Porosity prediction from pre-stack seismic data via committee machine with optimized parameters-Reference-Cited by-同舟云学术

Porosity prediction from pre-stack seismic data via committee machine with optimized parameters

Published:2022-03 Issue: Volume:210 Page:110067
ISSN:0920-4105
Container-title:Journal of Petroleum Science and Engineering
language:en
Short-container-title:Journal of Petroleum Science and Engineering

Author:

Gholami Amin,Amirpour Masoud^ORCID,Ansari Hamid Reza,Seyedali Seyed Mohsen,Semnani Amir^ORCID,Golsanami Naser,Heidaryan Ehsan,Ostadhassan Mehdi

Publisher

Elsevier BV

Subject

Geotechnical Engineering and Engineering Geology,Fuel Technology

Reference73 articles.

1. Past, present and prospect of an Artificial Intelligence (AI) based model for sediment transport prediction;Afan;J. Hydrol.,2016

2. Support vector regression for porosity prediction in a heterogeneous reservoir: a comparative study;Al-Anazi;Comput. Geosci.,2010

3. Bat-inspired algorithms with natural selection mechanisms for global optimization;Al-Betar;Neurocomputing,2018

4. Estimating the refractive index of oxygenated and deoxygenated hemoglobin using genetic algorithm–support vector regression model;Alade;Comput. Methods Progr. Biomed.,2018

5. Integration of geology, rock physics, ogs, and prestack seismic data for reservoir porosity estimation;AlMuhaidib;AAPG (Am. Assoc. Pet. Geol.) Bull.,2012

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