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dc.contributor.author
Yeste, Luis Miguel
dc.contributor.author
Palomino, Ricardo
dc.contributor.author
Varela, Augusto Nicolás
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dc.contributor.author
McDougall, Neil David
dc.contributor.author
Viseras, César
dc.date.available
2022-04-05T16:59:01Z
dc.date.issued
2021-07
dc.identifier.citation
Yeste, Luis Miguel; Palomino, Ricardo; Varela, Augusto Nicolás; McDougall, Neil David; Viseras, César; Integrating outcrop and subsurface data to improve the predictability of geobodies distribution using a 3D training image: A case study of a Triassic Channel – Crevasse-splay complex; Elsevier; Marine And Petroleum Geology; 129; 105081; 7-2021; 1-20
dc.identifier.issn
0264-8172
dc.identifier.uri
http://hdl.handle.net/11336/154398
dc.description.abstract
Fluvial sandstones deposited by high-sinuosity fluvial systems are one of the most complex reservoirs to predict and model with confidence, a reflection of both the geometries and complex distribution of the component geobodies. By integrating both analogue outcrop data and associated subsurface data, as well as new technical advances in the reconstruction of the outcrop in 3D (Digital Outcrop Models, DOM), the geostatistical parameters, which condition the modelling of these reservoirs, can be better determined. In addition, DOMs also allow us to easily extract the necessary georeferenced input data (digitized outcrop interpretations, geometrical parameters, aswell as, key surfaces) and so create geocellular outcrop models (GOM); a useful tool with which to contrast the results obtained from geostatistical simulations, as well as to quantify the uncertainty associated with the results. In this study, classical field data, digital data derived from outcrop models and subsurface data were combined in order to carry out a geostatistical modelling of aChannel ? Crevasse-splay complex outcrop analogue, located in the Triassic Red Beds of Iberian Meseta (TIBEM). Geostatistical modelling results were obtained by combining Object-based (OBM) and MultiPoint Statistics-based (MPS) modelling techniques.A critical element in this study was the design of appropriate modelling workflows with Petrel® which would best reproduce the distribution of heterogeneities at the scale of geobodies. The designed modelling workflow was used to construct a 3D Training Image (TI) of a fluvial reservoir comprising both a meandering channel system and its associated overbank sandstone deposits. The resulting TI represents all geobodies described in the studied outcrop example and is exportable to similar fluvial reservoirs. This TI was then used in MPS simulations, in order to establish how it could assist in the prediction of the reservoir geobodies, as well as confirming to what extent this prediction matched the outcrop.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Elsevier
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dc.rights
info:eu-repo/semantics/restrictedAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
Multi-point statistics
dc.subject
Training Images
dc.subject
Object-Based modelling
dc.subject
Digital Outcrop Model
dc.subject
Meandering fluvial system
dc.subject
Crevasse splay
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Heterogeneity
dc.subject
Outcrop/Behind Outcrop characterisation
dc.subject
TIBEM
dc.subject
Triassic
dc.subject.classification
Geología
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dc.subject.classification
Ciencias de la Tierra y relacionadas con el Medio Ambiente
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dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
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dc.title
Integrating outcrop and subsurface data to improve the predictability of geobodies distribution using a 3D training image: A case study of a Triassic Channel – Crevasse-splay complex
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2022-04-04T20:06:52Z
dc.journal.volume
129
dc.journal.number
105081
dc.journal.pagination
1-20
dc.journal.pais
Países Bajos
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dc.journal.ciudad
Amsterdam
dc.description.fil
Fil: Yeste, Luis Miguel. Universidad de Granada. Facultad de Ciencias. Departamento de Estratigrafía y Paleontología.; España
dc.description.fil
Fil: Palomino, Ricardo. Repsol Exploración S.A; España
dc.description.fil
Fil: Varela, Augusto Nicolás. YPF - Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
dc.description.fil
Fil: McDougall, Neil David. Repsol Exploración S.A; España
dc.description.fil
Fil: Viseras, César. Universidad de Granada. Facultad de Ciencias. Departamento de Estratigrafía y Paleontología.; España
dc.journal.title
Marine And Petroleum Geology
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dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0264817221001847?via%3Dihub
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/https://doi.org/10.1016/j.marpetgeo.2021.105081
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