Reservoir Modeling Using Multiple-Point Statistics

Strebelle, Sebastien; Journel, André G.

doi:10.2523/71324-ms

Cited by 35 publications

(32 citation statements)

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“…However, often the marginal distributions of the different categories in the TI are not equal to those of the real sample, which needs to be simulated; that is, the percentages of occurrence of the different categories diverge between the TI and the desired simulation. Strebelle and Journel [32] implemented a method to adapt this discrepancy of the marginal category distribution. However, if the marginal probability of the TI and the desired marginal probability are not close enough to each other, the algorithm would not reproduce the desired proportions of each category present in the simulated images.…”

Section: Snesim Algorithmmentioning

confidence: 99%

“…Four general scale orders can be recognized, which are pore to lithofacies, lithofacies to geomodel, and geomodel to reservoir model. Multiplepoint geostatistics (MPS) gained importance in the recent years for modelling geological structures at different spatial scales, from m to m [32,33]. For example, in the field of hydrology, MPS allows building models on decameter scale [34], while Okabe and Blunt [35] used the technique to model pore space on a micrometer scale.…”

Section: Introductionmentioning

confidence: 99%

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Lattice Boltzmann Simulations of Fluid Flow in Continental Carbonate Reservoir Rocks and in Upscaled Rock Models Generated with Multiple-Point Geostatistics

Soete

Claes

et al. 2017

Geofluids

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Microcomputed tomography ( CT) and Lattice Boltzmann Method (LBM) simulations were applied to continental carbonates to quantify fluid flow. Fluid flow characteristics in these complex carbonates with multiscale pore networks are unique and the applied method allows studying their heterogeneity and anisotropy. 3D pore network models were introduced to single-phase flow simulations in Palabos, a software tool for particle-based modelling of classic computational fluid dynamics. In addition, permeability simulations were also performed on rock models generated with multiple-point geostatistics (MPS). This allowed assessing the applicability of MPS in upscaling high-resolution porosity patterns into large rock models that exceed the volume limitations of the CT. Porosity and tortuosity control fluid flow in these porous media. Micro-and mesopores influence flow properties at larger scales in continental carbonates. Upscaling with MPS is therefore necessary to overcome volume-resolution problems of CT scanning equipment. The presented LBM-MPS workflow is applicable to other lithologies, comprising different pore types, shapes, and pore networks altogether. The lack of straightforward porosity-permeability relationships in complex carbonates highlights the necessity for a 3D approach. 3D fluid flow studies provide the best understanding of flow through porous media, which is of crucial importance in reservoir modelling.

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Section: Snesim Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Lattice Boltzmann Simulations of Fluid Flow in Continental Carbonate Reservoir Rocks and in Upscaled Rock Models Generated with Multiple-Point Geostatistics

Soete

Claes

et al. 2017

Geofluids

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“…For one of the representative stationary reservoirs, most stochastic modelling methods (including MPS) were tested in the fluvial reservoir and showed widely approved results [1][2][3][4][5][6][7]. However, in the delta reservoir, the sedimentary characteristics change along the source direction, and the model is not accepted for a fluvial deposit with the use of MPS based on the stationary hypothesis [7].…”

Section: Introductionmentioning

confidence: 99%

A location-based multiple point statistics method: modelling the reservoir with non-stationary characteristics

Yin¹,

Feng²

2017

Open Geosciences

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Abstract:In this paper, a location-based multiple point statistics method is developed to model a non-stationary reservoir. The proposed method characterizes the relationship between the sedimentary pattern and the deposit location using the relative central position distance function, which alleviates the requirement that the training image and the simulated grids have the same dimension. The weights in every direction of the distance function can be changed to characterize the reservoir heterogeneity in various directions. The local integral replacements of data events, structured random path, distance tolerance and multi-grid strategy are applied to reproduce the sedimentary patterns and obtain a more realistic result. This method is compared with the traditional Snesim method using a synthesized 3-D training image of Poyang Lake and a reservoir model of Shengli Oilfield in China. The results indicate that the new method can reproduce the non-stationary characteristics better than the traditional method and is more suitable for simulation of delta-front deposits. These results show that the new method is a powerful tool for modelling a reservoir with non-stationary characteristics.

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“…For example, the Sequential Indicator Simulation (SIS) (Caers, 2005), lacks the ability to control facies boundary conditions, the Truncated Gaussian Simulation (TGS) (Caers, 2005), provides for only simple facies transitional boundaries and while Object (also termed Boolean) Simulation (OS) can manage most non-overprinted complex facies sets, it is unstable in the presence of high density, closely spaced wells, highly computationally intensive and reliant on the (3D) training image models (Caers, 2005). Multi-Point GeoStatistics (MPS) (Strebelle and Journel, 2001) is rapidly growing in popularity offering the modeler the ability to create geological models with complex geometries, while conditioning to large amounts of well and seismic data. However, as pointed out by Daly and Mariethoz (2011), it is still a relatively new topic, which has had a long academic history and is now just finding its way into commercial software.…”

Section: Geologically-driven Facies Modelingmentioning

confidence: 99%