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Predicting Performance 1
NExT December 2005
Predicting Performance
Predicting Performance 2
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Overview
• Objectives and limitations of future performance predictions
• Types of future performance predictions
• Data requirements for predicting future performance
• Transitioning from history to prediction
• Case studies
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Objectives of Future Performance Predictions
• Predict reservoir behavior
• Estimate performance in new reservoirs
• Optimize operating conditions
• Maximize economic gain
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Limitations of Future Performance Predictions
• The major limitation of future performance predictions is the accuracy of the reservoir model.
• A good history match does not guarantee an accurate and representative performance prediction.
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Limitations of Future Performance Predictions
• This might occur if future performance predictions represent operating scenarios that are dramatically different from the historical operation of the field. Examples include– Converting a depletion drive reservoir to
waterflooding, pressure maintenance or enhanced recovery
– Converting an old, depleted reservoir to gas storage
In some cases, this problem arises because of a dramatic change in the displacement mechanism occurring in the reservoir.
The new displacement process was not part of the original history match and, therefore, may not yield correct results.
In waterflooding studies, for example, predicted water breakthrough times may not match the actual breakthrough times once the waterflood is implemented. In many cases, actual breakthrough occurs much sooner than predicted.
This problem can be fixed only by further history matching that includes the production and pressure performance of the field during the waterflooding, pressure maintenance or enhanced recovery process.
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Types of Future Performance Predictions
• Common uses for future performance predictions– Depletion studies– Secondary or enhanced recovery studies– Timing of facilities installation– Timing of well workovers– Timing of well conversions– Infill drilling studies
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Other Applications of Performance Predictions
• Laboratory studies (corefloods, small-scale core studies, relative permeability studies)
• Parametric studies
• Investigation of vertical flow effects (cross-sectional models)
• Pilot projects
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Data Requirements for Predicting Future Performance
• Number and timing of new wells
• New well data
• Well, production facility and field operating constraints
• Economic limits
• Workover plan for existing wells
• Completion plan for new wells
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Number and Timing of New Wells -Based On
• Availability of drilling rigs
• Time required to drill a well
• Budget considerations
• In some cases, new well locations can be selected automatically by simulator
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New Well Data
• Well location in the simulation grid
• Type of well (producer or injector)
• Well constant, denoted WC, (related to PI of well)
Peaceman has published a series of papers on representation of wells in reservoir simulation. His publications have focused onthe calculation of the well constant, WC, which relates the well flowing bottomhole pressure to the pressure of the grid block.
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New Well Data• Skin factor must also be considered. Incorrect
assumptions about skin factors for new wells could lead to unrealistic forecasts.
• Skin factor for new wells can be estimated using(1) knowledge of skin factors resulting from
drilling and completion practices in the field of interest, or
(2) measured skin factors in existing wells (possibly before and after cleanup or stimulation treatments).
• Another possibility is to perform a sensitivity analysis using a range of expected skin factors.
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Well (Existing and New) and Facilities Constraint Data
• Minimum and maximum operating pressures at– Compression facilities– Separators– Liquid processing facilities
• Maximum fluid cuts (GOR, WOR) and liquid rates, which may limit– Lifting facilities at wells– Gathering and processing facilities
• All constraints can apply to wells, production facilities and/or the entire field operation.
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Economic Limits
• Economic limits determine the operating life of a project or well in a future performance prediction.
• Economic limits are often minimum production rates for oil and gas, for individual wells or the entire field.
• Producing gas-oil ratios and water-oil ratios can also be used.
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Economic Limits• Data requirements for determining economic limits
– Estimate of future pricing for oil and gas– Fixed operating costs– Monthly operating costs for wells– Lifting costs– Routine maintenance costs– Workover/repair costs for wells– Taxes and regulatory factors– Operating cost and oil and gas price escalations
Data requirements are usually translated into a fixed cost per well per unit time. The per well cost can then be converted to a minimum economic oil or gas production rate.
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Economic Limits
• Alternative approach - allow an economics model to determine when a project is uneconomic.– Use overall production stream for entire
project.– Input fixed and per well operating cost into
economics model.• Limit use of economic limits in reservoir
simulation.
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Workover/Completion Plan For Wells
• Develop a plan for workovers of existing wells– Skin damage removal– Hydraulic fracturing– Mechanical repairs
• Develop a plan for completion of new wells– Stimulation– Mechanical configuration
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Transitioning From History to Predictions
• Transitioning from history matching to performance predictions means wells are no longer controlled by known operating conditions, but rather by an estimated future operating scenario.
• Unless there is an immediate change in the operating conditions of a field after history matching, the well and field production rates and fluid cuts (overall production performance) should be similar to recent past history.
The first performance prediction is usually a base case. The base case might also be called a "do nothing" case, since well and field operations are not changed for this forecast.
Other, more sophisticated performance predictions usually involve operational changes that take place some time in the future. Rarely do operational changes take place immediately after the end of history matching. This might be due to the time required to
• Drill new wells,
• Install new production and/or injection facilities,
• Upgrade existing production and/or injection facilities.
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Smooth Transitions From History to Predictions
• The quality or smoothness of the transition is dependent on the quality of the history match.
• If a smooth transition is not seen, then it might be necessary to further refine the history match.
• Also a function of how future operating conditions are specified.
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• Methods for a smooth transition from history matching to future performance:– If wells were rate constrained at the end of
history, then begin forecasting using the same rate constraints on wells.
– If the wells were producing at capacity (pressure constrained) at the end of history, then the wells should be pressure constrained at the start of performance predictions.
– As an alternative, use the average well rate or pressure from the last several days, weeks or months for future predictions.
Choosing a method for a smooth transition from history matching to future performance will also depend on whether the field is currently constrained by allowables or is operating at capacity.
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Summary of Production Constraints ForForecast Cases
Parameter Value
Minimum well flowing bottomholepressure (FBHP)
300 psia
Minimum well oil rate 50 STB/D
Maximum completion water-oil ratio(WOR)
6 STB/STB
Minimum field oil production rate 500 STB/D
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47
46
45
483
12900
44
Block V
Block VI7
1
2
109
8
3
4
5
6
OW
C
OW
C
OW
C
existing production wells
true fault traces
fault traces in simulation model
proposed production wells
wells with proposed re-completions
proposed water injection wells
Legend
Well Locations for Case Fore2a-New Wells and Recompletions
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FORE Field Prod Rates
1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 20100
10
20
30
40
50
60
0
50
100
150
200
250
300
Obs QoObs QwObs Qghist33k:Field OIL Production Rate hist33k:Field W AT Production Rate hist33k:Field GAS Production Rate fore2a:Field OIL Production Rate fore2a:Field W AT Production Rate fore2a:Field GAS Production Rate fore1b:Field OIL Production Rate fore1b:Field W AT Production Rate fore1b:Field GAS Production Rate
Time, years
Qo
, Q
w (
MS
TB
/D)
Qg
(M
MC
F/D
)
Field Production Rates for Base (Fore1b) and New Wells and Recompletion (Fore2a) Forecast Cases
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New Wells and Recompletions Increase Recoveries
0
50
100
150
200
250
300
1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010
Time, years
Cu
m O
il, C
um
Wat
er (
MM
ST
B)
Obs Cum OilObs Cum WaterObs Cum Gas
Hist33k:Field Oil CumHist33k:Field WaterHist33k:Field GasFore2a:Field Oil CumFore2a:Field WaterFore2a:Field GasFore1b:Field Oil CumFore1b:Field WaterFore1b:Field Gas Cum
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New Wells and Recompletions Lower Reservoir Pressure
0
1000
2000
3000
4000
5000
6000
1990 1995 2000 2005 2010Time, years
Pre
ssur
e, p
sia
Obs C3C4 MidPerf SIObs C4 MidPerf SIObs C5 MidPerf SIObs C3C4 NoPerf Datum SIObs C4 NoPerf Datum SIObs C5 NoPerf Datum SIhist33k: Field Average Pressurefora2a: Field Average Presssurefore1b: Field Average Pressure
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Water Saturation Maps (0.2 - 1.0 Scale) for Case Hist33k, Fore1b and Fore2a for Layer 1
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Movable Oil Maps for Cases HIST33k, FORE1b and FORE2a for Layer 1
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Summary of Forecast Simulation Cases
CaseName
UltimateOil
Production(MMSTB)
UltimateWater
Production(MMSTB)
UltimateGas
Production(Bscf)
UltimateOil
Recovery(% of OOIP)
Base (Fore1b) 216 129 179 34.3
250 167 227 39.7New Wells and
Recompletions (Fore2a)
Summary of Forecast Simulation Cases
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Conclusions
• There are several fault blocks in the VLE-196 field with significant volumes of bypassed oil.
• Oil recovery can be increased by 34 million STB (5.4% of the OOIP) by recompleting 5 existing wells and drilling 8 new wells
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Recommendations
• Develop and calibrate an expanded model of the VLE-196 C-4/C-5 reservoirs, to better model communication with other reservoirs.
• This should include the B/C-2/C-3 reservoirs, areas across the VLE-400 fault to the west and block VI to the north.