A workflow for modelling fluvial meander-belt successions: Combining forward stratigraphic modelling and multi-point geostatistics-Reference-Cited by-同舟云学术

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A workflow for modelling fluvial meander-belt successions: Combining forward stratigraphic modelling and multi-point geostatistics

Published:2021-06 Issue: Volume:201 Page:108411
ISSN:0920-4105
Container-title:Journal of Petroleum Science and Engineering
language:en
Short-container-title:Journal of Petroleum Science and Engineering

Author:

Montero Jose M.,Colombera Luca,Yan Na,Mountney Nigel P.

Funder

Occidental Petroleum

Saudi Aramco

Shell

Tullow Oil

Fundación YPF

Chevron

China National Offshore Oil Corporation

Equinor

Aker BP

ConocoPhillips

Natural Environment Research Council

Publisher

Elsevier BV

Subject

Geotechnical Engineering and Engineering Geology,Fuel Technology

Reference64 articles.

1. Dynamic impact and flow-based upscaling of the estuarine point-bar stratigraphic architecture;Alpak;J. Petrol. Sci. Eng.,2014

2. Uncertainty quantification in reservoir prediction: Part 1—model realism in history matching using geological prior definitions;Arnold;Math. Geosci.,2019

3. Sedimentation in the meandering river Endrick;Bluck;Scot. J. Geol.,1971

4. Simulation model of alluvial stratigraphy;Bridge;Sedimentology,1979

5. Geostatistical reservoir modelling using statistical pattern recognition;Caers;J. Petrol. Sci. Eng.,2001

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1. Assessing the impact of sedimentary heterogeneity on CO2 injection in fluvial meander-belt successions using geostatistical modelling informed by geological analogues;International Journal of Greenhouse Gas Control;2024-07

2. Stochastic Modeling of Thin Mud Drapes Inside Point Bar Reservoirs With ALLUVSIM‐GANSim;Water Resources Research;2024-06

3. A 3D forward stratigraphic model of aeolian dune evolution for prediction of lithofacies heterogeneity;Computers & Geosciences;2024-05

4. Conditional stochastic simulation of fluvial reservoirs using multi-scale concurrent generative adversarial networks;Computational Geosciences;2024-03-25

5. Research on the Construction Method of a Training Image Library Based on cDCGAN;Applied Sciences;2023-08-30

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