History match by simultaneous calibration of flow functions

A. Barrera, Sanjay Srinivasan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Reliable predictions of reservoir flow response require a realistic geological model of heterogeneity and an understanding of its relationship with the flow properties. This paper presents a novel approach for the integration of dynamic data into reservoir models that combines stochastic techniques for the simultaneous calibration of geological models and multiphase flow functions associated with pore-level spatial representations of porous media. In this probabilistic approach, a stochastic simulator is used to model the spatial distribution of rock types identified by rock/connectivity indexes (CIs). Each CI corresponds to a particular pore network structure with a characteristic connectivity. Displacements are modeled on the pore networks to generate multiphase flow functions linked to the CIs. During assisted history matching, the stochastic simulator perturbs the spatial distribution of the CIs to match the simulated pressures and flow rates to historic data. Perturbation of the CIs in turn result in the update of all the flow functions. Comparison is made with the history-matched model obtained only by perturbing permeability and it is argued that reliable predictions of future production can only be made when the entire suite of flow functions is consistent with the real reservoir.

Original languageEnglish (US)
Title of host publicationPetroleum Geostatistics 2007
StatePublished - 2007
EventPetroleum Geostatistics 2007 - Cascais, Portugal
Duration: Sep 10 2007Sep 14 2007

Other

OtherPetroleum Geostatistics 2007
CountryPortugal
CityCascais
Period9/10/079/14/07

Fingerprint

connectivity
Connectivity
Calibration
histories
calibration
history
multiphase flow
Multiphase flow
porosity
Multiphase Flow
Spatial distribution
simulators
spatial distribution
Spatial Distribution
Simulators
Rocks
simulator
rocks
Simulator
History Matching

All Science Journal Classification (ASJC) codes

  • Statistics, Probability and Uncertainty
  • Geology
  • Geophysics
  • Geotechnical Engineering and Engineering Geology

Cite this

Barrera, A., & Srinivasan, S. (2007). History match by simultaneous calibration of flow functions. In Petroleum Geostatistics 2007
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title = "History match by simultaneous calibration of flow functions",
abstract = "Reliable predictions of reservoir flow response require a realistic geological model of heterogeneity and an understanding of its relationship with the flow properties. This paper presents a novel approach for the integration of dynamic data into reservoir models that combines stochastic techniques for the simultaneous calibration of geological models and multiphase flow functions associated with pore-level spatial representations of porous media. In this probabilistic approach, a stochastic simulator is used to model the spatial distribution of rock types identified by rock/connectivity indexes (CIs). Each CI corresponds to a particular pore network structure with a characteristic connectivity. Displacements are modeled on the pore networks to generate multiphase flow functions linked to the CIs. During assisted history matching, the stochastic simulator perturbs the spatial distribution of the CIs to match the simulated pressures and flow rates to historic data. Perturbation of the CIs in turn result in the update of all the flow functions. Comparison is made with the history-matched model obtained only by perturbing permeability and it is argued that reliable predictions of future production can only be made when the entire suite of flow functions is consistent with the real reservoir.",
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Barrera, A & Srinivasan, S 2007, History match by simultaneous calibration of flow functions. in Petroleum Geostatistics 2007. Petroleum Geostatistics 2007, Cascais, Portugal, 9/10/07.

History match by simultaneous calibration of flow functions. / Barrera, A.; Srinivasan, Sanjay.

Petroleum Geostatistics 2007. 2007.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AU - Barrera, A.

AU - Srinivasan, Sanjay

PY - 2007

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N2 - Reliable predictions of reservoir flow response require a realistic geological model of heterogeneity and an understanding of its relationship with the flow properties. This paper presents a novel approach for the integration of dynamic data into reservoir models that combines stochastic techniques for the simultaneous calibration of geological models and multiphase flow functions associated with pore-level spatial representations of porous media. In this probabilistic approach, a stochastic simulator is used to model the spatial distribution of rock types identified by rock/connectivity indexes (CIs). Each CI corresponds to a particular pore network structure with a characteristic connectivity. Displacements are modeled on the pore networks to generate multiphase flow functions linked to the CIs. During assisted history matching, the stochastic simulator perturbs the spatial distribution of the CIs to match the simulated pressures and flow rates to historic data. Perturbation of the CIs in turn result in the update of all the flow functions. Comparison is made with the history-matched model obtained only by perturbing permeability and it is argued that reliable predictions of future production can only be made when the entire suite of flow functions is consistent with the real reservoir.

AB - Reliable predictions of reservoir flow response require a realistic geological model of heterogeneity and an understanding of its relationship with the flow properties. This paper presents a novel approach for the integration of dynamic data into reservoir models that combines stochastic techniques for the simultaneous calibration of geological models and multiphase flow functions associated with pore-level spatial representations of porous media. In this probabilistic approach, a stochastic simulator is used to model the spatial distribution of rock types identified by rock/connectivity indexes (CIs). Each CI corresponds to a particular pore network structure with a characteristic connectivity. Displacements are modeled on the pore networks to generate multiphase flow functions linked to the CIs. During assisted history matching, the stochastic simulator perturbs the spatial distribution of the CIs to match the simulated pressures and flow rates to historic data. Perturbation of the CIs in turn result in the update of all the flow functions. Comparison is made with the history-matched model obtained only by perturbing permeability and it is argued that reliable predictions of future production can only be made when the entire suite of flow functions is consistent with the real reservoir.

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Barrera A, Srinivasan S. History match by simultaneous calibration of flow functions. In Petroleum Geostatistics 2007. 2007