Аннотация лекции

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ЕАГО приглашает ВАС прослушать 10 ноября 2015 года (четверг) публичную лекцию на английском языке всемирно известного европейского ученого –практика О.Дюбрула (Olivier Dubrule, Imperial College/Total) на тему:

«Variogram and Transiogram-Based Approaches for building 3D Geological Facies Models»

Лекция состоится в Конференц-зале (8 эт. нового здания Научно-технической библиотеки РГУ нефти и газа имени И. М. Губкина) по адресу: г. Москва, Ленинский проспект, дом. 65, кор. 1.

Начало Лекции в 17 часов. Продолжительность лекции – один академический час.

Убедительно просим ВАС зарегистрироваться для посещения этой бесплатной лекции, прислав в наш адрес Вашу фамилию, имя и отчество и название организации.

Президент МОО ЕАГО Золотая Людмила Алексеевна

Аннотация лекции

«Variogram and Transiogram-Based Approaches for building 3D Geological Facies Models»

Much progress has been made in the recent years in the geostatistical modelling of clastic reservoirs. Approaches based on object-based models for fluviatile and turbidite reservoirs are now used routinely and included in most commercial earth modelling packages. The progress has not been as significant for reservoirs with less well-defined geometries, such as aeolian, shoreface or carbonate deposits. In these environments, variogram-based approaches appear to be quite flexible and capable of generating realistic models.

The goal of this presentation is to discuss the variogram-based approaches used for quantifying geological facies architecture in 3-D. We focus especially on Pluri-Gaussian Simulations and Transiogram-Based approaches.

Indicator Variograms are used in Sequential Indicator Simulations (SIS) (Alabert and Massonnat, 1990) or Pluri-Gaussian Simulations (PGS) (Armstrong et al, 2003). SIS usually treats indicator variograms independently from each other, which results in an unrealistic independence between the occurrence of different facies. PGS, a generalization of TGS (Truncated Gaussian Simulations) generate facies models which are internally consistent and where facies transitions can be accounted for through the definition of the Truncation Diagram.

Transiograms quantify the probability of finding a given facies at a distance h from another measured facies. Transiograms are closely related to spatial covariance functions. They are much more intuitive than variograms to the geologist and they also provide more flexibility for representing specific geological patterns such as assymetrical facies transitions (ie transition from A to B has a different probability from that from B to A). This cannot be done with the indicator variogram. Carle and Fogg, 2006 provide very convincing applications using “Markovian” transiograms, which are internally consistent and are rather simple to model. However it can be argued that the Markovian assumption is quite strong and too limited to cover all geological situations.

There is great benefit to draw from using PGS and transiogram-based approaches in combination, as PGS allow the use of much more general transiogram models than the Markovian family. Thanks to the PGS formalism, these models are internally consistent and open a very large spectrum of applications which can represent geology in a much more flexible way than just the Markovian ones. This is discussed from the theoretical point of view and illustrated through 3-D modelling examples.

References

Alabert F.G. and G.J. Massonnat, 1990. Heterogeneity in a Complex Turbiditic Reservoir: Stochastic Modelling of Facies and Petrophysical Variability, SPE 20604.

Armstrong, M., A.G. Galli, G. Le Loc’h, F. Geffroy and R. Eschard, 2003. Plurigaussian Simulations in Geosciences, Springer, 149 p.

Carle S.F. and Fogg G.E., 1996. Transition Probability-Based Geostatistics, Mathematical Geology, 28(4), p. 453-476.