A comprehensive model to history match and predict gas/water production from coal seams
Effect of Water Salinity on Coal Wettability during CO2 Sequestration in Coal Seams
Effects of formation-water salinity, formation pressure, gas composition, and gas-flow rate on carbon dioxide sequestration in coal formations
DOI: 10.2118/185949-pa
Effect of well shut-in after fracturing operations on near wellbore permeability
Stability Improvement of Carbon Dioxide Foam Using Nanoparticles and Viscoelastic Surfactants for Enhanced-Oil-Recovery Applications
DOI: 10.2118/191251-PA
A novel workflow for water flowback RTA analysis to rank the shale quality and estimate fracture geometry
Evaluation of Formation Damage of Oil-Based Drilling Fluids Weighted with Micronized Ilmenite or Micronized Barite
DOI: 10.2118/200482-PA
A flew Cationic Polymer System That Improves Acid Diversion in Heterogeneous Carbonate Reservoirs
A New Cationic Polymer System That Improves Acid Diversion in Heterogeneous Carbonate Reservoirs
DOI: 10.2118/194647-PA
Advancement of Hydraulic Fracture Diagnostics in Unconventional Formations
DOI: 10.1155/2021/4223858
Application of Various Machine Learning Techniques in Predicting Total Organic Carbon from Well Logs
DOI: 10.1155/2021/7390055
Retraction:Prediction of the Least Principal Stresses Using Drilling Data: A Machine Learning Application
DOI: 10.1155/2021/8865827
New insights into guar gum as environmentally friendly polymer for enhanced oil recovery in high-salinity and high-temperature sandstone reservoirs
Applications of Artificial Intelligence to Predict Oil Rate for High Gas-Oil Ratio and Water-Cut Wells
Experimental evaluation of a new nonaromatic nonionic surfactant for deep carbonate stimulation
DOI: 10.2118/193596-PA
Artificial intelligence models for real-time synthetic gamma-ray log generation using surface drilling data in Middle East Oil Field
Machine learning application to predict in-situ stresses from logging data
Prediction of oil rates using Machine Learning for high gas oil ratio and water cut reservoirs
Application of Machine Learning to Predict Estimated Ultimate Recovery for Multistage Hydraulically Fractured Wells in Niobrara Shale Formation
DOI: 10.1155/2022/7084514
Application of Machine Learning to Predict the Failure Parameters from Conventional Well Logs
Machine Learning Applications to Predict Surface Oil Rates for High Gas Oil Ratio Reservoirs
DOI: 10.1115/1.4052485
Prediction of cohesion and friction angle from well-logging data using decision tree and random forest
Real-time prediction of in-situ stresses while drilling using surface drilling parameters from gas reservoir
Prediction of Water Saturation in Tight Gas Sandstone Formation Using Artificial Intelligence
Application of various machine learning techniques in predicting coal wettability for CO2 sequestration purpose
Corrigendum to “Prediction of oil rates using Machine Learning for high gas-oil ratio and water cut reservoirs” [Flow Meas. Instrum. 82 (2021) 102065] (Flow Measurement and Instrumentation (2021) 82, (S0955598621001680), (10.1016/j.flowmeasinst.2021.102065))
Prediction of Surface Oil Rates for Volatile Oil and Gas Condensate Reservoirs Using Artificial Intelligence Techniques
DOI: 10.1115/1.4051298
Reviewer’s Recognition
DOI: 10.1115/1.4053502
New Empirical Correlations to Estimate the Least Principal Stresses Using Conventional Logging Data
A novel retarded HCl acid system for HPHT carbonate acidizing applications: Experimental study
DOI: 10.1002/cjce.24203
Empirical correlation for formation resistivity prediction using machine learning
New generalized correlations for oil rate predictions through wellhead chokes for high GOR reservoirs
Prediction of coal wettability using machine learning for the application of CO2 sequestration
Application of Various Machine Learning Techniques in Predicting Water Saturation in Tight Gas Sandstone Formation
DOI: 10.1115/1.4053248
Formation Resistivity Prediction Using Decision Tree and Random Forest
Real-Time GR logs Estimation While Drilling Using Surface Drilling Data; AI Application
Data-Driven Approach for Resistivity Prediction Using Artificial Intelligence
DOI: 10.1115/1.4053954
Real-time prediction of tensile and uniaxial compressive strength from artificial intelligence-based correlations
A hybrid data-driven solution to facilitate safe mud window prediction
Integrated workflow to investigate the fracture interference effect on shale well performance
Real-Time Prediction of Petrophysical Properties Using Machine Learning Based on Drilling Parameters
Uncertainty quantification for CO2 storage during intermittent CO2-EOR in oil reservoirs
Data-driven EUR for multistage hydraulically fractured wells in shale formation using different machine learning methods
Data-Driven Framework for Real-time Rheological Properties Prediction of Flat Rheology Synthetic Oil-Based Drilling Fluids
Estimating electrical resistivity from logging data for oil wells using machine learning
Effect of Crude Oil Properties on the Interfacial Tension of Crude Oil/CO2 Under HPHT Conditions
Machine learning framework for estimating CO2 adsorption on coalbed for carbon capture, utilization, and storage applications
Resistivity Log Prediction in Horizontal Low Formation Quality Well Using Data-Driven Robust Models
Influence of impurities on reactive transport of CO2 during geo-sequestration in saline aquifers
Prediction of shale wettability using different machine learning techniques for the application of CO2 sequestration
Photoelectric factor prediction using automated learning and uncertainty quantification
Revisiting the effect of oil type and pressure on optimum salinity of EOR surfactant formulation using phase behavior evaluation
The impact of CO2 saturated brine temperature on wormhole generation and rock geomechanical and petrophysical properties
Applications of Different Classification Machine Learning Techniques to Predict Formation Tops and Lithology While Drilling
The impact of CO2 saturated brine salinity on wormhole generation and rock geomechanical and petrophysical properties
Correction to: Probabilistic estimation of hydraulic fracture half-lengths: validating the Gaussian pressure-transient method with the traditional rate transient analysis-method (Wolfcamp case study) (Journal of Petroleum Exploration and Production Technology, (2023), 13, 12, (2475-2489), 10.1007/s13202-023-01680-9)
Data-driven models to predict shale wettability for CO2 sequestration applications
Estimation of rocks’ failure parameters from drilling data by using artificial neural network
Probabilistic estimation of hydraulic fracture half-lengths: validating the Gaussian pressure-transient method with the traditional rate transient analysis-method (Wolfcamp case study)
Estimation of fracture half-length with fast Gaussian pressure transient and RTA methods: Wolfcamp shale formation case study
Estimation of tensile and uniaxial compressive strength of carbonate rocks from well-logging data: artificial intelligence approach
Optimizing cluster spacing in multistage hydraulically fractured shale gas wells: balancing fracture interference and stress shadow impact
Impact of Pressure and Temperature on Foam Behavior for Enhanced Underbalanced Drilling Operations
Impact of Eco-Friendly Drilling Additives on Foaming Properties for Sustainable Underbalanced Foam Drilling Applications
Foam Stability Analysis at High pH and Saline Environments for Underbalanced Drilling Operations
Optimizing Recovery of Fracturing Fluid in Unconventional and Tight Gas Reservoirs Through Innovative Environmentally Friendly Flowback Additives
Impact of Pore Pressure on Wormhole Generation due to CO2-Saturated Brine Injection
Utilizing machine learning for flow zone indicators prediction and hydraulic flow unit classification
Automated Borehole Image Interpretation Using Computer Vision and Deep Learning
DOI: 10.2118/218881-pa
Impact of Pressure and Gas/Oil Ratios (GORs) on the Optimal Parameters for Surfactant Formulations in Chemical EOR: Experimental Study
Impact of rock mineralogy on reactive transport of CO2 during carbon sequestration in a saline aquifer
A Study of the Optimum Injection Rate of CO2-Saturated Brine in Limestone Aquifers and Its Impact on Rock Geomechanics
Leveraging machine learning for prediction and optimization of texture properties of sustainable activated carbon derived from waste materials
Applications of ionic liquids in improving CO2 miscibility in crude oil for enhanced oil recovery and CO2 sequestration applications
Prediction of Foam Half-Life Time Using Machine Learning Algorithms for Enhanced Oil Recovery and CO2 Sequestration
Advanced generalized machine learning models for predicting hydrogen–brine interfacial tension in underground hydrogen storage systems
Effects of Long-Term CO2 Storage on Carbonate Rock Stability
A study of the geomechanical and petrophysical impact of CO2-saturated brine injection in limestones with various low permeability
Prediction of Formation Permeability While Drilling: Machine Learning Applications
Prediction of Proppant Concentration Variations Between Different Perforation Clusters in a Hydraulically Fractured Stage
Numerical investigation of CO2 plume migration and trapping mechanisms in the sleipner field: Does the aquifer heterogeneity matter?
Learning based prediction of cuttings concentration for enhancing hole cleaning efficiency in eccentric and deviated wells
Improving CO2 Miscibility in Crude Oil Utilizing Viscosity Reducer: Experimental and Molecular Simulation Study
Machine learning predictive models of CO2 adsorption in sustainable waste-derived activated carbon
Sustainable foam stabilization using red mud-derived nanoparticles for enhanced oil recovery and CO2 sequestration
Impact of uncertainty in Utsira formation temperature and salinity on CO2 storage: A field-scale reactive transport simulation study
Experimental study of CO2 sequestration and H2 generation potential through mineral carbonation in Saudi red mud