相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。Acoustic impedance and lithology-based reservoir porosity analysis using predictive machine learning algorithms
Obed Kweku Agbadze et al.
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING (2022)
Performance evaluation of machine learning-based classification with rock-physics analysis of geological lithofacies in Tarakan Basin, Indonesia
Gian Antariksa et al.
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING (2022)
Half a century experience in rate of penetration management: Application of machine learning methods and optimization algorithms - A review
Mohammad Najjarpour et al.
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING (2022)
Optimization of selective withdrawal systems in hydropower reservoir considering water quality and quantity aspects
Motahareh Saadatpour et al.
EXPERT SYSTEMS WITH APPLICATIONS (2021)
Scale-dependent permeability and formation factor in porous media: Applications of percolation theory
Misagh Esmaeilpour et al.
FUEL (2021)
Experimental investigation of deterioration in mechanical properties of oil-based mud (OBM) contaminated API cement slurries & correlations for ultrasonic cement analysis
Nachiket Arbad et al.
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING (2021)
A modified semi-empirical correlation for designing two-phase separators
Mehdi Fadaei et al.
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING (2021)
Effect of Pore-Scale Heterogeneity on Scale-Dependent Permeability: Pore-Network Simulation and Finite-Size Scaling Analysis
Behzad Ghanbarian et al.
WATER RESOURCES RESEARCH (2021)
On the feasibility of using physics-informed machine learning for underground reservoir pressure management
Dylan Robert Harp et al.
EXPERT SYSTEMS WITH APPLICATIONS (2021)
Evolution of hydraulic conductivity models for sandy soils
Muhammad Arshad et al.
PROCEEDINGS OF THE INSTITUTION OF CIVIL ENGINEERS-GEOTECHNICAL ENGINEERING (2020)
Modeling reactive flow on carbonates with realistic porosity and permeability fields
Leandro de Paulo Ferreira et al.
ADVANCES IN WATER RESOURCES (2020)
Machine learning in geo- and environmental sciences: From small to large scale
Pejman Tahmasebi et al.
ADVANCES IN WATER RESOURCES (2020)
Computing the permeability and Forchheimer tensor of porous rocks via closure problems and digital images
C. G. Aguilar-Madera et al.
ADVANCES IN WATER RESOURCES (2020)
A stochastic learning-from-data approach to the history-matching problem
Cristina C. B. Cavalcante et al.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2020)
The role of fines on internal instability and its impact on undrained mechanical response of gap-graded soils
Jitrakon Prasomsri et al.
SOILS AND FOUNDATIONS (2020)
Pore-scale imaging with measurement of relative permeability and capillary pressure on the same reservoir sandstone sample under water-wet and mixed-wet conditions
Ying Gao et al.
ADVANCES IN WATER RESOURCES (2020)
Immiscible fluid displacement in porous media with spatially correlated particle sizes
Oshri Borgman et al.
ADVANCES IN WATER RESOURCES (2019)
A continuous learning algorithm for history matching
Cristina C. B. Cavalcante et al.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2019)
Fast evaluation of well placements in heterogeneous reservoir models using machine learning
Azor Nwachukwu et al.
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING (2018)
Estimation of permeability and effective porosity logs using deep autoencoders in borehole image logs from the brazilian pre-salt carbonate
Manuel Blanco Valentin et al.
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING (2018)
Effect of 2D Image Resolution on 3D Stochastic Reconstruction and Developing Petrophysical Trend
Hossein Izadi et al.
TRANSPORT IN POROUS MEDIA (2018)
A closer look at cross-validation for assessing the accuracy of gene regulatory networks and models
Shayan Tabe-Bordbar et al.
SCIENTIFIC REPORTS (2018)
Prediction of fluid topology and relative permeability in imbibition in sandstone rock by direct numerical simulation
F. O. Alpak et al.
ADVANCES IN WATER RESOURCES (2018)
Data-driven modelling of the FRC network for studying the fluid flow in the conduit system
Rostislav Savinkov et al.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2017)
Data mining and machine learning for identifying sweet spots in shale reservoirs
Pejman Tahmasebi et al.
EXPERT SYSTEMS WITH APPLICATIONS (2017)
Application of full set of two point correlation functions from a pair of 2D cut sections for 3D porous media reconstruction
Hossein Izadi et al.
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING (2017)
Estimation of soil permeability
Amr F. Elhakim
ALEXANDRIA ENGINEERING JOURNAL (2016)
Automatic classification of carbonate rocks permeability from 1H NMR relaxation data
Pablo Nascimento da Silva et al.
EXPERT SYSTEMS WITH APPLICATIONS (2015)
Particle-Size Analysis for the Pike 1 Project, McMurray Formation
Matt Abram et al.
JOURNAL OF CANADIAN PETROLEUM TECHNOLOGY (2014)
Relative permeability hysteresis and capillary trapping characteristics of supercritical CO2/brine systems: An experimental study at reservoir conditions
Morteza Akbarabadi et al.
ADVANCES IN WATER RESOURCES (2013)
Estimation of prediction error by using K-fold cross-validation
Tadayoshi Fushiki
STATISTICS AND COMPUTING (2011)
Application of an enhanced decision tree learning approach for prediction of petroleum production
Xiongmin Li et al.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2010)
Particle clogging in radial flow: Microscale mechanisms
Julio R. Valdes et al.
SPE JOURNAL (2006)
A saw-tooth genetic algorithm combining the effects of variable population size and reinitialization to enhance performance
VK Koumousis et al.
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2006)
Predicting the saturated hydraulic conductivity of sand and gravel using effective diameter and void ratio
RP Chapuis
CANADIAN GEOTECHNICAL JOURNAL (2004)
Goodbye, Hazen; Hello, Kozeny-Carman
WD Carrier
JOURNAL OF GEOTECHNICAL AND GEOENVIRONMENTAL ENGINEERING (2003)
An integrated neural-fuzzy-genetic-algorithm using hyper-surface membership functions to predict permeability in petroleum reservoirs
YT Huang et al.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2001)