An optimized XGBoost method for predicting reservoir porosity using petrophysical logs

Generating pseudo density log from drilling and logging-while-drilling data using extreme gradient boosting (XGBoost)

(2020) Ruizhi Zhong et al.   INTERNATIONAL JOURNAL OF COAL GEOLOGY

Using Machine Learning Methods To Identify Coal Pay Zones from Drilling and Logging-While-Drilling (LWD) Data

(2020) Ruizhi Zhong et al.   SPE JOURNAL

Prediction of methane adsorption in shale: Classical models and machine learning based models

(2020) Meng Meng et al.   FUEL

Predicting porosity, permeability, and tortuosity of porous media from images by deep learning

(2020) Krzysztof M. Graczyk et al.   Scientific Reports

Using the motor power and XGBoost to diagnose working states of a sucker rod pump

(2020) Lu Chen et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

Developing an XGBoost model to predict blast-induced peak particle velocity in an open-pit mine: a case study

(2019) Hoang Nguyen et al.   Acta Geophysica

Machine learning for predicting properties of porous media from 2d X-ray images

(2019) Naif Alqahtani et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

Domestic Violence Crisis Identification from Facebook Posts based on Deep Learning

(2018) Sudha Subramani et al.   IEEE Access

A new low-permeability reservoir core analysis method based on rate-transient analysis theory

(2018) Christopher R. Clarkson et al.   FUEL

Total porosity measurement in gas shales by the water immersion porosimetry (WIP) method

(2013) Utpalendu Kuila et al.   FUEL

Health assessment and life prediction of cutting tools based on support vector regression

(2013) T. Benkedjouh et al.   JOURNAL OF INTELLIGENT MANUFACTURING

Artificial neural network modeling and cluster analysis for organic facies and burial history estimation using well log data: A case study of the South Pars Gas Field, Persian Gulf, Iran

(2011) Bahram Alizadeh et al.   COMPUTERS & GEOSCIENCES