Stochastic integration of seismic data and geologic scenarios: A West Africa submarine channel saga

Caers, Jef; Strebelle, Sebastien; Payrazyan, Karen

doi:10.1190/1.1564521

Cited by 52 publications

(19 citation statements)

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“…The approach allows simulations of facies maps using conditional probabilities that describe the exact geometry of the surrounding data. In practice, the conditional probabilities are calculated from a training image that can be derived either from outcrop observation, expert knowledge or geophysics (see an example in Caers et al 2003). The method makes it possible to simulate complex geometries such as channels, meanders or lenses and can preserve the relations between the facies.…”

Section: Geostatistics Fights Back: Discontinuous Facies Modelsmentioning

confidence: 99%

Dealing with spatial heterogeneity

et al. 2005

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Heterogeneity can be dealt with by defining homogeneous equivalent properties, known as averaging, or by trying to describe the spatial variability of the rock properties from geologic observations and local measurements. The techniques available for these descriptions are mostly continuous Geostatistical models, or discontinuous facies models such as the Boolean, Indicator or Gaussian-Threshold models and the Markov chain model. These facies models are better suited to treating issues of rock strata connectivity, e.g. buried high permeability channels or low permeability barriers, which greatly affect flow and, above all, transport in aquifers. Genetic models provide new ways to incorporate more geology into the facies description, an approach that has been well developed in the oil industry, but not enough in hydrogeology. The conclusion is that future work should be focused on improving the facies models, comparing them, and designing new in situ testing procedures (including geophysics) that would help identify the facies geometry and properties. A world-wide catalog of aquifer facies geometry and properties, which could combine site genesis and description with methods used to assess the system, would be of great value for practical applications.RØsumØ On peut aborder le problme de l'hØtØrogØnØitØ en s'efforçant de dØfinir une permØabilitØ Øquivalente homogne, par prise de moyenne, ou au contraire en dØ-crivant la variation dans l'espace des propriØtØs des roches à partir des observations gØologiques et des mesures locales. Les techniques disponibles pour une telle description sont soit continues, comme l'approche GØosta-tistique, soit discontinues, comme les modles de facis, BoolØens, ou bien par Indicatrices ou Gaussiennes SeuillØes, ou enfin Markoviens. Ces modles de facis sont mieux capables de prendre en compte la connectivitØ des strates gØologiques, telles que les chenaux enfouis à forte permØabilitØ, ou au contraire les facis fins de barrires de permØabilitØ, qui ont une influence importante sur les Øcoulement, et, plus encore, sur le transport. Les modles gØnØtiques rØcemment apparus ont la capacitØ de mieux incorporer dans les modles de facis les observations gØologiques, chose courante dans l'industrie pØ-trolire, mais insuffisamment dØveloppØe en hydrogØo-logie. On conclut que les travaux de recherche ultØrieurs devraient s'attacher à dØvelopper les modles de facis, à les comparer entre eux, et à mettre au point de nouvelles mØthodes d'essais in situ, comprenant les mØthodes gØo-physiques, capables de reconnaître la gØomØtrie et les propriØtØs des facis. La constitution d'un catalogue mondial de la gØomØtrie et des propriØtØs des facis aquifres, ainsi que des mØthodes de reconnaissance utilisØes pour arriver à la dØtermination de ces systmes, serait d'une grande importance pratique pour les applications.Resumen La heterogeneidad se puede manejar por medio de la definición de características homogØneas equivalentes, conocidas como promediar o tratando de describir la variabilidad espacia...

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Section: Geostatistics Fights Back: Discontinuous Facies Modelsmentioning

confidence: 99%

Dealing with spatial heterogeneity

et al. 2005

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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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“…A common approach resulting from geostatistics to determine the effect of modelling uncertainty a posteriori, is to create a set of possible realizations of the reservoir model [3], [11]. The finite set of realizations is created in such a way that it gives a discretized approximation of the uncertainty space associated with the modelling process of the real oil reservoir.…”

Section: Introductionmentioning

confidence: 99%

Robust optimization of oil reservoir flooding

Essen

Zandvliet

Hof

et al. 2006

2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006

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Abstract-Over the recent years a variety of new developments have been introduced within the field of oil recovery, with the aim to maximize production of oil and gas from petroleum reservoirs. One of these new developments is the introduction of so-called "smart wells", which are equipped with control valves to actively control the oil production. The optimal operational strategy of these control valves can be found using a dynamic optimization procedure. However, due to geological uncertainty inherent to reservoir modelling, the mismatch between the reservoir model and the real reservoir may become considerable. As a result, a model-based optimal solution may seize to be the optimal, but will yield sub-optimal or even worse results. Within this work a robust optimization approach is presented that takes the possibly large impact of the mismatch between model and reservoir into account using a set of multiple reservoir realizations.

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Stochastic integration of seismic data and geologic scenarios: A West Africa submarine channel saga

Cited by 52 publications

References 0 publications

Dealing with spatial heterogeneity

Dealing with spatial heterogeneity

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

Robust optimization of oil reservoir flooding

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