An approach to Seismic Interpretation based on Cognitive Vision/Seismic Interpretation

Verney, Philippe

doi:10.3997/2214-4609.20148090

Cited by 4 publications

(5 citation statements)

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“…The method employed in this software is based on a global geological model from 3D seismic data (Gupta et al, 2008;Pauget et al, 2009;Lemaire et al, 2010;Schmidt et al, 2010;Hoyes and Cheret, 2011). Other methods of global automated 3D horizon picking exist and have been reviewed by Hoyes and Cheret (2011), as "dip-driven" type (Lomask, 2003;De Groot et al, 2006) or "Horizon patches" methods (Verney et al, 2008). These methods are based on merging small surfaces that exhibit similar seismic attributes.…”

Section: Methodsmentioning

confidence: 98%

High-resolution architecture of a polygonal fault interval inferred from geomodel applied to 3D seismic data from the Gjallar Ridge, Vøring Basin, Offshore Norway

et al. 2012

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Section: Methodsmentioning

confidence: 98%

High-resolution architecture of a polygonal fault interval inferred from geomodel applied to 3D seismic data from the Gjallar Ridge, Vøring Basin, Offshore Norway

et al. 2012

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“…In spite of their interest, all of these methods are sensitive to weak seismic amplitudes close to the faults. This is the main reason why automatic interpretation of horizons and faults based on cognitive vision was proposed as an alternative solution (Verney et al, 2008).…”

Section: Accepted Manuscriptmentioning

confidence: 99%

“…This method allows to add more interpretative constraints than an automatic analysis of the information captured in a seismic bloc, specifically on complex area. These surface extrapolations can complement a preliminary manual or automatic seismic interpretation of horizon and faults (Verney, 2008) or other methods for fault characterization.…”

Section: Accepted Manuscriptmentioning

confidence: 99%

Building a 3D faulted a priori model for stratigraphic inversion: Illustration of a new methodology applied on a North Sea field case study

Rainaud

Clochard

Delépine

et al. 2018

Journal of Applied Geophysics

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Accurate reservoir characterization is needed all along the development of an oil and gas field study. It helps building 3D numerical reservoir simulation models for estimating the original oil and gas volumes in place and for simulating fluid flow behaviors. At a later stage of the field development, reservoir characterization can also help deciding which recovery techniques need to be used for fluids extraction. In complex media, such as faulted reservoirs, flow behavior predictions within volumes close to faults can be a very challenging issue. During the development plan, it is necessary to determine which types of communication exist between faults or which potential barriers exist for fluid flows. The solving of these issues rests on accurate fault characterization. In most cases, faults are not preserved along reservoir characterization workflows. The memory of the interpreted faults from seismic is not kept during seismic inversion and further interpretation of the result. The goal of our study is at first to integrate a 3D fault network as a priori information into a model-based stratigraphic inversion procedure. Secondly, we apply our methodology on a well-known oil and gas case study over a typical North Sea field (UK Northern North Sea) in order to demonstrate its added value for determining reservoir properties. More precisely, the a priori model is composed of several geological units populated by physical attributes, they are extrapolated from well log data following the deposition mode, but usually a priori model building methods respect neither the 3D fault geometry nor the stratification dips on the fault sides. We address this difficulty by applying an efficient flattening method for each stratigraphic unit in our workflow. Even before seismic inversion, the obtained stratigraphic model has been directly used to model synthetic seismic on our case study. Comparisons between synthetic seismic obtained from our 3D fault network model give much lower residuals than

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“…The choice for this case study is motivated by the fact that it defines a complex chain involving different compositions of services. Moreover, precise information on this part through the work of (Verney et al, 2008) can be accessed.…”

Section: Seismic Interpretationmentioning

confidence: 99%

Toward a Semantic Management of Geological Modeling Workflows

Belaid¹,

Aït‐Ameur²,

Jean³

et al. 2010

Proceedings of the International Conference on Knowledge Engineering and Ontology Development

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Today, the petroleum industry demonstrates a greater concern toward ecology. Actions are undertaken in order to reduce the CO2 emissions in particular. Storing the CO2 in depleted petroleum reservoirs represents one of the ways of controlling the CO2 emissions. However, a prior modeling of the reservoirs has to be done for a secure storage. This geological modeling task follows series of complex workflows (business processes) of data processing services. These workflows are built without any methodological rule. It is difficult for geologists to execute workflows or even services that they have not designed. Moreover, it is not possible to build new workflows without having a precise knowledge on the compounding services and sub-workflows. We claim that in order to solve the two stated problems, explicit semantics has to be applied to describe the workflows and the services that compose them. In this article, we first explain how geologists operate today. Then, we show how we enrich geological modeling workflows, the services that compose them and the data they manipulate with semantic indexations through ontology-based characterizations (Geological Data and Services Ontologies). Finally, we explain how our approach supports reuse of existing workflows and build new ones.

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An approach to Seismic Interpretation based on Cognitive Vision/Seismic Interpretation

Cited by 4 publications

References 0 publications

High-resolution architecture of a polygonal fault interval inferred from geomodel applied to 3D seismic data from the Gjallar Ridge, Vøring Basin, Offshore Norway

High-resolution architecture of a polygonal fault interval inferred from geomodel applied to 3D seismic data from the Gjallar Ridge, Vøring Basin, Offshore Norway

Building a 3D faulted a priori model for stratigraphic inversion: Illustration of a new methodology applied on a North Sea field case study

Toward a Semantic Management of Geological Modeling Workflows

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