A Machine Learning Approach for Gas Kick Identification

An intelligent model for early kick detection based on cost-sensitive learning

(2022) Peng Chi et al.   PROCESS SAFETY AND ENVIRONMENTAL PROTECTION

Early monitoring of gas kick in deepwater drilling based on ensemble learning method: A case study at South China Sea

(2022) Zizhen Wang et al.   PROCESS SAFETY AND ENVIRONMENTAL PROTECTION

Practical Machine-Learning Applications in Well-Drilling Operations

(2021) T. A. Olukoga et al.   SPE DRILLING & COMPLETION

Experimental Study of Cuttings Transport with Non-Newtonian Fluid in an Inclined Well Using Visualization and Electrical Resistance Tomography Techniques

(2021) Mohammad Mojammel Huque et al.   SPE DRILLING & COMPLETION

Machine Learning for Deepwater Drilling: Gas-Kick-Alarm Classification Using Pilot-Scale Rig Data with Combined Surface-Riser-Downhole Monitoring

(2021) Qishuai Yin et al.   SPE JOURNAL

Downhole quantitative evaluation of gas kick during deepwater drilling with deep learning using pilot-scale rig data

(2021) Qishuai Yin et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

A deep learning model for process fault prognosis

(2021) Rajeevan Arunthavanathan et al.   PROCESS SAFETY AND ENVIRONMENTAL PROTECTION

Application of the electric resistance tomographic technique to investigate its efficacy in cuttings transport in horizontal drilling scenarios

(2021) Muhammad Saad Khan et al.   Journal of Natural Gas Science and Engineering

Early Gas Kick Detection in Vertical Wells via Transient Multiphase Flow Modelling: A Review

(2020) Ahmad K. Sleiti et al.   Journal of Natural Gas Science and Engineering

Two-phase flow regime identification based on the liquid-phase velocity information and machine learning

(2020) Yongchao Zhang et al.   EXPERIMENTS IN FLUIDS

Machine learning workflow to predict multi-target subsurface signals for the exploration of hydrocarbon and water

(2020) Oghenekaro Osogba et al.   FUEL

Supervised data-driven approach to early kick detection during drilling operation

(2020) Somadina Muojeke et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

A new methodology for kick detection during petroleum drilling using long short-term memory recurrent neural network

(2020) Augustine Osarogiagbon et al.   PROCESS SAFETY AND ENVIRONMENTAL PROTECTION

Downhole working conditions analysis and drilling complications detection method based on deep learning

(2020) Chao Wang et al.   Journal of Natural Gas Science and Engineering

Measuring solid cuttings transport in Newtonian fluid across horizontal annulus using electrical resistance tomography (ERT)

(2020) M. Fahed Qureshi et al.   FLOW MEASUREMENT AND INSTRUMENTATION

Application of Artificial Intelligence-based predictive methods in Ionic liquid studies: A review

(2020) Falola Yusuf et al.   FLUID PHASE EQUILIBRIA

Identification of Gas-Liquid Flow Regimes Using a Non-intrusive Doppler Ultrasonic Sensor and Virtual Flow Regime Maps

(2019) Somtochukwu Godfrey Nnabuife et al.   FLOW MEASUREMENT AND INSTRUMENTATION

Data-driven approach augmented in simulation for robust fault prognosis

(2019) M.A. Djeziri et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Flow regime identification for air valves failure evaluation in water pipelines using pressure data

(2019) Haixing Liu et al.   WATER RESEARCH

Study of identification of global flow regime in a long pipeline transportation system

(2019) Qiang Xu et al.   POWDER TECHNOLOGY

Two stage forecast engine with feature selection technique and improved meta-heuristic algorithm for electricity load forecasting

(2018) Noradin Ghadimi et al.   ENERGY

Experimental investigation of multiphase flow behavior in drilling annuli using high speed visualization technique

(2018) Alap Ali Zahid et al.   Frontiers in Energy

A nonlinear support vector machine-based feature selection approach for fault detection and diagnosis: Application to the Tennessee Eastman process

(2018) Melis Onel et al.   AICHE JOURNAL

Intelligent identification of steam jet condensation regime in water pipe flow system by wavelet multiresolution analysis of pressure oscillation and artificial neural network

(2018) Qiang Xu et al.   APPLIED THERMAL ENGINEERING

State of the art and taxonomy of prognostics approaches, trends of prognostics applications and open issues towards maturity at different technology readiness levels

(2017) Kamran Javed et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Real time risk analysis of kick detection: Testing and validation

(2017) Rakibul Islam et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Monitoring of down-hole parameters for early kick detection

(2016) Ayesha Arjumand Nayeem et al.   JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES

Identification of flow regime in vertical upward air–water pipe flow using differential pressure signals and elastic maps

(2014) H. Shaban et al.   INTERNATIONAL JOURNAL OF MULTIPHASE FLOW

An improved method for applying the lockhart-martinelli correlation to three-phase gas-liquid-solid horizontal pipeline flows

(2013) M.A. Rahman et al.   CANADIAN JOURNAL OF CHEMICAL ENGINEERING

A new method for the study of two-phase flow patterns based on the chaotic characteristic method of image fields

(2012) Yunlong Zhou et al.   FLOW MEASUREMENT AND INSTRUMENTATION

Flow Regime Identification Under Adiabatic Upward Two-Phase Flow in a Vertical Rod Bundle Geometry

(2011) Sidharth Paranjape et al.   JOURNAL OF FLUIDS ENGINEERING-TRANSACTIONS OF THE ASME

Flow regime development analysis in adiabatic upward two-phase flow in a vertical annulus

(2010) J. Enrique Julia et al.   INTERNATIONAL JOURNAL OF HEAT AND FLUID FLOW

Identification Method of Gas-Liquid Two-phase Flow Regime Based on Image Multi-feature Fusion and Support Vector Machine

(2009) Yunlong ZHOU et al.   CHINESE JOURNAL OF CHEMICAL ENGINEERING

Upward vertical two-phase flow local flow regime identification using neural network techniques

(2007) J. Enrique Juliá et al.   NUCLEAR ENGINEERING AND DESIGN