Reservoir Flow Simulation study for a Sector in Main Pay-South Rumaila Oil Field

Summary In reservoir history matching or data assimilation, dynamic data, such as production rates and pressures, are used to constrain reservoir models and to update model parameters. As such, even if under certain conceptualization the model parameters do not vary with time, the estimate of such parameters may change with the available observations and, thus, with time. In reality, the production process may lead to changes in both the flow and geomechanics fields, which are dynamically coupled. For example, the variations in the stress/strain field lead to changes in porosity and permeability of the reservoir and, hence, in the flow field. In weak formations, such as the Lost Hills oil field, fluid extraction may cause a large compaction to the reservoir rock and a significant subsidence at the land surface, resulting in huge economic losses and detrimental environmental consequences. The strong nonlinear coupling between reservoir flow and geomechanics poses a challenge to constructing a reliable model for predicting oil recovery in such reservoirs. On the other hand, the subsidence and other geomechanics observations can provide additional insight into the nature of the reservoir rock and help constrain the reservoir model if used wisely. In this study, the ensemble-Kalman-filter (EnKF) approach is used to estimate reservoir flow and material properties by jointly assimilating dynamic flow and geomechanics observations. The resulting model can be used for managing and optimizing production operations and for mitigating the land subsidence. The use of surface displacement observations improves the match to both production and displacement data. Localization is used to facilitate the assimilation of a large amount of data and to mitigate the effect of spurious correlations resulting from small ensembles. Because the stress, strain, and displacement fields are updated together with the material properties in the EnKF, the issue of consistency at the analysis step of the EnKF is investigated. A 3D problem with reservoir fluid-flow and mechanical parameters close to those of the Lost Hills oil field is used to test the applicability.

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Unstructured Coarse Grid Generation for Reservoir Flow Simulation Using Background Grid Approach

10.2118/120170-ms ◽

2009 ◽

Author(s):

Mohammad Evazi ◽

Hassan Mahani

Keyword(s):

Flow Simulation ◽

Grid Generation ◽

Coarse Grid ◽

Reservoir Flow ◽

Grid Approach ◽

Background Grid

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Integrating kernel support vector machines for efficient rock facies classification in the main pay of Zubair formation in South Rumaila oil field, Iraq

Modeling Earth Systems and Environment ◽

10.1007/s40808-017-0277-0 ◽

2017 ◽

Vol 3 (1) ◽

Cited By ~ 11

Author(s):

Watheq J. Al-Mudhafar

Keyword(s):

Support Vector Machines ◽

Oil Field ◽

Support Vector ◽

Facies Classification ◽

Vector Machines ◽

South Rumaila Oil Field ◽

Kernel Support Vector Machines

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Staggered In Time Coupling of Reservoir Flow Simulation and Geomechanical Deformation: Step 1 - One-Way Coupling

10.2118/51920-ms ◽

1999 ◽

Cited By ~ 6

Author(s):

Susan E. Minkoff ◽

Charles M. Stone ◽

J. Guadalupe Arguello ◽

Steve Bryant ◽

Joe Eaton ◽

...

Keyword(s):

Flow Simulation ◽

Reservoir Flow ◽

Deformation Step ◽

Geomechanical Deformation

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