Multiple-point simulation integrating wells, three-dimensional seismic data, and geology

Liu, Yuhong; Harding, Andrew; Abriel, William L.; Strebelle, Sebastien

doi:10.1306/02170403078

Cited by 73 publications

(24 citation statements)

References 6 publications

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“…tance between the unsimulated grid and the data event saved in step (4), and the data event with the least distance is selected as the final simulation result. (6) Local or whole substitution of the un-simulated grid is conducted with the selected data event.…”

Section: Methodsmentioning

confidence: 99%

“…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%

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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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Section: Methodsmentioning

confidence: 99%

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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“…Multiple-point statistics allows for stochastically generating complex heterogeneous fields by integrating a conceptual model chosen by the user. Several case studies have shown the applicability of the method (Caers et al 2003;Liu et al 2004;Comunian et al 2011;Hajizadeh et al 2011). Moreover, de Iaco and Maggio (2011) or Kessler et al (2012) use several criteria emphasizing that multiple-point statistics gives better results than traditional simulation methods based on bi-point statistics (variograms, transiograms).…”

Section: Introductionmentioning

confidence: 99%

Parallel Multiple-Point Statistics Algorithm Based on List and Tree Structures

Straubhaar

Walgenwitz²,

Renard

2013

Math Geosci

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Multiple-point statistics are widely used for the simulation of categorical variables because the method allows for integrating a conceptual model via a training image and then simulating complex heterogeneous fields. The multiple-point statistics inferred from the training image can be stored in several ways. The tree structure used in classical implementations has the advantage of being efficient in terms of CPU time, but is very RAM demanding and then implies limitations on the size of the template, which serves to make a proper reproduction of complex structures difficult. Another technique consists in storing the multiple-point statistics in lists. This alternative requires much less memory and allows for a straightforward parallel algorithm. Nevertheless, the list structure does not benefit from the shortcuts given by the branches of the tree for retrieving the multiple-point statistics. Hence, a serial algorithm based on list structure is generally slower than a tree-based algorithm. In this paper, a new approach using both list and tree structures is proposed. The idea is to index the lists by trees of reduced size: the leaves of the tree correspond to distinct sublists that constitute a partition of the entire list. The size of the indexing tree can be controlled, and then the resulting algorithm keeps memory requirements low while efficiency in terms of CPU time is significantly improved. Moreover, this new method benefits from the parallelization of the list approach.

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“…, Caers et al, 2003;Liu et al, 2004;Tetzlaff et al, 2005;Falivene et al, 2006;Novakovic andRoth, 2011 , 2006;Okano, 2007 2006 Yamada (Fig. 6).…”

mentioning

confidence: 96%

多点間統計を用いた侵食谷形状モデリング

Tsuji

Okada

et al. 2013

Jour. Geol. Soc. Japan

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Geologic concepts are essential for building geologic models for the exploration and development of oil and gas reservoirs. It is, however, difficult to deliver geologic concepts into geologic models with traditional stochastic modeling when the geologic concepts featured have complex morphologies. Multiple-point geostatistics, regarded as one of the best ways to overcome this difficulty, are now being put into practical use. In multiple-point geostatistics, geologic concepts are captured as multiple-point patterns through training images. However, multiple-point geostatistics has not been used for building geologic models featuring complex morphology.Therefore, we applied multiple-point geostatistics to the reproduction of a complex-shaped reference model that is a close replica of dendritic, incised valleys. Pseudo-wells and three-dimensional seismic data based on the reference model were prepared, and training images were created by using process modeling to simulate the development of incised valley geomorphology.As a result, the geologic model built using multiple-point geostatistics properly reproduced the complex morphology of the reference model. Data of various scales and resolutions were able to be integrated with the model. Therefore, the study shows that a multiplepoint geostatistical approach is effective for modeling reservoirs composed of complex-shaped incised-valley-filling deposits.

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Multiple-point simulation integrating wells, three-dimensional seismic data, and geology

Cited by 73 publications

References 6 publications

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

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

Parallel Multiple-Point Statistics Algorithm Based on List and Tree Structures

多点間統計を用いた侵食谷形状モデリング

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