Devex’09 13 May 2009 1 Correlations in well rate fluctuations and coupled geomechanical modelling used to identify reservoir communication paths John Greenhough, Ian Main, Stuart Simmons The University of Edinburgh Kes Heffer, Reservoir Dynamics Ltd Xing Zhang, Assef Mohamad Hussein, Gaisoni Nasreldin, Nick Koutsabeloulis, Schlumberger Reservoir GeoMechanics Center of Excellence
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Devex’09 13 May 2009 1
Correlations in well rate fluctuations and coupled geomechanical modelling used to identify reservoir communication paths
John Greenhough, Ian Main, Stuart Simmons The University of Edinburgh
Kes Heffer, Reservoir Dynamics Ltd
Xing Zhang, Assef Mohamad Hussein, Gaisoni Nasreldin, Nick Koutsabeloulis, Schlumberger Reservoir GeoMechanics Center of Excellence
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Talk outline
• The Statistical Reservoir Model– Shortterm forecasting
• Rate correlations – General characteristics– Conceptual mechanisms
• Rate diffusivities• Valhall results (cf. microseismic records)• Aggregated results from 6 North Sea fields• Integration into reservoir management• Messages
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Flow rate fluctuations
Producers
Injectors
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Statistical Reservoir Model
• Finds best small group of wells to model flow rate of any well of interest
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Example of correlated wells
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History Match Well 15 (R2!"#$%&'!()*
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Statistics of fits & forecasts
Total production errors ~2 x size if only use previous month as fit
211416117Error ! on total production [%]
2224173317Mean error ! over all producers [%]
0.970.950.960.900.92Mean R2 over all producers
4/26(15%)
9/82(11%)
8/72(11%)
13/59(22%)
12/159(8%)
Mean predictors per producer (out of total predictors with 10+ months data)
16/1770/8137/4834/3673/118Producers output (out of those with 10+ months data)
Field 5Field 4Field 3Field 2Field 1
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Shortterm rate prediction
Blind test of prediction with SRM of 3 months of Gullfaks production (refereed by Rock Deformation Research, University of Leeds)“The actual production figures for most (>70%) of the wellbores lie
within the 95% confidence limits given by Edinburgh.”
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broadband fluctuationshigh frequency fluctuations__ zero correlation
Shmax
First principal component of matrix of rate correlations between all wells in field B – independent mode ‘explaining’ largest proportion of fluctuation variance
General characteristics of rate correlations (Spearman rank)
Longrange
Faultrelated
Stressrelated
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Basic concept
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Concept of longrange transmission of strain by shear
dilatation
compression
More complexdiscontinuousshear
SH
local cause
of rate changes
transmission
Conductivity determined by normal stress during shear vsrock strength, ductility, damage zone, displacement etc
LongrangeStressrelated
Faultrelated
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Extraction of rate diffusivities from timebehaviour of rate correlations
Looking to extract tensors related to diffusive rate behaviour:
–Local (shorterrange)
–Nonoscillatory in time
–Fitted with nonnegative diffusivities
– (Decaying in time)
Likely to be related to permeability tensors.
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Valhall fielddiffusivity major axes & lag0 PC1on fault traces
diffusivity major axes on induced inelastic shear strains (VISAGETM)
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Valhall field: Microseismic emissions vs rate diffusivity trends
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Valhall: Microseismic events and interpreted diffusivity axes from rate correlations
Fast shear waves = fracture strikesTeanby et al. (GJI 2004)
Zoback & Zincke(PAGeophys, 2002) Focal mechanism: normal slip
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Valhall: Microseismicity and modelled strain due to depletion
(VISAGE coupled model)
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Valhall: Diffusivity axes and casing collapse/deformation
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Neotectonic setting of North SeaMaximum horizontal stress axes(World Stress Map Heidbach et al (2008))
Earthquake epicentres (US Geological Survey/National Earthquake Information Center (PDE) 1973 Present)
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Aggregated North Sea fields Longrange correlations (zero lag time)(detrended rate data)
From Statistical Reservoir Model:
Mean exponent of ratio correlated/available wellpairs vs distance = 0.14
Exponent ~ 0.07
Average exponent of mean correlated distance vs time ~ 0.1
Orientational distribution of major diffusivity axes (aggregated fields)
Shmax
North Viking graben South Viking / Witch Ground grabens
Central graben
N SStrikeslip/thrust stress state
Highly anisotropic horizontal stresses
Normal stress state
~Isotropic horizontal stress
Azimuthally smoothed Slip tendency of faults
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Orientational frequency distributions for 2 types of analysis of production histories both indicate the involvement of shear slip – even in ‘unfractured’ fields
______
most favoured breakthrough directions for injected fluid in 47 ‘unfractured’fields worldwide
________
major diffusivity axes for 4 ‘unfractured’fields in North Sea
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Integration into reservoir management work process
Infill well numbers & configuration; pressure management; improved vertical & areal sweep efficiencies; water production reduction; EOR schemes…
Choke settings
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Messages
• Geomechanical effects appear to be influencing fluid behaviour in reservoirs worldwide (these effects appear to be commercially significant)
• Rate fluctuation analysis and geomechanical modelling can assist understand those effects and provide commercially useful information >>>
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Potential application of rate correlation analysis
1. Indicator of reservoir communications, complementary to geological model,microseismicity, seismic anisotropy, 4D seismic, well test permeabilities (mutual validation & calibration).
2. Timelapse changes in communications .3. Calibration of geomechanical understanding
NERC CONNECT grant GR3/C0022 with matching funding from BP
COFFERS project, under the Industry Technology Facilitator (sponsors: Amerada Hess, BG Group, BP, ConocoPhillips, DTI, KerrMcGee, StatoilHydro, Shell and Total)
RESURGE project, sponsored by theTechnology Strategy BoardFIELD DATA provided by BP, Nexen, StatoilHydro