Modified aquila optimizer for forecasting oil production
MAA Al-qaness, AA Ewees, H Fan… - Geo-Spatial …, 2022 - Taylor & Francis
Oil production estimation plays a critical role in economic plans for local governments and
organizations. Therefore, many studies applied different Artificial Intelligence (AI) based …
organizations. Therefore, many studies applied different Artificial Intelligence (AI) based …
Optimized ANFIS model using Aquila Optimizer for oil production forecasting
Oil production forecasting is one of the essential processes for organizations and
governments to make necessary economic plans. This paper proposes a novel hybrid …
governments to make necessary economic plans. This paper proposes a novel hybrid …
Forecasting oil production using ensemble empirical model decomposition based Long Short-Term Memory neural network
W Liu, WD Liu, J Gu - Journal of Petroleum Science and Engineering, 2020 - Elsevier
Oil production forecasting is an important means of understanding and effectively
developing reservoirs. Reservoir numerical simulation is the most mature and effective …
developing reservoirs. Reservoir numerical simulation is the most mature and effective …
Attention-based LSTM network-assisted time series forecasting models for petroleum production
Petroleum production forecasting is the process of predicting fluid production from the wells
using historical data. In contrast to the traditional methods of analysing surface and …
using historical data. In contrast to the traditional methods of analysing surface and …
Advance artificial time series forecasting model for oil production using neuro fuzzy-based slime mould algorithm
AM AlRassas, MAA Al-Qaness, AA Ewees… - Journal of Petroleum …, 2022 - Springer
Oil production forecasting is an important task to manage petroleum reservoirs operations. In
this study, a developed time series forecasting model is proposed for oil production using a …
this study, a developed time series forecasting model is proposed for oil production using a …
Reinforcement learning based automated history matching for improved hydrocarbon production forecast
History matching aims to find a numerical reservoir model that can be used to predict the
reservoir performance. An engineer and model calibration (data inversion) method are …
reservoir performance. An engineer and model calibration (data inversion) method are …
Efficient deep-learning-based history matching for fluvial channel reservoirs
In history matching, the calibration of a prior reservoir model is computationally expensive
because many forward reservoir simulation runs are required. Multiple posterior (or …
because many forward reservoir simulation runs are required. Multiple posterior (or …
Inversion framework of reservoir parameters based on deep autoregressive surrogate and continual learning strategy
History matching is a crucial process that enables the calibration of uncertain parameters of
the numerical model to obtain an acceptable match between simulated and observed …
the numerical model to obtain an acceptable match between simulated and observed …
Reservoir simulation using smart proxy in SACROC unit-Case study
Q He, SD Mohaghegh, Z Liu - SPE Eastern Regional Meeting, 2016 - onepetro.org
In oil and gas industry, quick decisions on reservoir management have a huge impact on
business success. Reservoir simulation is used as a typical tool to predict field performance …
business success. Reservoir simulation is used as a typical tool to predict field performance …
Conditioning Model Ensembles to Various Observed Data (Field and Regional Level) by Applying Machine-Learning-Augmented Workflows to a Mature Field with 70 …
G Vanegas, J Nejedlik, P Neff… - SPE Reservoir Evaluation …, 2021 - onepetro.org
Forecasting production from hydrocarbon fields is challenging because of the large number
of uncertain model parameters and the multitude of observed data that are measured. The …
of uncertain model parameters and the multitude of observed data that are measured. The …