Developing Ensemble Machine Learning Models to Predict Petrophysical Properties of Sandstone Reservoirs

QR Code

Developing Ensemble Machine Learning Models to Predict Petrophysical Properties of Sandstone Reservoirs

This research investigated the applicability of bagging and boosting ensemble machine learning algorithms in predicting petrophysical properties, namely porosity, permeability and water saturation which is a vital aspect in reservoir characterization. Further, an in-depth analysis was done on the ef...

Full description

Bibliographic Details
Main Author:	Kohona Walawwe, Kushan Oshadi Sandunil
Format:	Thesis
Published:	Curtin University 2025
Online Access:	http://hdl.handle.net/20.500.11937/97704

Similar Items

Two-Phase Oil-Water Empirical Correlation Models for SCAL and Petrophysical Properties in Intermediate Wet Sandstone Reservoirs
by: Sabila, T., et al.
Published: (2019)

Petrophysics study of sandstone by ultrasonic pulse velocity
by: Samsuri, Ariffin, et al.
Published: (2004)

Petrophysical Evaluation of Gas shale Reservoirs
by: Labani, Mohammad Mahdi, et al.
Published: (2015)

Prediction of shear wave velocity from petrophysical data utilizing intelligent systems: An example from a sandstone reservoir of Carnarvon Basin, Australia
by: Rezaee, M. Reza, et al.
Published: (2007)

An optimized ensemble for predicting reservoir rock properties in petroleum industry
by: Kenari, Seyed Ali Jafari
Published: (2013)

Improving the prediction of petroleum reservoir characterization with a stacked generalization ensemble model of support vector machines
by: Fatai Adesina, Anifowose, et al.
Published: (2015)

A triple porosity model for petrophysical analysis of naturally fractured reservoirs
by: Aguilera, Roberto F., et al.
Published: (2004)

Feasibility of a data-constrained prediction of hydrocarbon reservoir sandstone microstructures
by: Yang, Y., et al.
Published: (2010)

Recent Advances in Multiscale Petrophysics Characterization and Multiphase Flow in Unconventional Reservoirs
by: Cai, J., et al.
Published: (2022)

Modelling the low-frequency electrical properties of pyrite-bearing reservoir sandstones
by: Han, T., et al.
Published: (2015)

An investigation into the interrelationship between petrophysical properties of potential gas shale reservoirs from Western Australia
by: Labani, Mohammad Mahdi
Published: (2014)

Predicting Petroleum Reservoir Properties from Downhole Sensor Data using an Ensemble Model of Neural Networks
by: Fatai Adesina, Anifowose, et al.
Published: (2013)

Prediction Of Petroleum Reservoir Properties Using Nonlinear Feature Selection And Ensembles Of Computational Intelligence Techniques
by: Anifowose, Fatai Adesina
Published: (2015)

Ensemble model of non-linear feature selection-based Extreme Learning Machine for improved natural gas reservoir characterization
by: Fatai Adesina, Anifowose, et al.
Published: (2015)

Drivers of low salinity effect in sandstone reservoirs
by: Pooryousefy, E., et al.
Published: (2018)

An ensemble of machine learning and anti-learning methods for predicting tumour patient survival rates
by: Roadknight, Chris, et al.
Published: (2015)

An enhanced approach to predict permeability in reservoir sandstones using artificial neural networks (ANN)
by: Ben-Awuah, Joel, et al.
Published: (2017)

An experimental study for carbonate reservoirs on the impact of CO2-EOR on petrophysics and oil recovery
by: Khather, M., et al.
Published: (2019)

Reservoir Characterisation of Gas Shale through Sedimentary, Mineralogical, Petrophysical and Statistical Rock Types Evaluation
by: Iqbal, Muhammad Atif
Published: (2023)

Ensemble Learning Boosting Model of Improving Classification and Predicting
by: Bambang, Siswoyo A, et al.
Published: (2020)

Stress induced anisotropy in sandstone reservoir and shale overburden - AVO modeling
by: Brajanovski, Miroslav, et al.
Published: (2009)

Trajectory Ensembles and Machine Learning: From reinforcement learning for rare event sampling to training of neural network ensembles
by: Mair, Jamie
Published: (2023)

Effect of Bioturbation on Reservoir Rock Quality of Reservoir Sandstones in the Baram Delta, Offshore Sarawak, Malaysia
by: Ben-Awuah, Joel, et al.
Published: (2015)

Petrophysical and Reservoir Characteristics of Sedimentary Rocks From Offshore West Baram Delta, Sarawak Basin, Malaysia
by: Ben-Awuah, Joel, et al.
Published: (2016)

Study on the effect of solid particle on water-flooding development in low permeability sandstone reservoir
by: Wu, J., et al.
Published: (2014)

Prediction of flow properties of upper cretaceous continental deposits from petrophysical and geological data: T. Field
by: Miley, E., et al.
Published: (2010)

An ensemble deep learning model for vehicular engine health prediction
by: Joseph Chukwudi, Isinka, et al.
Published: (2024)

Compaction Trends of Shales: Rock Physics and Petrophysical Properties
by: Beloborodov, Roman
Published: (2017)

A Novel CO2 Flooding Based EOR for Sandstone Reservoirs
by: Xu, Xingguang
Published: (2016)

Acoustic response of reservoir sandstones during injection of supercritical CO2
by: Lebedev, Maxim, et al.
Published: (2014)

Experimental study on permeability stress sensitivity in tight sandstone oil reservoirs
by: Xiaofeng Tian,, et al.
Published: (2015)

Controls on Pore Geometry in the Tirrawarra Sandstone Reservoir, Cooper Basin, Australia
by: Rezaee, M. Reza, et al.
Published: (1996)

Travel time prediction using ensemble learning algorithms
by: Li, Xia
Published: (2018)

Predicting young imposter syndrome using ensemble learning
by: Khan, Md. Nafiul Alam, et al.
Published: (2022)

Permeability Prediction Using Machine Learning Methods for the CO2 Injectivity of the Precipice Sandstone in Surat Basin, Australia
by: Rezaee, Reza, et al.
Published: (2022)

A Hybrid of Functional Networks and Support Vector Machine Models for the Prediction of Petroleum Reservoir Properties
by: Fatai Adesina, Anifowose, et al.
Published: (2011)

Ensemble learning model for petroleum reservoir characterization: A case of feed-forward back-propagation neural networks
by: Fatai, Anifowose, et al.
Published: (2013)

A variable shape distribution (VSD) model for characterization of pore throat radii, drill cuttings, fracture apertures and petrophysical properties in tight, shale and conventional reservoirs
by: Aguilera, Roberto F., et al.
Published: (2012)

Classification of Geochemical and Petrophysical Data by Using Classification of Geochemical and Petrophysical Data by Using Fuzzy Clustering
by: Kieu, D., et al.
Published: (2015)

Are self-consistent models capable of jointly modeling elastic velocity and electrical conductivity of reservoir sandstones?
by: Han, T., et al.
Published: (2016)

Cannot write session to /tmp/vufind_sessions/sess_02jcarvekqf0fevnhft8o97hge