Hydrocarbon production dynamics forecasting using machine learning: A state-of-the-art review
Accurate prediction of hydrocarbon production is crucial for the oil and gas industry.
However, the strong heterogeneity of underground formation, the inconsistency in oil–gas …
However, the strong heterogeneity of underground formation, the inconsistency in oil–gas …
A review on closed-loop field development and management
A Mirzaei-Paiaman, SMG Santos… - Journal of Petroleum …, 2021 - Elsevier
Closed-loop field development and management (CLFDM) is defined as a periodic update
of an uncertain field model using the latest measurements (data assimilation), followed by …
of an uncertain field model using the latest measurements (data assimilation), followed by …
[HTML][HTML] A hybrid machine learning approach based study of production forecasting and factors influencing the multiphase flow through surface chokes
Surface chokes are widely utilized equipment installed on wellheads to control hydrocarbon
flow rates. Several correlations have been suggested to model the multiphase flow of oil and …
flow rates. Several correlations have been suggested to model the multiphase flow of oil and …
Robust hybrid machine learning algorithms for gas flow rates prediction through wellhead chokes in gas condensate fields
ARB Abad, H Ghorbani, N Mohamadian, S Davoodi… - Fuel, 2022 - Elsevier
Condensate reservoirs are the most challenging hydrocarbon reservoirs in the world. The
behavior of condensate gas reservoirs regarding pressure and temperature variation is …
behavior of condensate gas reservoirs regarding pressure and temperature variation is …
Improved predictions of wellhead choke liquid critical-flow rates: modelling based on hybrid neural network training learning based optimization
Published relationships typically consider liquid critical-flow rate through wellhead chokes of
producing oil wells as functions of wellhead pressure, choke size and gas-liquid ratio. Such …
producing oil wells as functions of wellhead pressure, choke size and gas-liquid ratio. Such …
Prediction performance advantages of deep machine learning algorithms for two-phase flow rates through wellhead chokes
HS Barjouei, H Ghorbani, N Mohamadian… - Journal of Petroleum …, 2021 - Springer
Two-phase flow rate estimation of liquid and gas flow through wellhead chokes is essential
for determining and monitoring production performance from oil and gas reservoirs at …
for determining and monitoring production performance from oil and gas reservoirs at …
Impact of a new geological modelling method on the enhancement of the CO2 storage assessment of E sequence of Nam Vang field, offshore Vietnam
H Vo Thanh, Y Sugai, K Sasaki - Energy Sources, Part A: Recovery …, 2020 - Taylor & Francis
This study proposed a new geological modelling procedure for CO2 storage assessment in
offshore Vietnam by integrating artificial neural networks, co-kriging and object-based …
offshore Vietnam by integrating artificial neural networks, co-kriging and object-based …
Well performance classification and prediction: Deep learning and machine learning long term regression experiments on oil, gas, and water production
NM Ibrahim, AA Alharbi, TA Alzahrani, AM Abdulkarim… - Sensors, 2022 - mdpi.com
In the oil and gas industries, predicting and classifying oil and gas production for
hydrocarbon wells is difficult. Most oil and gas companies use reservoir simulation software …
hydrocarbon wells is difficult. Most oil and gas companies use reservoir simulation software …
Prediction of gas flow rates from gas condensate reservoirs through wellhead chokes using a firefly optimization algorithm
H Ghorbani, J Moghadasi, DA Wood - Journal of Natural Gas Science and …, 2017 - Elsevier
Numerous empirical correlation models for predicting wellhead flow rates have been
proposed. Here we apply a recently developed model based upon extensive data from the …
proposed. Here we apply a recently developed model based upon extensive data from the …
On application of machine learning method for history matching and forecasting of times series data from hydrocarbon recovery process using water flooding
M Pal - Petroleum Science and Technology, 2021 - Taylor & Francis
The focus of this paper is on application of advance data analytics and deep machine
learning methods for time series forecasting of injection/production data from subsurface …
learning methods for time series forecasting of injection/production data from subsurface …