Effective properties for flow calculations

King, Micháel J.; King, Peter R.; McGill, C. A.; Williams, John K.

doi:10.1007/bf00616929

Cited by 23 publications

(2 citation statements)

References 11 publications

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“…In particular, the voxel-gridblock relation is exploited for the determination of non-neighbor connections and inter-grid block transmissibility. Transmissibility is calculated by using the rock properties corresponding to voxels located in the halfblock volumes at either side of a grid block interface [6,7]. This calculation can be done using either analytical methods (combinations of arithmetic and harmonic averaging) or by application of a pressure solver.…”

Section: Upscaling and Simulation Modelmentioning

confidence: 99%

Dynamic Simulation of a Realistic 3-D Model of the Brent Slumps

et al. 2000

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TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractThe Brent Slumps of the Brent Field were formed by crestal collapse of the main Brent reservoir during the late Jurassic. Production from the Brent Slumps has been dominated by two main factors: varying levels of connectivity with the West Flank of the field through cross-fault juxtaposition and preferential production via prolific high-permeability zones. Remaining Brent Slumps undeveloped reserves represent a significant fraction of the field total.In order to improve the understanding of historical production performance and to address the remaining hydrocarbon volumes in place, a new realistically faulted 3-D simulation model has been constructed for the Slumps. The model contains over 140 listric and antithetic faults and utilises Shell's proprietary reservoir simulator (MoReS).The model basis is a very fine cellular 3-D static model that contains a detailed description of both reservoir structure and facies-controlled permeability architecture. Simulation models are extracted at various scales, ranging from coarse (quick look at material balance and pressures), to very fine (investigation of flushing patterns), using upgridding and upscaling algorithms that guarantee consistency of volumetrics, connectivity and well data.The simulation model is defined in terms of geological entities, i.e., individual faults, fault blocks, horizons and zones. This enables a high-level and systematic treatment of fault transmissibility and allows for monitoring of, e.g., material balance/pressures per fault block and flow across individual fault surfaces. This greatly facilitates sharing of simulation results within the multi-disciplinary development team.The integrated static/dynamic model is now used to help identify and rank the portfolio of remaining development targets, in addition to underpinning the planning of complex, multi-target horizontal wells. Many infill targets are relatively small and lie close to the economic threshold. The improved technical integrity provided by the new model has been critical in providing sufficient confidence to support an infill drilling programme.After outlining the particular development challenges for the Brent Slumps, the paper sketches the static model (seismic, analogues, structure, rock properties), explains the philosophy behind the integrated static/dynamic model and illustrates its utilisation (and successes) with a number of examples.

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Section: Upscaling and Simulation Modelmentioning

confidence: 99%

Dynamic Simulation of a Realistic 3-D Model of the Brent Slumps

et al. 2000

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“…A result of this proliferation has been a change in workhg practice, where the same asset-based teams 133 which build the geologic models now upscale them and use them for well planning and reservoir simulation purposes. This has highlighted limitations within the standard approach to upscaling [1,2] and has accelerated the development of new upscaling methodologies [3,4].…”

Section: Introductionmentioning

confidence: 99%

Application of Novel Upscaling Approaches to the Magnus and Andrew Reservoirs

King¹,

MacDonald²,

Todd³

et al. 1998

Proceedings of European Petroleum Conference

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TX 75083-3836, U. S. A., fax 01-972-952-9435. AbstractCases studies from three North Sea turbidite reservoirs will be presented, which together demonstrate our current understanding of permeability and relative permeability upscaling. The three formations, the Magnus, Magnus Sand Member (MSM), the Magnus, Lower Kimmeridge Clay Formation (LKCF), and the Andrew reservoir each provide distinct challenges for reservoir modelling, either because of reservoir complexity, the fluids in place, or the phase of field life. To meet these challenges, several novel upscaling approaches have been developed. Their use will be explored and current best practice delineated. This best practice differs significantly from previous definitions of "effective permeability" by placing more emphasis on extracting multiple properties from the fine scale geologic models. Distinct upscaling calculations are required to assess (i) the quality of sands, (ii) the quality of barriers, and (iii) the tortuosity of flow around these barriers. Similarly, when constructing upscaled relative permeabilities, the "e~ective" curves are distinguished from the "pseudo" curves. The former describe the physical displacement of fluids, while the latter include the additional numerical dispersion corrections required when implementing the relative permeability functions within a coarsely gridded full field simulator. Effective PermeabilityWhat is effective permeability? A cynic could describe it in terms of putting incorrect information into the wrong model. to get the r&& answer. The "wrong model" is that carried in a typical full field simulator: homogeneous blocks of numerical rock that extend for perhaps a hundred metres or m-ore laterally, and which may be ten's of metres thick. The "incorrect information" is the effective property. But, what the cynic would emphasise is that we can only define this property based on our expectation of the "right answer".Consider the simplified sketch of a simple sand/shale reservoir zone, in Figure 1a, and focus your attention onto the "coarse cell" in the centre of the figure. What is the vertical permeability of the cell? With the standard flow based computation of effective permeability [1], the upscaling region is treated as if it were a laboratory coreflood, Figure 1b. The sides of the system are sealed, a pressure drop is exerted vertically, and the pressures and flux are determined numerically.The volumetric flux defines the effective permeability, according to Darcy's Law.

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The Mathematics of Fluid Flow Through Porous Media

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Effective properties for flow calculations

Cited by 23 publications

References 11 publications

Dynamic Simulation of a Realistic 3-D Model of the Brent Slumps

Dynamic Simulation of a Realistic 3-D Model of the Brent Slumps

Application of Novel Upscaling Approaches to the Magnus and Andrew Reservoirs

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