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Article
Towards Rapid Prediction of Nuclear Magnetic Resonance-Based Bimodal Porosities: An Example from the Middle Eastern Carbonate Reservoir
The pore structure in carbonate rocks is intricate and heterogeneous, containing intraparticle and interparticle porosities. Assessment of hydrocarbon recovery in carbonate reservoirs without considering the p...
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Article
The use of FreeStyle libre improves glycaemic control along with reducing diabetes burden and hospital admissions in a socially deprived Northwest English population
This retrospective study aimed to use mixed (qualitative and quantitative) methods to evaluate the role of FSL in reducing hospital admissions due to all causes, HbA1c, and reported hypoglycaemic episodes in p...
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Article
Open AccessMachine learning accelerated approach to infer nuclear magnetic resonance porosity for a middle eastern carbonate reservoir
Carbonate rocks present a complicated pore system owing to the existence of intra-particle and interparticle porosities. Therefore, characterization of carbonate rocks using petrophysical data is a challenging...
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Article
Morphologically Divergent Development of SnS Photocatalysts from Under-Utilized Ionic Precursors of SILAR Process
Successive ionic layer adsorption and reaction (SILAR) process has been diversely used for deposition of various metal chalcogenides. SnS is one of them. Owing to the under-utilization of ionic precursor used ...
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Article
Graphitic carbon nitride–manganese oxide nanoflowers as promising T1 magnetic resonance imaging contrast material
Hierarchical and flower-like nanostructures have attained great attention over the past decades due to their unique and intriguing properties. Considering the advantages of their particular structure and prope...
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Article
Machine Learning Approaches for Compressibility Factor Prediction at High- and Low-Pressure Ranges
An accurate value of compressibility factor, also called Z-factor or deviation factor, is essential for petroleum engineering, especially for reservoir simulation and material balance calculations. Standing an...
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Article
Predicting the efficiency of bare silica-based nano-fluid flooding in sandstone reservoirs for enhanced oil recovery through machine learning techniques using experimental data
Determining additional oil recovery from a silica nano-fluid enhanced oil recovery project is essential prior to its field scale application to prepare economic feasibility of the project. Measurement of oil r...
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Chapter and Conference Paper
Early Prediction of Complex Business Processes Using Association Rule Based Mining
Complex business processes are challenging and hard to analyse. The objective here is to enhance delivery of processes in terms of improving quality of service and customer satisfaction. Therefore, an automate...
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Article
Evolving strategies for shear wave velocity estimation: smart and ensemble modeling approach
Shear wave velocity has many applications in subsurface engineering such as reservoir engineering, rock mechanics, and seismic studies. To estimate the shear wave velocity in rocks, different methods such as l...
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Article
Open AccessA systematic review of data science and machine learning applications to the oil and gas industry
This study offered a detailed review of data sciences and machine learning (ML) roles in different petroleum engineering and geosciences segments such as petroleum exploration, reservoir characterization, oil ...
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Article
Pristine and Janus monolayers of vanadium dichalcogenides: potential materials for overall water splitting and solar energy conversion
Emerging two-dimensional (2D) transition metal dichalcogenides with admirable optoelectronic and electrochemical properties can be used in many practical applications like photocatalysis. In this study, throug...
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Chapter and Conference Paper
An Event-Level Clustering Framework for Process Mining Using Common Sequential Rules
Process mining techniques extract useful knowledge from event logs to analyse and improve the quality of process execution. However, size and complexity of the real-world event logs make it difficult to apply ...
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Article
Application of Artificial Intelligence to Estimate Oil Flow Rate in Gas-Lift Wells
Optimization and monitoring schemes for oil well and reservoir system require accurate estimation of production rate. Real-time monitoring is conducted typically using flow transmitters that contain their own ...
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Article
An intelligent data-driven model for Dean–Stark water saturation prediction in carbonate rocks
Carbonate rocks have a very complex pore system due to the presence of interparticle and intraparticle porosities. This makes the acquisition and analysis of the petrophysical data and the characterization of ...
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Article
Strategic separation of metal sulfides from residual wet-chemical precursors for synchronous production of pure water and nanostructured photocatalysts
Pseudo successive ionic layer adsorption and reaction (p-SILAR) is an emerging technique for deposition of quantum dots (QDs) on a variety of nanoparticles (NPs); however, it has a limitation of wastage of water-...
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Article
Open AccessReal-time prognosis of flowing bottom-hole pressure in a vertical well for a multiphase flow using computational intelligence techniques
An accurate prediction of well flowing bottom-hole pressure (FBHP) is highly needed in petroleum engineering applications such as for the field production optimization, cost per barrel of oil reduction, and qu...
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Chapter
Graphitic Carbon Nitride/Metal Oxides Nanocomposites and Their Applications in Engineering
In recent decades, an intriguing two-dimensional polymeric graphitic carbon nitride has drawn significant multidisciplinary research consideration due to its captivating properties. It is an intriguing earth a...
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Article
Core log integration: a hybrid intelligent data-driven solution to improve elastic parameter prediction
Current oil prices and global financial situations underline the need for the best engineering practices to recover remaining hydrocarbons. A good understanding of the elastic behavior of the reservoir rock is...
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Article
Open AccessIntelligent prediction of optimum separation parameters in the multistage crude oil production facilities
To obtain the high-quality crude oil from the surface processing plants, oil and gas separation plants parameters need to be optimized, by minimizing the intermediate components, flash from the crude oil durin...
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Article
An integrated approach for estimating static Young’s modulus using artificial intelligence tools
Elastic parameters play a key role in managing the drilling and production operations. Determination of the elastic parameters is very important to avoid the hazards associated with the drilling operations, we...
