A multi-scale approach to integrate dynamic data in reservoir models

Sanjay Srinivasan, Alvaro Barrera

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 to flow performance of the reservoir. This paper presents a novel approach for integrating dynamic data in reservoir models that utilizes the probability perturbation approach for the simultaneous calibration of geological models at field scale and multiphase flow functions associated with porelevel spatial representations of the porous media. In this probabilistic approach, a stochastic simulator is used to model the spatial distribution of a discrete number of rock types identified by rock/connectivity indexes (CIs). Each CI corresponds to a particular pore network structure with a characteristic connectivity. Primary drainage and imbibition displacements are modeled on the 3D pore networks to generate multiphase flow functions, including effective permeability and porosity of the rock, the relative permeabilities and capillary pressure, linked to the CIs. During the 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 results in the update of all the flow functions. The results from the integrated history matching procedure are presented for a synthetic field example first. The convergence rate of the proposed method is comparable to other current techniques with the distinction of enabling consistent updates to all the flow functions while at the same time honoring the geological/ sedimentary model for the distribution of petrophysical properties. Consequently, the reservoir model and its predictions are consistent with realistic geological processes. The paper concludes with results for a realistic field example.

Original languageEnglish (US)
Title of host publicationIAMG 2009 - Computational Methods for the Earth, Energy and Environmental Sciences
PublisherStanford, School of Earth Sciences
ISBN (Print)9780615334493
StatePublished - Jan 1 2009
EventInternational Congress for Mathematical Geology: Computational Methods for the Earth, Energy and Environmental Sciences, IAMG 2009 - Stanford, CA, United States
Duration: Aug 23 2009Aug 28 2009

Publication series

NameIAMG 2009 - Computational Methods for the Earth, Energy and Environmental Sciences

Other

OtherInternational Congress for Mathematical Geology: Computational Methods for the Earth, Energy and Environmental Sciences, IAMG 2009
CountryUnited States
CityStanford, CA
Period8/23/098/28/09

Fingerprint

connectivity
Connectivity
Integrate
History Matching
Multiphase Flow
Multiphase flow
multiphase flow
Rocks
Spatial Distribution
Permeability
Spatial distribution
simulator
Simulator
Simulators
Update
perturbation
Model
rock
permeability
spatial distribution

All Science Journal Classification (ASJC) codes

  • Geology
  • Computational Mathematics

Cite this

Srinivasan, S., & Barrera, A. (2009). A multi-scale approach to integrate dynamic data in reservoir models. In IAMG 2009 - Computational Methods for the Earth, Energy and Environmental Sciences (IAMG 2009 - Computational Methods for the Earth, Energy and Environmental Sciences). Stanford, School of Earth Sciences.
Srinivasan, Sanjay ; Barrera, Alvaro. / A multi-scale approach to integrate dynamic data in reservoir models. IAMG 2009 - Computational Methods for the Earth, Energy and Environmental Sciences. Stanford, School of Earth Sciences, 2009. (IAMG 2009 - Computational Methods for the Earth, Energy and Environmental Sciences).
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Srinivasan, S & Barrera, A 2009, A multi-scale approach to integrate dynamic data in reservoir models. in IAMG 2009 - Computational Methods for the Earth, Energy and Environmental Sciences. IAMG 2009 - Computational Methods for the Earth, Energy and Environmental Sciences, Stanford, School of Earth Sciences, International Congress for Mathematical Geology: Computational Methods for the Earth, Energy and Environmental Sciences, IAMG 2009, Stanford, CA, United States, 8/23/09.

A multi-scale approach to integrate dynamic data in reservoir models. / Srinivasan, Sanjay; Barrera, Alvaro.

IAMG 2009 - Computational Methods for the Earth, Energy and Environmental Sciences. Stanford, School of Earth Sciences, 2009. (IAMG 2009 - Computational Methods for the Earth, Energy and Environmental Sciences).

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

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Srinivasan S, Barrera A. A multi-scale approach to integrate dynamic data in reservoir models. In IAMG 2009 - Computational Methods for the Earth, Energy and Environmental Sciences. Stanford, School of Earth Sciences. 2009. (IAMG 2009 - Computational Methods for the Earth, Energy and Environmental Sciences).