... and materials united states government complex reservoir upstream oil & gas well control drilling fluid management & disposal geological subdiscipline abdelaal ecd data reservoir characterization drilling data abdulraheem accuracy equivalent circulation density prediction elkatatny...

... rock reservoir characterization silicate application prediction brine system abdulraheem mahmoud wettability iglauer ffnn model colloid interface sci tariq interaction al-yaseri ARMA 23 755 Machine Learning Modeling of Saudi Arabian basalt/CO2/brine Wettability Prediction: Implications...

... government geological subdiscipline upstream oil & gas asia government breakdown pressure machine learning sedimentary rock abdulraheem prediction tensile strength enhancing breakdown pressure prediction tariq dataset prediction model geology neural network rock type coefficient...

... and reservoir productivity enhancement (Tariq et al., 2017). In contrast, Abdulraheem et al. (2009) reported that wrong estimation of rock mechanical properties could result in incorrect field development planning and loss of revenue. Obtaining rock samples at many different depth and carrying out laboratory...

... stability analysis, effective mud program and reduced overall drilling time and cost (Tingay et al., 2009; Zoback, 2007). artificial intelligence neural network machine learning abdulraheem upstream oil & gas elkatatny journal petroleum engineer dataset gradient abdelaal artificial...

... drilling fluid formulation drilling fluid property elkatatny abdulraheem hyperparameter accuracy artificial intelligence machine learning abdelaal baker hughe decision tree learning drilling fluid management & disposal drilling fluid chemistry rheology drilling drilling parameter mfv...

... abdulraheem exhibition petroleum science arabia reservoir geomechanics structural geology drilling parameter artificial neural network dataset ahmed mahmoud ARMA 21 1668 Bulk Density Prediction While Drilling Complex Lithology Using Functional Networks Model Ahmed, A.H., Elkatatny, S., Gamal, H...

... logs (Barree et al., 2009). reservoir characterization structural geology machine learning neural network artificial intelligence artificial neural networks-based equation empirical equation estimation mahmoud dyn elkatatny ann model dataset abdulraheem correlation empirical...

... time and cost (Tingay et al., 2009; Zoback, 2007). artificial intelligence fuzzy logic abdulraheem machine learning neural network pore pressure gradient transfer function reservoir characterization upstream oil & gas elkatatny formation pressure prediction prediction petroleum...

... drilling fluid management & disposal drilling operation upstream oil & gas accuracy king fahd university elkatatny exhibition neural network petroleum & mineral drilling parameter machine learning fuzzy logic abdulraheem correlation ecd artificial neural network model saudi...

...ARMA 21 1914 Generating the Rock Strength Profile While Drilling Complex Lithologies in real-time by Employing Artificial Neural Networks Gamal, H. King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia; Box: 5049 Gowida, A., Elkatatny, S., Abdulraheem, A., and Haidary, S. King...

...). Some of the correlations based on the well log data are but not limited to (Abdulraheem et al., 2007; Al-Shuhail et al., 2013; Anifowose et al., 2014; F. Anifowose et al., 2015; F. A. Anifowose et al., 2015; Babadagli and Al-Salmi, 2002; Barman et al., 1998; Basbug and Karpyn, 2007; Cozzi et al., 2007...

... learning well logging Artificial Intelligence Reservoir Characterization neural network abdulraheem transit time wave velocity prediction correlation gamma ray log analysis Upstream Oil & Gas empirical correlation compressional resistivity wave transit time sonic wave transit time...

..., M. A., Abdulraheem, A., Al-Shehri, D.A. KFUPM, Dharahan, Saudi Arabia Copyright 2018 ARMA, American Rock Mechanics Association This paper was prepared for presentation at the 52nd US Rock Mechanics / Geomechanics Symposium held in Seattle, Washington, USA, 17 20 June 2018. This paper was selected...

... correlation is very robust and accurate. Therefore, the developed correlation can serve as handy tool to help geo-mechanical engineers in order to determine the UCS. machine learning well logging abdulraheem log data ANN model Reservoir Characterization reservoir geomechanics neural network...