dor_id: 4132832

506.#.#.a: Público

590.#.#.d: Los artículos enviados a la revista "Geofísica Internacional", se juzgan por medio de un proceso de revisión por pares

510.0.#.a: Consejo Nacional de Ciencia y Tecnología (CONACyT); Scientific Electronic Library Online (SciELO); SCOPUS, Dialnet, Directory of Open Access Journals (DOAJ); Geobase

561.#.#.u: https://www.geofisica.unam.mx/

650.#.4.x: Físico Matemáticas y Ciencias de la Tierra

336.#.#.b: article

336.#.#.3: Artículo de Investigación

336.#.#.a: Artículo

351.#.#.6: http://revistagi.geofisica.unam.mx/index.php/RGI

351.#.#.b: Geofísica Internacional

351.#.#.a: Artículos

harvesting_group: RevistasUNAM

270.1.#.p: Revistas UNAM. Dirección General de Publicaciones y Fomento Editorial, UNAM en revistas@unam.mx

590.#.#.c: Open Journal Systems (OJS)

270.#.#.d: MX

270.1.#.d: México

590.#.#.b: Concentrador

883.#.#.u: https://revistas.unam.mx/catalogo/

883.#.#.a: Revistas UNAM

590.#.#.a: Coordinación de Difusión Cultural

883.#.#.1: https://www.publicaciones.unam.mx/

883.#.#.q: Dirección General de Publicaciones y Fomento Editorial

850.#.#.a: Universidad Nacional Autónoma de México

856.4.0.u: http://revistagi.geofisica.unam.mx/index.php/RGI/article/view/415/428

100.1.#.a: Méndez-venegas, Javier; Díaz-viera, Martín A.

524.#.#.a: Méndez-venegas, Javier, et al. (2013). Geostatistical modeling of clay spatial distribution in siliciclastic rock samples using the plurigaussian simulation method. Geofísica Internacional; Vol. 52 Núm. 3: Julio 1, 2013; 229-247. Recuperado de https://repositorio.unam.mx/contenidos/4132832

245.1.0.a: Geostatistical modeling of clay spatial distribution in siliciclastic rock samples using the plurigaussian simulation method

502.#.#.c: Universidad Nacional Autónoma de México

561.1.#.a: Instituto de Geofísica, UNAM

264.#.0.c: 2013

264.#.1.c: 2013-07-01

653.#.#.a: Geoestadística; medios porosos; monogaussiano; plurigaussiano; distribución espacial; rocas siliciclásticas; Geostatistics; porous media; monogaussian; plurigaussian; spatial distribution; siliciclastic rock

506.1.#.a: La titularidad de los derechos patrimoniales de esta obra pertenece a las instituciones editoras. Su uso se rige por una licencia Creative Commons BY-NC-SA 4.0 Internacional, https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.es, para un uso diferente consultar al responsable jurídico del repositorio por medio del correo electrónico revistagi@igeofisica.unam.mx

884.#.#.k: http://revistagi.geofisica.unam.mx/index.php/RGI/article/view/415

001.#.#.#: 063.oai:revistagi.geofisica.unam.mx:article/415

041.#.7.h: spa

520.3.#.a: In order to implement secondary and enhanced oil recovery processes in complex terrigenous formations as is usual in turbidite deposits, a precise knowledge of the spatial distribution of shale grains is a crucial element for the fluid flow prediction. The reason of this is that the interaction of water with shale grains can significantly modify their size and/or shape, which in turn would cause porous space sealing with the subsequent impact in the flow. In this work, a methodology for stochastic simulations of spatial grains distributions obtained from scanning electron microscopy images of siliciclastic rock samples is proposed. The aim of the methodology is to obtain stochastic models would let us investigate the shale grain behavior under various physico-chemical interactions and flux regimes, which in turn, will help us get effective petrophysical properties (porosity and permeability) at core scale. For stochastic spatial grains simulations a plurigaussian method is applied, which is based on the truncation of several standard Gaussian random functions. This approach is very flexible, since it allows to simultaneously manage the proportions of each grain category in a very general manner and to rigorously handle their spatial dependency relationships in the case of two or more grain categories. The obtained results show that the stochastically simulated porous media using the plurigaussian method adequately reproduces the proportions, basic statistics and sizes of the pore structures present in the studied reference images.doi: https://doi.org/10.1016/S0016-7169(13)71474-0

773.1.#.t: Geofísica Internacional; Vol. 52 Núm. 3: Julio 1, 2013; 229-247

773.1.#.o: http://revistagi.geofisica.unam.mx/index.php/RGI

022.#.#.a: ISSN-L: 2954-436X; ISSN impreso: 0016-7169

310.#.#.a: Trimestral

300.#.#.a: Páginas: 229-247

264.#.1.b: Instituto de Geofísica, UNAM

doi: https://doi.org/10.1016/S0016-7169(13)71474-0

handle: 4fcfb047916547df

harvesting_date: 2023-06-20 16:00:00.0

856.#.0.q: application/pdf

file_creation_date: 2013-06-21 16:04:10.0

file_modification_date: 2022-07-05 14:55:21.0

file_creator: Méndez-Venegas J.

file_name: c8f866334d3cb62ed30a3b8723aec6675b0c97bd54c5a9b019496485b172664b.pdf

file_pages_number: 19

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file_size: 4493170

245.1.0.b: Geostatistical modeling of clay spatial distribution in siliciclastic rock samples using the plurigaussian simulation method

last_modified: 2023-06-20 16:00:00

license_url: https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.es

license_type: by-nc-sa

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