Real time prediction of drilling fluid rheological properties using Artificial Neural Networks visible mathematical model (white box)
Development of New Mathematical Model for Compressional and Shear Sonic Times from Wireline Log Data Using Artificial Intelligence Neural Networks (White Box)
New insights into the prediction of heterogeneous carbonate reservoir permeability from well logs using artificial intelligence network
A rigorous data-driven approach to predict Poisson's ratio of carbonate rocks using a functional network
New insights into porosity determination using artificial intelligence techniques for carbonate reservoirs
A new look into the prediction of static young’s modulus and unconfined compressive strength of carbonate using artificial intelligence tools
An experimental study to reduce the fracture pressure of high strength rocks using a novel thermochemical fracturing approach
DOI: 10.1155/2019/1904565
New Correlation for the Gas Deviation Factor for High-Temperature and High-Pressure Gas Reservoirs Using Neural Networks
An integrated approach for estimating static Young’s modulus using artificial intelligence tools
Core log integration: a hybrid intelligent data-driven solution to improve elastic parameter prediction
Intelligent prediction of optimum separation parameters in the multistage crude oil production facilities
Carbonate rocks resistivity determination using dual and triple porosity conductivity models
An experimental study to reduce the breakdown pressure of the unconventional carbonate rock by cyclic injection of thermochemical fluids
Real-time prognosis of flowing bottom-hole pressure in a vertical well for a multiphase flow using computational intelligence techniques
Effects of Nanoclay and Silica Flour on the Mechanical Properties of Class G Cement
Experimental Investigation of a Novel, Efficient, and Sustainable Hybrid Silicate System in Oil and Gas Well Cementing
Data-driven acid fracture conductivity correlations honoring different mineralogy and etching patterns
Development of New Rheological Models for Class G Cement with Nanoclay as an Additive Using Machine Learning Techniques
An intelligent data-driven model for Dean–Stark water saturation prediction in carbonate rocks
Improvement of petrophysical properties of tight sandstone and limestone reservoirs using thermochemical fluids
Data-Driven Approaches to Predict Thermal Maturity Indices of Organic Matter Using Artificial Neural Networks
Scale-prediction/inhibition design using machine-learning techniques and probabilistic approach
DOI: 10.2118/198646-PA
Thermochemical acid fracturing of tight and unconventional rocks: Experimental and modeling investigations
Application of Artificial Intelligence to Estimate Oil Flow Rate in Gas-Lift Wells
H2S Scavenging Capacity and Rheological Properties of Water-Based Drilling Muds
Novel gemini surfactant as a clay stabilizing additive in fracturing fluids for unconventional tight sandstones: Mechanism and performance
Polyoxyethylene quaternary ammonium gemini surfactants as a completion fluid additive to mitigate formation damage
DOI: 10.2118/201207-PA
Anhydrite (Calcium Sulfate) Mineral as a Novel Weighting Material in Drilling Fluids
DOI: 10.1115/1.4047762
Self-destructive barite filter cake in water-based and oil-based drilling fluids
Chelating Agents as Acid-Fracturing Fluids: Experimental and Modeling Studies
Novel Expandable Cement System for Prevention of Sustained Casing Pressure and Minimization of Lost Circulation
Productivity Enhancement in Multilayered Unconventional Rocks Using Thermochemicals
DOI: 10.1115/1.4047976
Relative contribution of wettability Alteration and interfacial tension reduction in EOR: A critical review
Okra as an environment-friendly fluid loss control additive for drilling fluids: Experimental & modeling studies
Kinetic and thermodynamic modelling of thermal decomposition of bitumen under high pressure enhanced with simulated annealing and artificial intelligence
DOI: 10.1002/cjce.24134