history matching/prediction - new mexico institute of...
TRANSCRIPT
History Matching/Prediction
History Matching –
Objectives
• Improve and validate the reservoir
simulation model
• Better understanding of reservoir
processes
• Improve the reservoir description and data
acquisition program
• Identify unusual operating conditions
History Matching –
methods
• Manual
– Run simulation for
historical period
– Compare results to
actual field data
– Adjust simulation input
to improve match
– Selection of input data
based on knowledge
and experience
• Automatic
– Minimizes the
objective function; i.e.,
difference between
observed reservoir
performance and
simulation results
– Excludes human
knowledge/experience
factor; thus results
could be in error.
History Matching –
General procedure for history matching
Ertekin, et al.
History Matching –
Selection of production data to specify
• Depends on stage of history match and
type of hydrocarbons
• Data quality issues:
– allocations
– Measurement
– usage
History Matching –
General strategy
for history matching
Ertekin, et al.
History Matching –
Selection of production data to match
• Depends on availability and quality of data
• Pressure match
– Shutin buildup (Static) pressures
• Saturation match
– WOR and/or GOR
– Breakthrough times
– Log-derived fluid saturations
History Matching –
Selection of reservoir data to adjust
• Common parameters to adjust are:
– Aquifer size and strength
– Vertical permeability barriers
– Flow capacity, kHh
– kV/kH ratio
– Pore volume
– Relative permeability
History Matching –
Selection of reservoir data to adjust
• Consequences
Sw
oil
water
0 1
kr
1
Initial Kr curves
Adjusted kr curves
History Prediction
??
History Matching –
Adjusting reservoir data to match production
• To match average reservoir pressure,
adjust:
– Aquifer size
– Pore volume
– Total system compressibility
• Aids: Material balance and aquifer influx
studies
History Matching –
Adjusting reservoir data to match production
• To match pressure gradients, adjust:
– Aquifer connectivity
– Reservoir kHh
– Regional pore volume
– Transmissibilities across faults
• Aids: Coarse gridded 3D models
History Matching –
Adjusting reservoir data to match production
• To match saturation variables, adjust:
– Coning
• kV or vertical permeability barriers
– Lateral water encroachment
• kHh, relative permeability or pore volume
History Matching –
Quality of match
• Relevant to objectives of study– Size additional water handling facilites
Acceptable: level of watercut
and trend are approximately correct
– Future infill well locations
Poor: model underpredicting
watercut performance
Time, years
wate
rcut
actualmatch
History Matching -
Example
Specified
Match
History Matching –
Example (welltest)
Match:
Flowing
Bottomhole
pressure
Hazlett, et al
History Matching-
Example
1
10
100
1000
0 5 10 15 20 25
time, years
pro
du
cti
on
ra
te,
ms
cf/
mo
0
200
400
600
800
1000
1200
SIB
HP
, p
si
simulated
measured
0
50
100
150
200
250
300
1950 1960 1970 1980 1990 2000
time
Pw
simulated
actual
Specified PwfMatch SIBHP and rate
Prediction-
Example
Medford