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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About me
About me
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Posts
Future Blog Post
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Siyan test blog post
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portfolio
Research item 1
Lattice Boltzmann Method (LBM) single/multi-phase flow simulation in porous media
Research item number 2
Mechanistic study of Low salinity waterflooding (LSW) in carbonates reservoir system
Research summary
A research summary mindmap 1
publications
Molecular Simulation Of Enhanced Oil Recovery In Shale
Published in 10th International Conference on Applied Energy (ICAE2018), 2018
Ali Takbiri-Borujeni, Mohammad Kazemi, Siyan Liu, Zhi Zhong. ICAE 2018.
Download here
Numerical simulation of Water-alternating-gas Process for Optimizing EOR and Carbon Storage
Published in 10th International Conference on Applied Energy (ICAE2018), 2018
Zhi Zhong, Siyan Liu, Timothy R. Carr, Ali Takbiri-Borujeni, Mohammad Kazemi, Qinwen Fu. ICAE 2018.
Download here
A case study on homogeneous and heterogeneous reservoir porous media reconstruction by using generative adversarial networks
Published in 10th International Conference on Applied Energy (ICAE2018), 2018
Siyan Liu, Zhi Zhong, Ali Takbiri-Borujeni, Mohammad Kazemi, Qinwen Fu, Yuhao Yang ICAE 2018.
Download here
Dew point pressure prediction based on mixed-kernels-function support vector machine in gas-condensate reservoir
Published in Fuel 2018, 2018
Zhi Zhong, Siyan Liu, Mohammad Kazemi, Timothy R. Carr. Fuel.
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Application of Neural Networks in Multiphase Flow Through Porous Media: Predicting Capillary Pressure and Relative Permeability Curves. Journal of Petroleum Science and Engineering, Volume 180, September 2019, Page 445-455
Published in Journal of Petroleum Science and Engineering, 2019
Siyan Liu, Arsalan Zolfaghari, Shariar Shaun Sattarin, Amirmasoud Kalantari-Dahaghi, Shahin Negahban. Journal of Petroleum Science and Engineering, Volume 180, September 2019, Page 445-455.
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Fast estimation of permeability in sandstones by 3d convolutional neural networks
Published in SEG Technical Program Expanded Abstracts 2019, 2019
Siyan Liu, Reza Barati, and Chi Zhang.
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Pore-Scale Characterization of Eagle Ford Outcrop and Reservoir Cores with SEM/BSE, EDS, FIB-SEM, and Lattice Boltzmann Simulation
Published in SPE Annual Technical Conference and Exhibition, 30 September - 2 October, Calgary, Alberta, Canada, 2019
Sherifa Cudjoe, Siyan Liu, Reza Barati, Franciszek Hasiuk, Robert Goldstein, Jyun-Syung Tsau, Brian Nicoud, Kyle Bradford, Amanda Baldwin, David Mohrbacher.
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An Efficient Bayesian Method for Advancing the Application of Deep Learning in Earth Science
Published in 2019 International Conference on Data Mining Workshops (ICDMW), 2019
Dan Lu, Siyan Liu, Daniel Ricciuto.
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Application of variational policy gradient to atomic-scale materials synthesis
Published in Arxiv, 2020
Siyan Liu, Nikolay Borodinov, Lukas Vlcek, Dan Lu, Nouamane Laanait, Rama K. Vasudevan.
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talks
Statistical 3D Modeling of the Triassic Fine Siliciclastic Reservoir in the An-Sai Oil Field, Shaanxi, Central China
Published:
Siyan Liu, Jiafei Zhang, Ping Wang and Ziqiang Chen
Numerical simulation of Water-alternating-gas Process for Optimizing EOR and Carbon Storage
Published:
Zhi Zhong, Siyan Liu, Timothy R. Carr, Ali Takbiri-Borujeni, Mohammad Kazemi, Qinwen Fu. ICAE 2018.
Molecular Simulation Of Enhanced Oil Recovery In Shale
Published:
Ali Takbiri-Borujeni, Mohammad Kazemi, Siyan Liu, Zhi Zhong. ICAE 2018.
A case study on homogeneous and heterogeneous reservoir porous media reconstruction by using generative adversarial networks
Published:
Siyan Liu, Zhi Zhong, Ali Takbiri-Borujeni, Mohammad Kazemi, Qinwen Fu, Yuhao Yang ICAE 2018.
Understanding the Mechanisms of Low Salinity Water Flooding in Carbonate Reservoir at Pore Scale: A Numerical Study Using Lattice-Boltzmann Method Coupled with Multi-Phase Reactive Transport Modeling
Published:
Siyan Liu, Chi Zhang and Reza Barati
An efficient Bayesian inference algorithm for advancing neural network optimization and uncertainty quantification
Published:
Dan Lu and Siyan Liu
Fast estimation of permeability in sandstones by 3D convolutional neural networks
Published:
Siyan Liu, Reza Barati, and Chi Zhang SEG 2019.
Pore-Scale Characterization of Eagle Ford Outcrop and Reservoir Cores with SEM/BSE, EDS, FIB-SEM, and Lattice Boltzmann Simulation
Published:
Sherifa Cudjoe, Siyan Liu, Reza Barati, Franciszek Hasiuk, Robert Goldstein, Jyun-Syung Tsau, Brian Nicoud, Kyle Bradford, Amanda Baldwin, David Mohrbacher. SPE-ATCE 2019.
Fast Estimation of Permeability for Sandstones and carbonate reservoir rocks by 3D Bayesian Convolutional Neural Networks with uncertainty quantification
Published:
Siyan Liu, Dan Lu, Chi Zhang, Reza Barati. AGU 2019.
teaching
Graduate Teaching Assistant (Spring 2017)
C&PE 628 Petroleum Engineering Design, The University of Kansas, Department of Chemical & Petroleum Engineering, 2017
C&PE 628 is about the design problems related to petroleum reservoir development such as selection of optimum well spacing for a specified reservoir, evaluation of a producing property or installation of a waterflood. Designs consider economic, uncertainty analysis, as well as conservation, environmental, and professional ethics factors.
Graduate Teaching Assistant (Spring 2018)
C&PE 618 Secondary Recovery, The University of Kansas, Department of Chemical & Petroleum Engineering, 2018
C&PE 618 is the study of waterflooding based upon linear displacement theory. Extension to two and three dimensions through correlations and stream tube models. Design of waterfloods including preparation of a reservoir description for waterflood evaluation.
Graduate Teaching Assistant (Fall 2018)
C&PE 625 Unconventional Reservoirs, The University of Kansas, Department of Chemical & Petroleum Engineering, 2018
C&PE 625 is about the principles of unconventional reservoir engineering including properties and use of shale reservoirs, hydraulic fracturing, and relevant environmental and economic factors
Graduate Teaching Assistant (Spring 2019)
C&PE 325 Numerical Methods and Statistics for Engineers, The University of Kansas, Department of Chemical & Petroleum Engineering, 2019
C&PE 325 An introduction to numerical methods and statistics and their application to engineering problems. Numerical methods topics include finding roots of a single nonlinear equation, numerical solution of ordinary differential equations, numerical integration, and solutions of ordinary differential equations. Statistical topics include regression and curve fitting, probability and probability distributions, expected value and hypothesis testing, and optimization of single and multiple-variable systems. Implementing numerical algorithms using computer programming will be emphasized, along with the fundamentals of programming, including data typing, branching, and iteration. Applications specific to chemical and petroleum engineering systems will be considered. The fast, easy to use dynamical typed programming language Julia (https://julialang.org/) will be introduced in this course.