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Study of gas/condensate reservoir exploitation using neurosimulation
Luis F. Ayala
, Turgay Ertekin
, Michael Adewumi
John and Willie Leone Department of Energy & Mineral Engineering (EME)
Institute for Computational and Data Sciences (ICDS)
Research output
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Contribution to journal
›
Article
›
peer-review
9
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Scopus citations
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Keyphrases
Gas Condensate Reservoir
100%
Neurosimulation
100%
Compositional Simulation
50%
Simulation Study
25%
Neural Network
25%
Hydrocarbon Recovery
25%
Optimization Tool
12%
Gas Reservoir
12%
Computationally Intensive
12%
Phase Behavior
12%
Fluid Composition
12%
Computation Overhead
12%
Desired Outcomes
12%
Oil Reservoir
12%
Software Requirements
12%
Screening Tool
12%
Expert System
12%
Soft Computing
12%
Accurate Modeling
12%
Reservoir Characteristics
12%
Dry Gas
12%
Hardware Requirements
12%
Output Response
12%
Fluid Characteristics
12%
Optimum Production
12%
Wet Gas
12%
Hard Computing
12%
Training Phase
12%
Fluid Flow Characteristics
12%
Minimum Loss
12%
Computational Software
12%
Material Science
Fluid Flow
100%
Wet Gas
100%
Phase Composition
100%
Engineering
Condensate Gas
100%
Input Parameter
25%
Artificial Neural Network
25%
Parametric Study
12%
Gas Reservoir
12%
Reservoir Condition
12%
Oil Reservoir
12%
Dry Gas
12%
Output Response
12%
Wet Gas
12%
Fluid Flow Characteristic
12%
Phase Composition
12%
Earth and Planetary Sciences
Gas Condensate
100%
Compositional Simulation
50%
Artificial Neural Network
25%
Fluid Composition
12%
Fluid Flow
12%
Flow Characteristics
12%
Hydrocarbon Reserve
12%
Chemical Engineering
Gas Condensate
100%
Neural Network
25%
Fluid Flow
12%