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Evaluation des ressources, incertitudes et risques : du stockage vers la géothermie Jeudi 16 mars 2017 Thomas SCHAAF, Ing. réservoir, STORENGY, groupe ENGIE [email protected]
Evaluation des ressources, incertitudes
et risques :
du stockage vers la géothermie
Jeudi 16 mars 2017
Thomas SCHAAF, Ing. réservoir, STORENGY, groupe ENGIE
Common framework : geological reservoir characterization
Common goal : reliable performance forecasts
Common bias and pitfalls
Cross-discipline application cases:
— Pre-development screening through a Petrel/Prosper workflow : Paris area
— Data assimilation through a Petrel RE worklow : Bordeaux area
Wrap up and perspectives:
— Structural/Petrophysical/Dynamic uncertainties assessment
Outline
15/03/2017 Pôle Avenia – Club Géosciences – Journée « Transferts de technologie entre les filières du sous-sol » 2
Reservoir characterization : Obtain representative model(s!) of a
geological object in an uncertain framework
Our concern: subsurface uncertainties (up to economics possibly)
Common framework– Reservoir Characterization
15/03/2017 Pôle Avenia – Club Géosciences – Journée « Transferts de technologie entre les filières du sous-sol » 3
Data from:
-Geophysics,
-Geology,
-Reservoir.
Modelling:
-Structural,
-Facies,
-Petrophysical,
-Dynamic Simulation.
Geothermal doublet case
Well spacing
Proper uncertainties quantification assessment and risk analysis
Reliable production forecasts :
Common goal – Reliable production forecasts
15/03/2017 Pôle Avenia – Club Géosciences – Journée « Transferts de technologie entre les filières du sous-sol » 4
E&P application case
Cumulative oil production
Gas storage case
Mean pressure
Uncertainties quantification to properly manage them and …
… to make good decision in an uncertain framework
whatever the numerical modeling steps are : whatever geomodeling
tool, fluid flow simulator, etc.
Workflows for subsurface uncertainty quantification
15/03/2017 Pôle Avenia – Club Géosciences – Journée « Transferts de technologie entre les filières du sous-sol » 5
Uncertain (stochastic?)
Input
Parameters
Numerical
Modeling
Steps
Distributions
Of key OutputsDecision
Making
Data
Assimilation
(live process)
CPU intensive, non linear
ill-posed
problem
Objective
Function
Overconfidence
Optimism
Anchoring
Deterministic cases versus fully probabilistic approach
Exploit the full potential of geostatistics (static versus dynamic
outputs)
Common bias and pitfalls
15/03/2017 Pôle Avenia – Club Géosciences – Journée « Transferts de technologie entre les filières du sous-sol » 6
McVay - JPT 2015 Paper
Common framework : geological reservoir characterization
Common goal : reliable performance forecasts
Common bias and pitfalls
Cross-discipline application cases:
— Pre-development screening through a Petrel/Prosper workflow : Paris area
— Data assimilation through a Petrel RE worklow : Bordeaux area
Wrap up and perspectives:
— Structural/Petrophysical/Dynamic uncertainties assessment
Outline
15/03/2017 Pôle Avenia – Club Géosciences – Journée « Transferts de technologie entre les filières du sous-sol » 7
Context - Low enthalpy geothermal projects in the Paris basin
Target: Paris Basin – Dogger formation
Uncertainty quantification and risk assessment of flow rates and well spacing for investment decision making
15/03/2017 Pôle Avenia – Club Géosciences – Journée « Transferts de technologie entre les filières du sous-sol »
Set well architecture
A Dogger generic well architecture is assumed:
—Kick off point @ 420 m/ground
—40° slanted well
—9’’5/8 tubing size
—Open-hole at reservoir face
15/03/2017 Pôle Avenia – Club Géosciences – Journée « Transferts de technologie entre les filières du sous-sol »
Workflow to derive the statistics of key properties
Based on a STORENGY well database
Example: reservoir net pay property
Zoom in
Reservoir net pay data
15/03/2017 Pôle Avenia – Club Géosciences – Journée « Transferts de technologie entre les filières du sous-sol »
Workflow to derive the statistics of key properties
Uncertain parameters: seed (integer value) and Lc [750,1500]m
Extraction & statistics over the zone of interest
Workflow repeated for NTG, , k, pressure and temperature
200 samplesKey inputs for the
dynamic modeling
Pôle Avenia – Club Géosciences – Journée « Transferts de technologie entre les filières du sous-sol »15/03/2017
Dynamic modelling of the reservoir-well system
Material Balance approach
Nodal analysis - operating point based on the crossing point of 2
curves:
—The inflow performance curve (--- curve): « Productivity »
—The vertical lift performance curve (--- curve): « Well architecture;
fluids lifted »
Well flow rate (m3/h)
Bottom hole
Pressure (bar)
15/03/2017 Pôle Avenia – Club Géosciences – Journée « Transferts de technologie entre les filières du sous-sol »
Modelling a down hole pump
A pump giving X bar of pressure support = initial reservoir pressure
boosted of X bar generate a set of curves with an interval of extra
pressures:
Well flow rate (m3/h)
Example:
(o) Artesian flow of 100 m3/h
o
(o) Achieving 250 m3/h would require
7 bar of extra pressure
o
This value could be directly
translated into a variation of the
liquid level in the annular space
« Drawdown » value
Bottom hole
Pressure (bar)
15/03/2017 Pôle Avenia – Club Géosciences – Journée « Transferts de technologie entre les filières du sous-sol »
NTG
T
Sampling
Risk analysis: distributions of drawdowns
Given the statistics/distributions of key properties (NTG, , k,P,T):
—Sample 50 alternative reservoir/well systems from those
distributions
—Apply the nodal analysis to those 50 samples
—Increase by 10 bar the drawdown values obtained (/pump cavitation)
Nodal analysis Results analysis
15/03/2017 Pôle Avenia – Club Géosciences – Journée « Transferts de technologie entre les filières du sous-sol »
Common framework : geological reservoir characterization
Common goal : reliable performance forecasts
Common bias and pitfalls
Cross-discipline application cases:
— Pre-development screening through a Petrel/Prosper workflow : Paris area
— Data assimilation through a Petrel RE worklow : Bordeaux area
Wrap up and perspectives:
— Structural/Petrophysical/Dynamic uncertainties assessment
Outline
15/03/2017 Pôle Avenia – Club Géosciences – Journée « Transferts de technologie entre les filières du sous-sol » 15
Long term production test - data integration
▪ Production test on Benauge well in 1981
▪ Pressures registered on Lormont & Meriadec wells
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3 bar
Faults
15/03/2017 Pôle Avenia – Club Géosciences – Journée « Transferts de technologie entre les filières du sous-sol »
Long term production test
▪ Numerical modeling:
▪ Geomodeling (inc. Geostatistics) + 3D fluid flow simulation
▪ 4 zones : East/West fault; carbonate+sandstone reservoirs
▪ 4 parameters : poro/perm + T_fault_Bordeaux + Pini
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West East
Cénomanien carb.Cénomanien sands
Bordeaux Fault
Simulation results
15/03/2017 Pôle Avenia – Club Géosciences – Journée « Transferts de technologie entre les filières du sous-sol »
Experimental Design = 57 runs3 best out of 57 runs
Able to pick up the runs having the best simulation results with respect to the observations
Long term production test - workflow
▪ Sensitivity study : petro + fault transmissivity + P_ini
▪ PetrelRE workflow + process "Uncertainty & Optimization" :
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U&O process – workflow editor Variables definition + intervals
15/03/2017 Pôle Avenia – Club Géosciences – Journée « Transferts de technologie entre les filières du sous-sol »
Common framework, goal and bias
Workflows developed for E&P and gas storage applications could be
used straight ahead or with minor modification (e.g. simulator)
Tackling Structural/Petrophysical/Dynamic uncertainties through a
single project:
With a Cougar / Petrel RE / AD-GPRS workflow
Wrap up and perspectives
15/03/2017 Pôle Avenia – Club Géosciences – Journée « Transferts de technologie entre les filières du sous-sol » 19
AD-GPRS simulatorCougar : sensitivity study, risk analysis, …
PetrelRE workflows
Evaluation des ressources, incertitudes
et risques :
du stockage vers la géothermie
Jeudi 16 mars 2017
Thomas SCHAAF, Ing. réservoir, STORENGY, groupe ENGIE
