Machine learning and data-driven prediction of pore pressure from geophysical logs: A case study for the Mangahewa gas field, New Zealand

Integrated Sedimentological and Petrophysical Characterization for Clastic Reservoirs: A case study from New Zealand

(2021) Ahmed A. Radwan et al.   Journal of Natural Gas Science and Engineering

Modeling pore pressure and fracture pressure using integrated well logging, drilling based interpretations and reservoir data in the Giant El Morgan oil Field, Gulf of Suez, Egypt

(2021) Ahmed E. Radwan   JOURNAL OF AFRICAN EARTH SCIENCES

Effect of Depletion and Fluid Injection in the Mesozoic and Paleozoic Sandstone Reservoirs of the October Oil Field, Central Gulf of Suez Basin: Implications on Drilling, Production and Reservoir Stability

(2021) Ahmed A. Kassem et al.   Natural Resources Research

Predicting Formation Pore-Pressure from Well-Log Data with Hybrid Machine-Learning Optimization Algorithms

(2021) Mohammad Farsi et al.   Natural Resources Research

Present-day in-situ stresses in Southern Gulf of Suez, Egypt: Insights for stress rotation in an extensional rift basin

(2021) Ahmed E. Radwan et al.   JOURNAL OF STRUCTURAL GEOLOGY

Characterization of in-situ stresses and its implications for production and reservoir stability in the depleted El Morgan hydrocarbon field, Gulf of Suez rift basin, Egypt

(2021) Ahmed E. Radwan et al.   JOURNAL OF STRUCTURAL GEOLOGY

Seismic interpretation, reservoir characterization, gas origin and entrapment of the Miocene-Pliocene Mangaa C sandstone, Karewa Gas Field, North Taranaki Basin, New Zealand

(2021) Ahmed A. Radwan et al.   MARINE AND PETROLEUM GEOLOGY

Bakken stratigraphic and type well log learning network exploited to predict and data mine shear wave acoustic velocity

(2020) David A. Wood   JOURNAL OF APPLIED GEOPHYSICS

Machine learning for pore-water pressure time-series prediction: Application of recurrent neural networks

(2020) Xin Wei et al.   Geoscience Frontiers

A machine learning methodology for multivariate pore-pressure prediction

(2020) Hao Yu et al.   COMPUTERS & GEOSCIENCES

Stress Path Analysis for Characterization of In Situ Stress State and Effect of Reservoir Depletion on Present-Day Stress Magnitudes: Reservoir Geomechanical Modeling in the Gulf of Suez Rift Basin, Egypt

(2020) Ahmed Radwan et al.   Natural Resources Research

Geomechanical Modeling Using the Depth-of-Damage Approach to Achieve Successful Underbalanced Drilling in the Gulf of Suez Rift Basin

(2020) Wael K. Abdelghany et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

Random Forests and Cubist Algorithms for Predicting Shear Strengths of Rockfill Materials

(2019) Jian Zhou et al.   Applied Sciences-Basel

Comparative analysis of artificial intelligence techniques for formation pressure prediction while drilling

(2019) Abdulmalek Ahmed et al.   Arabian Journal of Geosciences

Pore and fracture pressure modeling using direct and indirect methods in Badri Field, Gulf of Suez, Egypt

(2019) A.E. Radwan et al.   JOURNAL OF AFRICAN EARTH SCIENCES

Artificial Neural Networks in the domain of reservoir characterization: A review from shallow to deep models

(2019) Pallabi Saikia et al.   COMPUTERS & GEOSCIENCES

Geopressure evaluation using integrated basin modelling, well-logging and reservoir data analysis in the northern part of the Badri oil field, Gulf of Suez, Egypt

(2019) A.E. Radwan et al.   JOURNAL OF AFRICAN EARTH SCIENCES

Evaluation of machine learning methods for formation lithology identification: A comparison of tuning processes and model performances

(2018) Yunxin Xie et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

Statistical modeling for real time pore pressure prediction from pre-drill analysis and well logs

(2018) Jacopo Paglia et al.   GEOPHYSICS

Reservoir geomechanical modeling: In-situ stress, pore pressure, and mud design

(2017) Ali Reza Najibi et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

Application of extreme learning machine and neural networks in total organic carbon content prediction in organic shale with wire line logs

(2016) Xian Shi et al.   Journal of Natural Gas Science and Engineering

Automated recognition of stratigraphic marker shales from geophysical logs in iron ore deposits

(2015) Katherine Silversides et al.   COMPUTERS & GEOSCIENCES

Support vector regression based determination of shear wave velocity

(2015) Parisa Bagheripour et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

Back Analysis of Geomechanical Parameters Using Hybrid Algorithm Based on Difference Evolution and Extreme Learning Machine

(2015) Zhan-ping Song et al.   MATHEMATICAL PROBLEMS IN ENGINEERING

Deep learning in neural networks: An overview

(2015) Jürgen Schmidhuber   NEURAL NETWORKS

Prediction breakthrough time of water coning in the fractured reservoirs by implementing low parameter support vector machine approach

(2013) Mohammad Ali Ahmadi et al.   FUEL

Evolving artificial neural network and imperialist competitive algorithm for prediction oil flow rate of the reservoir

(2012) Mohammad Ali Ahmadi et al.   APPLIED SOFT COMPUTING

Overpressure and mudrock compaction in the Lower Kutai Basin, Indonesia: A radical reappraisal

(2011) Agus M. Ramdhan et al.   AAPG BULLETIN

Pore pressure prediction from well logs: Methods, modifications, and new approaches

(2011) Jincai Zhang   EARTH-SCIENCE REVIEWS

Overpressure-generating mechanisms in the Peciko Field, Lower Kutai Basin, Indonesia

(2010) Agus M. Ramdhan et al.   PETROLEUM GEOSCIENCE