A5031632734- Hydrocarbon exploration and reservoir analysis
- Reservoir Engineering and Simulation Methods
- Geological formations and processes
- Hydraulic Fracturing and Reservoir Analysis
- Geochemistry and Geologic Mapping
- Energy Load and Power Forecasting
- Geochemistry and Elemental Analysis
- Hydrology and Sediment Transport Processes
- Oil and Gas Production Techniques
- Grey System Theory Applications
- Real-time simulation and control systems
- Market Dynamics and Volatility
- Geological Studies and Exploration
- Enhanced Oil Recovery Techniques
- Soil erosion and sediment transport
- Gas Dynamics and Kinetic Theory
- Computational Fluid Dynamics and Aerodynamics
- Geological and Geochemical Analysis
- Solar Radiation and Photovoltaics
Gombe State University
2019-2023
University of Aberdeen
2019-2022
King's College Hospital
2020
Summary Predicting oilfield performance is extremely challenging because of the large number variables that can influence and control it. Traditional methods such as decline-curve analysis have been commonly used but shown to significant shortcomings. In recent years, advances in machine learning (ML) provided a new suite tools tackle complex multivariant problems understanding oil-reservoir predicating final recovery factor. this study, application random-forest algorithm train three...
Numerous subsurface factors, including geology and fluid properties, can affect the connectivity of storage spaces in depleted reservoirs; hence, flow simulations become more complicated, predicting their deliverability remains challenging. This paper applies Machine Learning (ML) techniques to predict underground natural gas (UNGS) reservoirs. First, three baseline models were developed based on Support Vector Regression (SVR), Artificial Neural Network (ANN), Random Forest (RF) algorithms....
The methods used to estimate recovery factor change through the life cycle of a field. During appraisal, prior development when there are no production data, we typically rely on analog fields and empirical methods. Given absence perfect analog, these associated with wide range uncertainty. plateau, factors simulation dynamic modeling, whereas in later field life, once drops off decline curve analysis is also used. use different during stages leads uncertainty potential inconsistencies...
A number of geological and engineering parameters influence control the performance ultimate recovery from an oil reservoir. These are commonly interlinked relative importance each can be difficult to unravel. variables include such as depositional environment, which has long been considered a key factor influencing production characteristics fields. However, quantifying any single factor, is complicated by impact other (geological engineering) their numerous interdependencies. The main aim...
Abstract Basin‐wide analysis of an ancient distributive fluvial system (the upper Bima Formation) was carried out using field‐based observation/measurement and ‘photo‐realistic’ virtual outcrop data from 19 locations with good exposure the Formation in Northern Benue Trough. The goal this study is to provide assessment spatial distribution both vertical lateral trends within system. Vertical variations different facies formation were assessed quantitatively; includes proximal, medial distal...
Natural gas accounts for one of the most industriously marketed energy commodities with a meaningful impact on various financial activities around world. As direction price natural changes over time, accurate prediction is essential since this useful in decision making, commodity marketing, and sustainability planning. In paper, deep neural network (DNN) model monthly proposed. Deep networks are becoming standard tools that offer lot values to researchers solving different problems machine...