Simulation Final Project(Fall 2011)

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1.0 INTRODUCTION:Reservoir simulation is an area of reservoir engineering in which computer models (created by Reservoir Simulators) are used to predict the flow of fluids (typically, oil, water, and gas) through porous media (Reservoir).

There are different types of simulators today and they all have their different uses under the different classifications of reservoir simulation. This could range from applications in black oil simulation, compositional, chemical flooding or even Multi-purpose simulation. There are many different reservoir simulation software packages such as Eclipse and Stars, but for the purpose of this project we will be making use of CMG’s ‘BUILDER’ and ‘IMEX’ and ‘RESULTS’. The Model (Base case) will be built using BUILDER, we will be running the models in IMEX, and we will view and compare results in RESULTS. BUILDER is an application used in the preparation of reservoir simulation models. RESULTS is A CMG application designed for visualizing and reporting simulator output. It enables users to efficiently analyze the output from CMG simulators. It can prepare 2D and 3D plots and generate various informative graphs, and prepare tables of required information to be included in a study report. IMEX is a full featured Black oil Simulator developed by Computer Modeling Group (CMG). IMEX models the flow of three phase fluids in gas, gas-water, oil-water, and oil-water-gas reservoirs. It models in one, two, or three dimensions, including complex heterogeneous faulted structures.

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1.1 WHY DO WE NEED RESERVOIR SIMULATION?

Reservoir simulation can be important in both situations of new fields and in developed fields. Models are used in developed fields where production forecasts are needed to help make investment decisions. In the case of new fields, reservoir simulation models may be found instrumental in identifying the number of wells required, the optimal completion of wells, the present and future needs for artificial lift, and the expected production of oil, water and gas through forecasting. Reservoir simulation can be used to identify opportunities to increase oil production in heavy oil deposits.

1.2 OBJECTIVES OF THIS PROJECT

To build a model of the reservoir and to examine its performance in terms of production and pressure.

Performance a History matching of the model to production and pressure data at our disposal.

To predict Future performance for 5 years as-is – that is, make the forecast based on the history matched model as-is.

To find ways to increase ultimate recovery by trying out five other scenarios (In addition to the ‘as-is’ scenario) and to determine which is most economical by creating and comparing different Scenarios.

1.3 METHODOLOGY This project will be carried out in steps to coincide with the objectives of this project. As mentioned earlier, this model will be built using CMG’s ‘BUILDER’, and it will be run with ‘IMEX’ and results will be compared in a graphical manner using ‘RESULTS’.

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DEVELOPING THE BASE CASE MODEL

2.1 STEP 1- BUILDING THE MODEL USING BUILDER This step involves reservoir characterization in terms of four components. The combination of these four components is used to create the model using Builder. The Components are:

Geological data Fluid model/fluid properties. Reservoir properties data Production/Injection constraints

The files needed to build to this model are:

Table 1: Files defining the geological parameters for the model.

Type of file/use File Name

Production History data file Production-history.prd

Porosity data file Porosflt.bna

Top of Structure Map file TO10FLT.bna

Grid Thickness data file Thickflt.bna

Well Trajectory data file TRAJ_Meter.wdb

Well perforation data file PERFS_Meter.perf

2.1.1. GEOLOGICAL COMPONENT:

This component identifies all key factors that will affect flow through the reservoir. Step 1: The Builder icon was clicked to launch builder from inside the CMG software and the simulation settings were:

IMEX for simulator type, other options there were GEM and STARS. But for this purpose of this project we will be using IMEX.

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The working unit for this project is SI units.

And the porosity was set to ‘single porosity’ because we are going to assign a single porosity to all layers of this model

The Date was set to 1991-01-01

Figure 1: Top-of-structure contour map imported from map file, TO10FLT.bna

Step 2: This step involves creating a grid. The reservoir has to be defined by a set of grid blocks whose properties, dimensions and boundaries are well defined. The reservoir will be gridded in three dimensions, that is to say, it will be gridded in the i, j and k direction.

A new ‘’Orthogonal Corner Point’’ grid block is created. For this model, we will be requiring 25 grids in the i-direction, 35 grids in the j-direction and 4 grids in the k-direction

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So now, it has to be specified what the length of each grid block would be. For this model, the grid block in the i-direction will be 110 meters in length (that is, 25*110); the j-direction grid blocks will be 135 meters in length (that is, 35*125). No length will be entered for the k-direction blocks. This is controlled by the geological structure imported from the map file.

The New grid created is then overlaid on the contour map already displaying in the screen, in such a way that it covers all parts of the contour map and it was ensured that it was aligned with the fault line on the contour map (see figure 2 below).

Figure 2: Contour map with overlaying ‘Orthogonal Corner Point grid blocks.

At this point, the property of the grid blocks will be defined as follows:

Grid top: This is gotten from the top-of-structure map file, TO10FLT.bna. This is inputted into layer 1( the top layer)

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Figure 3: Model showing Grid Top

Grid thickness: The grid thickness data is gotten from one of the files earlier mentioned; Thickflt.bna. This file is dropped on layer 1 and multiplied by 0.25 since this thickness has to be shared by 4 grid blocks in the k-direction. This is copied to Layer 2, 3 and 4. Figure 4 below shows the Grid Thickness of the model.

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Figure 4: Model showing Grid Thickness

Porosity: The porosity was set by importing the geological map for porosity, Porosflt.bna, into layer 1.This same value was copied to Layers 1, 2 and 3. This means that we are giving the reservoir a single porosity value. After loading the Porosity file, this is what the model looks like (figure 5 below).

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Figure 5: Model showing Grid Porosity

Permeability: The ‘’permeability I’’ was set as follows: Layer 1 - 50 Layer 2 - 250 Layer 3 - 500 Layer 4 - 100

‘’Permeability J’’ was set as ‘’EQUALSI’’ for the whole grid-block. ‘’Permeability K’’ was set as ‘’EQUALSI’’ to apply a Kv/Kh ratio of 0.1.

Rock Compressibility = 2E-5 1/kPa

Reference pressure = 20,000 kPa

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2.1.2 PVT DATA At this stage, a black oil model will be created using correlations. The following are the values different parameters that will be used to generate the PVT data for this black oil model.

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Parameters Values Comments

Reservoir Temperature 70 in centigrade

Generate data up to max. Pressure of 35,000 In kPa.

Bubble point pressure calculation 6,500 In kPa.

Oil density @ STC (14.7psia,60F) 35 Stock tank oil gravity (API)

Gas density @ STC (14.7psia,60F) 0.65 Gas gravity (Air 1)

Reference pressure for water properties 20,000 In kPa

Water Salinity(ppm) 10,000

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Figure 7: A graph of Rso and Bo vs. Reservoir Pressure (Base Case)

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Table 3: PVT Table with values generated using the quick Black Oil Model

P Rs

(m3/m3) Bo Eg (m3/m3)

OIL VISCOSITY

GAS VISCOSITY

ROCK COMPRESSIBILITY(1/KPA)

101.325 0.678902 1.0455 0.84551 2.54115 0.0125 4.35E-06

527.904 2.08715 1.04838 4.43496 2.40806 0.012541 4.35E-06

954.482 3.69433 1.0517 8.07294 2.27459 0.012595 4.35E-06

1381.06 5.43371 1.05531 11.7597 2.1482 0.012658 4.35E-06

1807.64 7.2747 1.05917 15.4955 2.03107 0.012728 4.35E-06

2234.22 9.19919 1.06324 19.2803 1.92355 0.012804 4.35E-06

2660.8 11.1951 1.06749 23.1141 1.82526 0.012887 4.35E-06

3087.37 13.2536 1.0719 26.9967 1.73552 0.012975 4.35E-06

3513.95 15.3682 1.07648 30.9277 1.65354 0.013068 4.35E-06

3940.53 17.5335 1.0812 34.9066 1.57856 0.013167 4.35E-06

4367.11 19.7454 1.08605 38.9328 1.50986 0.013272 4.35E-06

RELATIVE PERMEABILITY CURVES The relative permeability curves were generated using the following correlations. Table 4: Parameters for the analytical relative permeability curve generation.

Parameters Values

Connate Water Endpoint Saturation (SWCON) 0.2

Critical Water Endpoint Saturation(SWCRIT) 0.2

Irreducible Oil for Water-Oil Table - Endpoint Saturation(SOIRW) 0.4

Residual Oil for Water-Oil Table-Endpoint Saturation(SORW) 0.4

Irreducible Oil for Gas-Liquid Table Endpoint Saturation(SOIRG) 0.2

Residual Oil for Gas-Liquid Table Endpoint Saturation(SORG) 0.2

Connate Gas - Endpoint Saturation(SGCON) 0.05

Critical Gas- Endpoint Saturation(SGCRIT) 0.05

Kro at Connate Water(KROCW) 0.8

Krw at Irreducible Oil(KRWIRO) 0.3

Krg at Connate Liquid(KRGCL) 0.3

Krog at Connate Gas(KROGCG) 0.8

Exponent for calculating Krw from KRWIRO 2.0

Exponent for calculating Krow from KROCW 2.0

Exponent for calculating Krog from KROGCG 2.0

Exponent for calculating Krg from KRGCL 2.0

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The above Parameters generated the following Relative permeability Plot.

Figure 8: Relative permeability curve (for base_case) generated by the correlation in table 2.

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Below is the Relative permeability table for the above plot.

Table 5: Table showing values for the above Relative Permeability plot.

2.1.3 INITIAL CONDITIONS The initial conditions for this model are as follows:

Table 6: Parameters for the Initial Condition

Initial fluid in the reservoir Water, oil and gas

Reference Pressure 27,600 kPa

Reference Depth 3,050 m

Water-oil Contact 3,080 m

Gas-Oil Contact 1,980 m

Constant Bubble Point Pressure 6500 kPa

Note: The Water-Oil contact is above the reference Depth and below the Gas-oil contact (meaning it is in the oil region).Also the bubble point is below the Reference pressure (which means that the reservoir is above bubble point pressure).

Sw krw krow

0.2 0 0.8

0.225 0.001172 0.703125

0.25 0.004688 0.6125

0.275 0.010547 0.528125

0.3 0.01875 0.45

0.325 0.029297 0.378125

0.35 0.042188 0.3125

0.375 0.057422 0.253125

0.4 0.075 0.2

0.425 0.094922 0.153125

0.45 0.117187 0.1125

0.475 0.141797 0.078125

0.5 0.16875 0.05

0.525 0.198047 0.028125

0.55 0.229688 0.0125

0.575 0.263672 0.003125

0.6 0.3 0

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2.1.5 WELL TRAJECTORIES AND PERFORATIONS The file, TRAJ_Meter.wdb, for well trajectory is imported in table format and with units in meters (m) under the Well & Recurrent menu in Builder. This imports Well trajectory for 10 Wells, Well 1-10.

Figure 9: Model showing well (vertical) trajectories

Perforation intervals for each well were importing file from the well perforation file, PERFS_Meter.perf, into the builder in order to define trajectory perforations on each well. It should be noted that ‘WELL 7’’ has no perforation data.

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2.1.6 HISTORICAL PRODUCTION/INJECTION DATA At this stage the Field historical production data will be imported from Production History file, Production-history.prd. This file should contain Production/injection data for fluids produced and/or injected through these wells, in and out of the reservoir. The Field history file provides a means of History Matching. Without this file there can be no history matching of the model and history data. It is noted that for those wells with production data, the first date is 31st December, 1991. There was no production data for ‘wells 5, 7 and 9’. Since those three wells (5, 7 and 9) have no production/injection data, we can either delete them or define them as a producer or injector and shut-in the wells so that they will not affect the history match. For the purpose of this project, ‘Well 5’ was set as a producer and Shut-in on 1991-01-01 (1st January, 1991) and ‘Wells 7 and 9’ were made injectors and Shut-in on 1991-01-01 (1st January, 1991)

Well 5 was constrained to operate at a minimum of 200kPa and ‘wells 7 and 9’ were constrained to operate at a maximum pressure 25,000kPa (that is to say that they will operate only when the BHP drops below 25,000kPa.The injected fluid for the injector wells, 7 and 9 is water.

An .fhf file is then created for the production history data so that we can make a comparison between the simulation run and the actual field history file in ‘Results’. As there is no perforation information for ‘Well 7’ in ‘PERF_Meter.perf’ file .The perforation was done manually by adding a new completion in Well & Recurrent menu. The perforations were done on the 1st, 2nd and 3rd layer (Gridlocks) in the K-direction as shown below.

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Model showing Perforated zones for ‘Well 7’ view from the ‘’IK-2D X-Sec’’

view type

2.1.7 RESTART At this point, a restart file was created. Restart runs are used to break a simulation run into a sequence of (shorter) simulation runs. For example, you could run one simulation for the history portion of a simulation, and then run several forecast runs, each for a different development scenario, without having to repeat the simulation of the historical period. The restart date was set to 1991-01-01 which is the first simulation date. So we can have all we have inputted into the model up to this point.

Well 7

Well 7

0 1,000 2,000

0 1,000 2,000

3,0

00

3,1

00

3,2

00

2,9

00

3,0

00

3,1

00

3,2

00

0.00 1085.00 2170.00 feet

0.00 0.25 0.50 0.75 1.00 km

File: Base_Case.datUser: 541860Date: 11/23/2011

Scale: 1:16984Z/X: 6.00:1Axis Units: m

2,987

3,005

3,023

3,041

3,059

3,076

3,094

3,112

3,130

3,148

3,166

Grid Top (m) 1991-01-01 J layer: 15

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Figure 11: Completed Base-Case Model (Showing well names and trajectories) just before running in IMEX

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2.1.8 RESULTS The Base-Case model was run in IMEX, and below is the cumulative fluid production data for the field, for gas, oil, water, and liquid (water+ oil).

Figure 12: Graph showing the Cumulative fluid production in this field.

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3.0 HISTORY MATCHINGHistory matching is the process of adjusting a reservoir model until it closely reproduces the past behavior of a reservoir. The historical production and pressures are matched in the best way possible. It is important to note that the accuracy of the history-match depends greatly on the quality of the reservoir model created and the quality and quantity of pressure and production data. So here we are trying to match two variables (from history Data):

1. Pressure 2. Production data

First, it is important to compare the Cumulative fluid production in the Base-Case model with that of the actual field Production history and Pressure data, so that we can determine how far away we are from matching the model with the history data and what needs to be adjusted in order to successfully history-match this model.

Figure 13: Graph showing the Cumulative fluid production for the Base-Case model in comparison with the Field history data.

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Discussion: From the above graph, the following can be observed:

The Cumulative oil production (SC) in the Base-Case is higher than that of the production history.

The Cumulative water production (SC) in the Base-Case is lower than that of the production history.

The Cumulative liquid production (SC) in the Base-Case matched exactly that of the production history.

The Cumulative gas production (SC) in the Base-Case is higher that of the production history.

What we can do to match this could be that we can increase the Gas-to-oil ratio in order to increase the dissolved gas (hence reducing the oil viscosity) thereby causing the oil

3.1 GOR MATCHING First we took a look at the GOR for the Base Case and production history to see if it matches.

Figure 14: GOR Comparison between Base Case and Production History before increasing Rso

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From Figure 14 above, we see that the Base Case GOR is lower than that of the production history, we will increase it by changing the Rs from table 3 above, the RSOb (RSO at bubble point pressure) is 31.3963. What we can do to match this could be that we can increase the Gas-to-oil ratio (RSo) in order to increase the dissolved gas (hence reducing the oil viscosity) thereby causing the oil to flow more easily.

Figure 15: GOR Comparison between Base Case and Production History after increasing Rso

From the Figure above, it can be seen that by changing the Gas-to-oil ratio from 31.3963 to 37 we were able to match exactly the GOR of the Production History.

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3.2 PRESSURE MATCHING

Let’s now see if the pressure is matching.

Figure 16: Graph showing Reservoir pressure for Base Case overlaying Pressure History From the Above graph, one can see that the pressure in the base case does not match that of the pressure history, in fact, it is lower than that of the pressure history. We have to match that.

To do this, we incorporated an aquifer with the following configuration. Location: Bottom Thickness: 12m Porosity: 0.2 Permeability: 100md Radius: 1500m Modeling method: Carter-Tracy (Infinite extent)

No leakage allowed.

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Figure 17: Graph showing Reservoir pressure for Base Case overlaying Pressure History after Aquifer.

From the graph in figure 15 above, it can be seen that we were able to match the pressure history considerably well by incorporating the aquifer.

3.3 RELATIVE PEMEABILITY ADJUSTMENTS

The cumulative liquid production matched, but the water and oil production didn’t match. The water and the oil make up the ‘liquid’ component. If something is done to the water saturation, it will potentially affect the oil saturation which would increase the oil production, thus pushing it up to match with the production history cumulative oil production (SC). The water possibly has reduced mobility, Mobility, k/µ, is defined as the permeability of a porous material to a given phase divided by the viscosity of that phase, if we have to increase the mobility, we have to either increase the

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Permeability, k, or reduce the viscosity, µ, but it will be more practical to increase the permeability than to reduce the viscosity of fluid in a reservoir.

In the base Case, The KRWIRO-Krw at irreducible oil saturation was increased from 0.3 to 0.5 and then finally to 0.8, where we got a match for the Oil and water production. Below are two diagrams showing the match at 0.5 and 0.8. Please note: figure 8 shows the match when the KRWIRO was at 0.3. The Figures below show the relative permeability/saturation curves and the matches between the Base Case and History data at 0.5 and 0.8 Krw (at irreducible Oil saturation) respectively.

Figure 16: Relative permeability curve (for base-case) after KRWIRO was adjusted to 0.5

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Figure 19: Fluid Production comparison (for base-case) after KRWIRO was adjusted to 0.5

At KRWIRO of 0.5, the oil and water production in the base case still did not match that of the production history, but again, the liquid production matched. So we took further step to increase the KRWIRO to 0.8.

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The Figures below shows relative permeability/saturation curves and the matches between the Base Case and History data at 0.8 Krw (at irreducible Oil saturation).

Figure 20: Relative permeability curve (for base-case) after KRWIRO was adjusted to 0.8

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Figure 21: Fluid Production comparison (for base-case) after KRWIRO was adjusted to 0.8

Now we have a match!

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From the figure 19 above, it can be seen that we have gotten a match for oil and water production. The gas is way off, but since this reservoir is production above bubble point pressure, then we do not really care about the gas, since there is no free gas.

At the end of history match, the fluid production (volumes) is shown in the table below.

Table 7: Fluid production after History Match

Cum. Water Prod. Cum. Oil Prod.(m3) Cum. Oil Prod.(bbl.)

Cum Gas Prod.

139,860.00 788,850.00 4,961,866.50 29,187,000.00

139,860.00 788,850.00 4,961,866.50 29,187,000.00

139,860.00 788,850.00 4,961,866.50 29,187,000.00

139,860.00 788,850.00 4,961,866.50 29,187,000.00

139,860.00 788,850.00 4,961,866.50 29,187,000.00

139,860.00 788,850.00 4,961,866.50 29,187,000.00

What’s next? Now that we have successfully achieved a history match, we are going to run a forecast for five years in order to perform some economic evaluations. For the purpose of this project, we will consider 6 different scenarios for which we will run a forecast for five years.

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After successfully getting a history-match for the model, a 5-year forecast will now be made based on the six different scenarios below. The history matching was from 1991-01-01 to 1991-09-01. The Forecasting starts from 1991-12-01. The following scenarios will be examined and evaluated for their economics.

1. Forecasted ‘As-is’: That is operating at the current conditions (conditions just after history matching)

2. Drill a horizontal well (well 11) on Dec.1st, 1991 and operate the rest of the well at their

current condition

3. Open ‘well 5’ on Dec. 1st, 1991 and operate the rest of the well at their current condition

4. Drill a horizontal well, ‘well 11’ & open ‘well 5’ on Dec 1st, 1991 and operate the rest of

the well at their current condition

5. Drill ‘well 11’, open ‘well 5’ & start injection on well 7& 9 on Dec 1, 1991 and operate the rest of the well at their current condition

6. Acidize the Horizontal and frac. Vertical well in scenario 5 and operate the rest of the

well at their current condition. (From case 5, frac. well 5 and give its skin factor as -4 and acidize well 11 and give it a skin factor of -2)

SCENARIO 1: Forecasted ‘As-is’

This scenario involves operating the well at the ordinary conditions. By ordinary conditions, we mean, conditions just after the history-matched model and no extra well or alterations were made. Below is a graph to show the cumulative fluid production (field) for each fluid; oil, water, and gas.

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Figure 22: Cumulative Fluid production for Case 1

The fluid production after forecasting Case/scenario 1 is shown in the table below. Table 8: Cumulative fluid production (volume) for Case 1

Forecast Case

Cumulative Oil Prod.

Cumulative Oil Prod.

Cumulative water Prod.

Cumulative Gas Prod.

(m3) (bbl.) (m3) (m3)

Case 1 3,540,400 22,269,116 1,161,790 130,995,000

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4.2 SCENARIO 2: Drill a horizontal well (well 11) on Dec.1st, 1991 and operate the rest of the well at their current condition. ‘Well 11’ was constrained to operate at a minimum BHP of 20,000kPa. Well 11 is a producer well.

Figure 23: Cumulative Fluid production for Case 2

Table 9: Cumulative fluid production (volume) for Case 2

Forecast Case

Cumulative Oil Prod.

Cumulative Oil Prod.

Cumulative water Prod.

Cumulative Gas Prod.

(m3) (bbl.) (m3) (m3)

Case 2 6,028,680 37,920,397 4,342,400 223,061,000

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4.3 SCENARIO 3: Open ‘well 5’ on Dec. 1st, 1991 and operate the rest of the well at their current condition. On Dec. 12st, 1991; well 5 was opened (as a producer) and constrained to operate at a minimum BHP of 20,000kPa.

Figure 24: Cumulative Fluid production for Case 3 The fluid production after forecasting Case/scenario 3 is shown in the table below. Table 10: Cumulative fluid production (volume) for Case 3

4.4 SCENARIO 4: Drill a horizontal ‘well 11’& open ‘well 5’ on Dec 1st, 1991 and operate the rest of the well at their current condition. ‘Well 5’ was opened (as a producer) and constrained to operate at a minimum BHP of 20,000kPa while ‘Well 11’ was constrained to operate at a minimum BHP of 20,000kPa. Well 11 is a producer well.

Forecast Case Cumulative Oil Prod.

Cumulative Oil Prod.

Cumulative water Prod.

Cumulative Gas Prod.

(m3) (bbl.) (m3) (m3)

Case 3 4,003,840 25,184,154 4,119,210 148,142,000

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Figure 25: Cumulative Fluid production for Case 4 The fluid production after forecasting Case/scenario 4 is shown in the table below. Table 11: Cumulative fluid production (volume) for Case 4

4.5 SCENARIO 5: Drill ‘well 11’, open ‘well 5’ & start injection on well 7& 9 on Dec 1, 1991 and operate the rest of the well at their current condition. The initial constraint of Well 7 & 9 (both injector wells) was constrained to function when the BHP gets to a maximum of 25,000.

Forecast Case

Cumulative Oil Prod.

Cumulative Oil Prod.

Cumulative water Prod.

Cumulative Gas Prod.

(m3) (bbl.) (m3) (m3)

Case 4 6,126,380 38,534,930 6,514,510 226,676,000

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The trigger was constrained to ‘open well 7’ and ‘open well 9’ when the ‘Pore volume weighted pressure’ is less than 24,000kPa.

Figure 26: Cumulative Fluid production for Case 5 The fluid production after forecasting Case/scenario 5 is shown in the table below. Table 12: Cumulative fluid production (volume) for Case 5

4.6 SCENARIO 6: Acidize the Horizontal Well (well 11) and frac. Vertical well (well 5) in scenario 5 and operate the rest of the well at their current condition. ’Well 5’ was frac’d it’s skin factor set to -4 and ‘well 11’ was acidized its skin factor was set to -2.

Forecast Case

Cumulative Oil Prod.

Cumulative Oil Prod.

Cumulative water Prod.

Cumulative Gas Prod.

(m3) (bbl.) (m3) (m3)

Case 5 6,135,900 38,594,811 6,739,270 227,028,000

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Figure 27: Cumulative Fluid production for Case 6 The fluid production after forecasting Case/scenario 6 is shown in the table below. Table 13: Cumulative fluid production (volume) for Case 6

4.7 COMPARISON BETWEEN SCENARIOS

This section compares each fluid in all six forecast scenarios.

Forecast Case Cumulative Oil Prod.

Cumulative Oil Prod.

Cumulative water Prod.

Cumulative Gas Prod.

(m3) (bbl.) (m3) (m3)

Case 6 6,807,740 42,820,685 9,515,260 251,886,000

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4.7.1 OIL PRODUCTION

Figure 28: Cumulative Oil production comparison for all cases From the above figure (graph), Case 6 has the most oil production.

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4.7.2 WATER PRODUCTION

Figure 29: Cumulative Water production comparison for all cases From the above figure (graph), Case 6 has the most water production.

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4.7.3 GAS PRODUCTION

Figure 30: Cumulative Gas production comparison for all cases

From the above figure (graph), Case 6 has the most gas production.

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5.0 ECONOMIC EVALUATION

Table 16: Cost overview for drilling and other well services

Cost of drilling: Vertical well $1.5million

Horizontal well $3 million

Operating Cost $5/bbl. of oil

Water disposal Cost $2/m3 of water

Average oil price $18/bbl.

Fracturing' job $250,000

Acidizing' job $75,000

5.1 FLUID MANAGEMENT

5.1.1 INCREMENTAL FLUID VOLUME The incremental fluid volume is a difference between the cumulative fluid production (volumes) at the end of the forecasting and the cumulative fluid production (volumes) at the end of History-Matching. Table 17: Table Showing Incremental Fluid Production

FORECAST END OF HISTORY MATCHING

INCREMENTAL PRODUCTION

Forecast Case

Cumulative Oil Prod.

Cumulative water Prod.

Cumulative water Prod.

Cum. Oil Prod.

Incremental Oil Prod.

Incremental Oil Prod.

Incremental Water Prod.

(m3) (m3) (m3) (m3) (m3) (bbl.) (m3)

Case 1 3,540,400 1,161,790 139,860.00 788,850.00 2751550 17307249.5 1021930

Case2 6,028,680 4,342,400 139,860.00 788,850.00 5239830 32958530.7 4202540

Case 3 4,003,840 4,119,210 139,860.00 788,850.00 3214990 20222287.1 3979350

Case 4 6,126,380 6,514,510 139,860.00 788,850.00 5337530 33573063.7 6374650

Case 5 6,135,900 6,739,270 139,860.00 788,850.00 5347050 33632944.5 6599410

Case 6 6,807,740 9,515,260 139,860.00 788,850.00 6018890 37858818.1 9375400

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5.1.2 DISPOSAL WATER This is the amount of water available to be disposed. It is the difference between the Incremental water produced and the water injected. Table 18: Volume of Water to Be Disposed

5.2 COST ANALYSIS 5.2.1 COST OF DRILLING, ACIDIZING & FRAC JOB FOR EACH CASE Table 19: Drilling, Acidizing & Frac. Job cost calculation

FORECAST CASE CUMULATIVE WATER INJECTED

INCREMENTAL WATER PROD.

DISPOSAL WATER

(m3) (m3) (m3)

Case 1 0.00 1021930 1161790

Case2 0.00 4202540 4342400

Case 3 0.00 3979350 4119210

Case 4 0.00 6374650 6514510

Case 5 695280 6599410 6043990

Case 6 1972700 9375400 7542560

FORECAST CASE EXTRA COST/INVESTMENT (DRILLING OR ACIDIZING & FRAC. JOB)

(MM$)

Case 1 0

Case2 3

Case 3 0

Case 4 3

Case 5 3

Case 6 3.325

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5.2.2 OPERATING COST Below is the operating cost, based on $5/bbl. of oil Production (Incremental) Table 20: Operating Cost Calculation

5.2.3 DISPOSAL COST

This is the analysis of what it will cost to dispose the waste water based on a cost of $2/m3 of water produced. Table 21: Cost of Disposal

FORECAST CASE INCREMENTAL WATER PROD.

COST OF DISPOSAL

(m3) (MM$)

Case 1 1021930 2.32

Case2 4202540 8.68

Case 3 3979350 8.24

Case 4 6374650 13.03

Case 5 6599410 12.09

Case 6 9375400 15.09

FORECAST CASE INCREMENTAL OIL PROD. OPERATING COST

(bbl.) MM($)

Case 1 17307249.5 86.5362475

Case2 32958530.7 164.7926535

Case 3 20222287.1 101.1114355

Case 4 33573063.7 167.8653185

Case 5 33632944.5 168.1647225

Case 6 37858818.1 189.2940905

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5.2.4 TOTAL REVENUE This is the total amount generated from the sale of the oil produced, based on an average oil price of $18/bbl. Table 22: Total Revenue generated from Oil sales

FORECAST CASE INCREMENTAL OIL PROD. TOTAL SALES

(bbl.) MM($)

Case 1 17307249.5 400.84

Case2 32958530.7 682.57

Case 3 20222287.1 453.31

Case 4 33573063.7 693.63

Case 5 33632944.5 694.71

Case 6 37858818.1 770.77

5.2.5 NET PROFIT BEFORE TAX The table below shows the net profit (Total sales-Total cost) Table 23: Net Profit before Tax

Forecast Scenario EXTRA COST/INVESTMENT

(DRILLING OR ACIDIZING & FRAC.JOB)

OPERATING COST

COST OF DISPOSAL

TOTAL COST TOTAL SALES NET PROFIT BEFORE

TAX

(MM$) MM($) (MM$) MM($) MM($) MM($)

Case 1 0 86.54 2.32 88.86 400.84 311.98

Case 2 3 164.79 8.68 176.48 682.57 506.09

Case 3 0 101.11 8.24 109.35 453.31 343.96

Case 4 3 167.87 13.03 183.89 693.63 509.73

Case 5 3 168.16 12.09 183.25 694.71 511.45

Case 6 3.325 189.29 15.09 207.70 770.77 563.07

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6.0 CONCLUSION AND RECOMMENDATION

6.1 CONCLUSION

In conclusion, from the above economic analysis carried out, CASE 6 appears to be the most profitable as it returns the highest ‘Net profit before tax’.

6.2 RECOMMENDATION Based on my conclusion, I strongly recommend that the company adopts ‘CASE 6’.