[HTML][HTML] Applications of machine learning in subsurface reservoir simulation—a review—part ii
In recent years, Machine Learning (ML) has become a buzzword in the petroleum industry,
with numerous applications which guide engineers in better decision making. The most …
with numerous applications which guide engineers in better decision making. The most …
Technical and non-technical challenges of development of offshore petroleum reservoirs: Characterization and production
Offshore oil and gas reservoirs comprise a significant portion of the world's reserve base,
and their development is expected to help close a potential gap in the supply of …
and their development is expected to help close a potential gap in the supply of …
Forecasting PVT properties of crude oil systems based on support vector machines modeling scheme
PVT properties are very important in the reservoir engineering computations. There are
numerous approaches for predicting various PVT properties, namely, empirical correlations …
numerous approaches for predicting various PVT properties, namely, empirical correlations …
Prediction of oil PVT properties using neural networks
Reservoir fluid properties are very important in reservoir engineering computations such as
material balance calculations, well test analysis, reserve estimates, and numerical reservoir …
material balance calculations, well test analysis, reserve estimates, and numerical reservoir …
Using artificial neural networks to develop new PVT correlations for Saudi crude oils
Reservoir fluid properties data are very important in reservoir engineering computations
such as material balance calculations, well testing, reserve estimates, and numerical …
such as material balance calculations, well testing, reserve estimates, and numerical …
Comparative evaluation of back-propagation neural network learning algorithms and empirical correlations for prediction of oil PVT properties in Iran oilfields
This paper presents a new approach to improve the performance of neural network method
to PVT oil properties prediction. The true value of PVT properties which is determined based …
to PVT oil properties prediction. The true value of PVT properties which is determined based …
Artificial neural network models for identifying flow regimes and predicting liquid holdup in horizontal multiphase flow
ESA Osman - SPE production & facilities, 2004 - onepetro.org
This paper presents two artificial neural network (ANN) models to identify the flow regime
and calculate the liquid holdup in horizontal multiphase flow. These models are developed …
and calculate the liquid holdup in horizontal multiphase flow. These models are developed …
Support vector machines framework for predicting the PVT properties of crude-oil systems
PVT properties are very important in the reservoir engineering computations. There are
many empirical approaches for predicting various PVT properties using regression models …
many empirical approaches for predicting various PVT properties using regression models …
Toward an intelligent approach for determination of saturation pressure of crude oil
Bubble point pressure is a crucial PVT parameter of reservoir fluids, which has a significant
effect on oil field development strategies, reservoir evaluation and production calculations …
effect on oil field development strategies, reservoir evaluation and production calculations …
A fast algorithm for calculating isothermal phase behavior using machine learning
Compositional models are frequently used to describe fluids in petroleum reservoir
simulation, particularly for simulations of enhanced oil recovery. While compositional models …
simulation, particularly for simulations of enhanced oil recovery. While compositional models …