth of each well. The injection pressures in a range from 70% to 90% of the fracture pressure at the corresponding well’s top depth were used in the simulations. The simulations were run for two different commercial injection rates of CO2 for the Kingfish field: 2 ×106 and 15 ×106 tonnes/year (2 and 15 Mt/y).

Infinite aquifers that surround the model area were added in the simulations, which is very critical to understand the behavior of CO2 injectivity because of the fact that, in closed systems, the pressure builds up very quickly. This makes the long-term injection of CO2 difficult. Aquifers are represented in the simulator using one of the analytical methods (The method proposed by Carter and Tracy, 1960, was used in this study), although it is known that analytical models are weak in modeling reservoir fluids flowing back to the aquifer (i.e. they account only for water outflow at the aquifer/reservoir boundary with CO2 remaining in the reservoir). In such cases, the use of numerical aquifers is preferred, which requires a large number of grid blocks in reservoir simulation. For simplified models, like those in this study, it is preferred to use an analytical model to represent surrounding aquifers rather than adding additional grid blocks, which is almost impossible for all aquifers. However, all effort was made to include some portion of aquifers in the grid system to allow the injected CO2 to migrate away from the wells. For the first model run, the initial condition for the reservoir was assumed to be at hydrostatic pressure with the total aquifer volume approximated by the four regions surrounding the reservoir.

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3. Results

3.1. Three-Dimensional Model of Kingfish Field

3.1.1. Model Description A simplified 3-D model of the Kingfish Oil Field was first constructed to develop a history match between the model and the production history. The area of interest for the model was simplified based on the areal and structural maps shown in Fig. 1.

The total number of grid blocks was 3060 (Nx = 34, Ny = 30, Nz = 3), with cell sizes in the x and y direction being 314 m. A variable grid size was used for the vertical direction based on the cross section given in Fig. 1. The top depth of the reservoir was 2224 m. Fig. 5 shows an areal view of the model, which matches field area of about 77 km2. There were 40 producing wells operated from Platforms A and B. There were two infinite-acting analytical aquifers attached to the model with the properties shown in the figure. An average porosity of 21% and average permeability of 5 D was used for this model (Table 1). The initial reservoir pressure of 3318 psi (22.9 MPa) was used for the formation (Malik and Mehin, 1998). The flow rate was 1.3 Msm3/d for the Platform A wells and 0.6 Msm3/d for the Platform B wells, respectively.

For the simulation of CO2 injection, the history-matched model with the following differences was used:

(1) The three-phase model was replaced by a two-phase gas-water model, which was a reasonable change with the depleted amount of the Kingfish oil.

(2) The 3-D reservoir model described above was expanded to be adequate for the Kingfish study area (Fig. 1). The reservoir area now became 296 km2 (21.9 x 13.5 km), which is approximately four times larger than the oil field itself (Fig. 6). This means that a large portion of aquifers surrounding the area of interest were included in the grid system, which affects the prediction of CO2 injectivity due to the limits in the inclusion of aquifers into the simulation. Four surrounding aquifers with the properties shown in Fig. 5 were still added to the model for incorporating infinite-acting aquifers in the system. The total number of grid blocks was 9900 (Nx = 66, Ny = 50, Nz = 3), with cell sizes in the x, y and z direction being 332 m, 270 m and variable, respectively. The reservoir includes only water initially.

(3) The initial reservoir pressure at the datum depth of 2224 m was 3118 psi (21.9 MPa), a value that was obtained by the history-matched model and that represents the stabilized reservoir pressure after closing the reservoir for one year.

3.1.2. History Match The history match between the numerical model and the oil production from the Kingfish Field is shown in Fig. 7. There generally is a good match between the simulation and production, especially in the late production stage. Extending the production time until 2005 using the numerical model, the current situation of the field can be predicted, for example in terms of water-cut and average reservoir pressure as shown in Fig. 8. When all producing wells in the field were shut in this year, according to the validated model, the average reservoir pressure would reach at a value of 22 MPa in 2010, which is a bit lower than the original pressure of 23 MPa. The residual oil saturation in the Kingfish Field is predicted to be approximately 35% in 2005 and the WOC is expected to have moved up to a depth of 2275 m from 2306 m. The predicted oil saturation distribution in Kingfish Oil Field is shown in Fig. 9.

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3.1.3. Sensitivity Study for CO2 Injectivity The 3-D two-phase gas/water model described above was used, based on the validated numerical model for Kingfish Oil Field, to examine the Kingfish Area (only layer ‘A’ in Fig. 3) for the CO2 injectivity. Fig. 10 shows the location of injection wells. Wells were just located in the grid blocks with an appropriate well index and not modelled comprehensively. Thus, the injection rates determined represent those for locations rather than for a specified wellbore. The number of actual wells required may increase depending on the wellbore geometry and data.

The simulation ran for the maximum injection rates with a single injection well (location 1), two symmetrical wells (locations 1 and 4) and four wells (all locations). Two different permeabilities, 1000 and 5000 md and two different injection pressures for the wells, 70% and 90% of the fracture pressure were used. The results are summarized in Table 4.

The numerical results indicate that both the permeability and the maximum injection pressure affect the injectivity of CO2 significantly. An increase in injection pressure from 70% to 90% the fracture pressure increases the flow rate about four times. Similarly a decrease in permeability from 5000 to 1000 md decreases the injectivity of CO2 about three times. The proposed injection rate of 2 Mt/y seems to be applicable with a single injection location for a period of 25 years, but it is very sensitive to the changes in permeability and injection pressure. However, the results indicate that locating two symmetrical wells in the model area guarantees the injection of CO2 with 2 Mt/y in the Kingfish Area with an injection pressure about 90% fracture pressure. Lowering the injection pressure considerably to about 70% fracture pressure, however, may require additional locations for the injection, as the results with four locations show. An assumption that the permeability in this area is high enough and the injection pressure can be set up to 90% fracture pressure may allow an injection of CO2 at a rate of 15 Mt/y.

The saturation distributions of both phases are shown in Fig. 11 as a function of the injection and post-injection period. The local increases in gas saturation at the boundary with analytical aquifers occur due to the insufficient representation of aquifers in the model. As mentioned earlier, analytical aquifer models do not consider a gas outflow from the reservoir and as a consequent gas accumulates at the aquifer boundary during injection. A further investigation is necessary to handle this problem. When injection ceased, the gravity forces dominate the CO2 migration in the high-permeability formation and CO2 moves upwards. At a post-injection period of 1000 years, almost all mobile CO2 will be trapped in the Kingfish Oil Field, as shown in Fig. 11.

Table 4: Results of the sensitivity analysis for CO2 injectivity for an injection period of 25 years.

Case Injection location

Permeability (md)

Max. bottomhole pressure (MPa)

Max. injection rate (Mt/y)

1 1 5000 25.8 (70% Pfrac) 1.8 2 1 5000 33.2 (90% Pfrac) 6.3 3 1 1000 33.2 2.3 4 1+4 5000 33.2 / 34.2 11.8 5 1+4 1000 33.2 / 34.2 4.3 6 1+2+3+4 5000 33.2/33.1/33.0/34.2 19.8 7 1+2+3+4 1000 33.2/33.1/33.0/34.2 7.3 8 1+2+3+4 1000 25.8/25.8/25.7/26.6 2.2

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3.2. Two-Dimensional Model for Latrobe Group Formations

3.2.1. Model Description A simple 2-D model was constructed that approximately describes the cross section depicted in Fig. 3 (see Fig. 12). The total number of grid blocks was 960 (Nx = 64, Ny = 1, Nz = 15), with cell sizes in the x, y and z direction being 500 m, 10,000 m and variable, respectively. The reservoir area now is 320 km2 (32 x 10 km) with no flow in the y-direction. The grid size in the y-direction has an effect on the volume of CO2 to be stored; however, here it is not so critical since two aquifers were attached at the eastern and western edges of the model, which allow the outflow of the displaced brine. An average permeability of 400 md and an average porosity of 20% were used, based on the porosity-permeability data shown in Fig. 4.

3.2.2. Numerical Results Table 5 gives the results of various scenarios for the injection of CO2. The wellbore geometry was not included in the model, thus the injectivity values represent those for locations rather than specific wellbores. In the cases where CO2 is injected in several layers, each layer has a perforation isolated from other layers. To do this in the model, a separate well is just located in each layer. Numerical results indicate that injection downdip in interval ‘C’ seems to be an optimum solution since the maximum injection rate determined is almost similar to that for the case where all layers are open to flow. This result supports the initial plan in which CO2 is injected downdip in interval ‘C’ to allow a larger contact area between CO2 and rock and brine, which is expected to increase the trapped volume of CO2.

A sensitivity analysis was performed for Case 1 to examine the effect of the injection period on the injectivity. The results shown in Fig. 13 demonstrate that, for the given case, there is negligible effect on the injectivity for the early stage of injection (up to 10 years) however, in later stage of injection, the injectivity decreases as the injection period increases. For this special case, the rate of decrease in the injection rate is determined to be approximately 0.13 Mt/y for the later stage of injection.

Table 5: Numerical results for 2-D model of the Kingfish simulation area for an injection period of 40 years.

Case Injection location

Max. bottomhole pressure (MPa)

Max. injection rate (Mt/y)

1 A 32.8 4.2 2 A’ 34.2 4.7 3 B 36.5 5.9 4 C 39.4 7.1 5 A+A’ 32.8/34.2 5.5 6 A+A’+B 32.8/34.2/36.5 6.4 7 All Layers 32.8/34.2/36.5/39.4 7.3

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3.3. Three-Dimensional Model for Latrobe Group Formations

3.3.1. Model Description The cross section shown in Fig. 3 was simplified in a way that ignores the top surface geometry and considers a flat top for simplicity. A simple 3-D model was then constructed with a total number of grid blocks of 9801 (Nx = 33, Ny = 33, Nz = 9), with varying cell sizes in the x, y and z direction having refined grids around the wellbores. The formation properties are given in Table 6 for this simplified model. The reservoir area now is 207 km2 (14.4 x 14.4 km). The plan was to inject CO2 deeply in interval ‘C’ at 15 Mt/y for a period of 40 years. The shale barriers in the formations were included in the numerical model by means of a reduced vertical permeability. A ratio of 0.05 for the vertical to lateral permeability was used. The model is a box-shaped, so a platform was first put at the center of the model that allows drilling many wells in there with a well spacing of approximately 500 m.

All vertical and horizontal wells were modeled for an injection tubing having ID=8.6 inch. All grid blocks around the wells were refined. All wells were located in a region at the center of simulation area with a spacing of approximately 500 m and fully-penetrating in interval ‘C’.

Table 6: The formation properties for the simplified 3-D model.

Interval Depth (mSS)

Thickness (m)

Permeability (md)

Porosity (%)

Gurnard 2224-2249 25 12 6.7 A 2249-2375 126 166 16.1 A’ 2375-2566 191 130 17.2 B 2566-2792 226 154 16.3 C 2792-3006 214 143 15.8

3.3.2. Numerical Results

3.3.2.1. Vertical Wells The numerical results are summarized in Table 7. For the injection rate of 2 Mt/y, two wells with a well spacing of 500 m seem to be sufficient. In Case 1, five vertical wells are located in the simulation area as the well placement pattern is shown in Fig. 14. Each well has a constant and equal injection rate. The injection pressure was 39 MPa, a 90% the fracture pressure at the top depth of interval ‘C’. The maximum total injection rate was predicted to be 5.8 Mt/y (Table 7), which is sufficient for the commercial rate of 2 Mt/y, but not for 15 Mt/y. A sensitivity run shows that additional 18 vertical wells may be required for 15 Mt/y, provided that an injection pressure is taken 90% fracture pressure into account. These 18 vertical wells are placed at the center of the model with a well placing of about 500 m, shown in Fig. 15. The effect of injection pressure on the number of the vertical wells required to inject CO2 at 15 Mt/y was also examined with various reruns of the model with different injection pressures. Results are summarized in Table 7 and plotted in Fig. 16. Fig. 15 shows the placement of the required wells in the simulations area. The results provide a conclusion that as the injection pressure approaches to the reservoir pressure, or in the other words, as the wells are constrained with a very conservative value of the fracture gradient, the number of wells required increases dramatically. For example, the number of wells required for the injection pressure with 75% fracture pressure is more than twice that for the pressure with 80% fracture pressure.

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Table 7: Numerical results for 3-D simulations.

Case Max. bottomhole pressure (MPa)

Max injection rate (Mt/y)

Number of wells required

1 39.0 (90% Pfrac) 5.8 5 2 39.0 (90% Pfrac) 15.0 18 3 36.8 (85% Pfrac) 15.1 29 4 34.6 (80% Pfrac) 15.0 40 5 32.4 (75% Pfrac) 15.0 93 6 39.0 (90% Pfrac) 2.0 2

Fig. 17 shows a relation between the formation permeability and the number of the vertical wells required for 15 Mt/y. The same model adjusted with various values of constant and uniform permeability was used to obtain this figure. As shown in the figure the formation permeability is of great importance for the injectivity of CO2. The data point at the lowest permeability is an approximate value rather than a numerical result. The results presented in Figs. 16 and 17 should be assessed together to determine the correct number of the wells required for 15 Mt/y.

3.3.2.2. Horizontal Wells Fig. 18 shows another sensitivity analysis for the cases where horizontal injectors are located. A constant and uniform permeability of 150 md was used in the simulation. All horizontal wells are fully-penetrating and located at the center of interval ‘C’ as depicted in Fig. 18. The length of the horizontal wellbore is assumed to be 1.2 km. The numerical results show that at least 12 horizontal injectors are required to meet a total injection rate of 15 Mt/y. For the same conditions, the simulations results demonstrate that at least 18 vertical wells are required for 15 Mt/y. A further investigation for different lengths of horizontal wellbore as well as different placements in the formation would be worthwhile to understand the effect of horizontal wells on CO2 injectivity. The same fracture gradient was used for horizontal well as used for the vertical case. This may be re-examined with the correct gradient for horizontal wells.

The 3-D model described in Section 3.3 should be improved that it includes continuous and non-continuous shale barriers as well as formation top depths.

4. Conclusions The following conclusions can be drawn from this numerical study: (1) the proposed rates of 2 Mt/y and 15 Mt/y seem to be applicable for the Kingfish Field Area, (2) the required number of wells is very sensitive to the formation permeability, maximum bottomhole pressure allowed, and the period of injection, and (3) the horizontal wells are advantageous over vertical wells in terms of the number of individual wells.

Acknowledgements We thank C. Gibson-Poole for her contributions in the reservoir description part and reviewing the manuscript, J. Ennis-King for providing the details for the model described in Section 3.3, and G. Allinson, P. Neal and R. Dunsmore for discussions of the results.

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References Carter, RD and Tracy, GW, 1960, An improved method for calculating water influx, Petroleum Transactions, American Institute of Mining Engineers, v. 219, 415-417.

Gibson-Poole, CM and Svendsen, L, 2005, Reservoir characterization and geological model, Kingfish Field/Southern Oil Fields area, Gippsland Basin, SE Australia: Implications for CO2 storage. Australian School of Petroleum, The University of Adelaide, Adeliade. CO2CRC Report No. RPT05-0041.

Malek, R and Mehin, K, 1998, Oil and gas resources in Victoria, Department of Natural Resources and Environment, Melbourne, ISBN: 0 7306 9449 6.

Mudge, WJ and Thomson, AB, 1990, Three-dimensional geological modeling in the Kingfish and West Kingfish oil fields: The method and applications, The APEA Journal 30(1) 342-354.

Mudge, WJ and Curry, JJ, 1992, Development opportunities in the Kingfish and West Kingfish Fields, Gippsland Basin, The APEA Journal, 9-18.

Preuss, K, et al., 2002, Intercomparison of Numerical Simulation Codes for Geologic Disposal of CO2, Technical Report, LBNL-51813, Lawrence Berkeley National Laboratory, Berkeley, CA, U.S.A.

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Figures

Figure 1: LVCSA study areas in Gippsland Basin for numerical simulation (Gibson-Poole and Svendsen, 2005).

12

Figure 2: Depth structure maps and cross-section of the Kingfish and West Kingfish Fields (Malek and Mehin, 1998).

13

Figure 3: Continuous and non-continuous shale layers in the Kingfish Area (Gibson-Poole and Svendsen, 2005).

14

Porosity vs Permeability - All Wellsy = 0.0298e0.377x

R2 = 0.5079

0.01

0.1

1

10

100

1000

10000

100000

0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0

Porosity (%)

Perm

eabi

lity

(mD

Figure 4: Porosity-permeability correlation of core-plug data for all formations within the southern oil field study area (Gibson-Poole and Svendsen, 2005).

15

Figure 5: Areal view of 3-D Model of the Kingfish Field.

16

Figure 6: Enlarged 3-D Model for the Kingfish Simulation Area.

17

Figure 7: History match between the oil production from the Kingfish Field and the numerical model.

18

Figure 8: Numerical results for water-cut and average reservoir pressure for the Kingfish Field.

19

Figure 9: Predicted oil saturation distribution in the Kingfish Oil Field in 2005.

20

Figure 10: Injection locations in the Kingfish simulation area.

21

Figure 11: Simulation results of CO2 migration during injection and post-injection periods (Case 7 in Table 4).

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Figure 12: Simplified 2-D model for the Latrobe Formations in the Kingfish Simulation Area.

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Figure 13: Variation of maximum injection rate as a function of injection period (Case 1).

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Figure 14: Schematic of grid scheme of the reservoir.

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Figure 15: Various scenarios of vertical wells for 15 Mt/y with different injection pressures.

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Figure 16: Number of vertical wells required for 15 Mt/y as a function of injection pressure.

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Figure 17: A relation between formation permeability and no of injection wells required for 15 Mt/y.

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Figure 18: Schematic of the placement of horizontal injectors for 15 Mt/y.