Multiple point geostatistical simulation with adaptive filter derived from neural network for sedimentary facies classification-Reference-Cited by-同舟云学术

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Multiple point geostatistical simulation with adaptive filter derived from neural network for sedimentary facies classification

Published:2020-08 Issue: Volume:118 Page:104406
ISSN:0264-8172
Container-title:Marine and Petroleum Geology
language:en
Short-container-title:Marine and Petroleum Geology

Author:

Han Feilong,Zhang Hongbing,Rui Jianwen,Wei Kuiye,Zhang Dailu,Xiao Wei

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Stratigraphy,Economic Geology,Geology,Geophysics,Oceanography

Reference44 articles.

1. Efficient training image selection for multiple-point geostatistics via analysis of contours;Abdollahifard;Comput. Geosci.,2019

2. Permeability prediction and diagenesis in tight carbonates using machine learning techniques;Al Khalifah;Mar. Petrol. Geol.,2020

3. Introduction to Machine Learning;Alpaydin,2009

4. Variations in the Arctic's multiyear sea ice cover: a neural network analysis of SMMR‐SSM/I data, 1979–2004;Belchansky;Geophys. Res. Lett.,2005

5. Generalized denoising auto-encoders as generative models;Bengio,2013

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2. Generative Adversarial Networks to incorporate the Training Image uncertainty in multiple-point statistics simulation;Geoenergy Science and Engineering;2023-11

3. A modified method of multiple point geostatistics for spatial simulation of sedimentary facies for carbonate reservoirs;Journal of Applied Geophysics;2023-08

4. Multiple-Point Geostatistical Simulation of Nonstationary Sedimentary Facies Models Based on Fuzzy Rough Sets and Spatial-Feature Method;SPE Journal;2023-06-27

5. The depositional model of the Lower Cretaceous Nantun Formation and its implications for oil accumulation in the northern Wuerxun Sag of Hailar Basin, NE China;Sedimentary Geology;2022-08

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