Experimental and Molecular Dynamics Simulation to Investigate Oil Adsorption and Detachment from Sandstone/Quartz Surface by Low-Salinity Surfactant Brines.

In this study, we explore the impact of monovalent (NaCl) and divalent (CaCl) brines, coupled with sodium dodecyl sulfate (SDS) surfactant at varying low concentrations, on the detachment and displacement of oil from sandstone rock surfaces. Employing the sessile drop method and molecular dynamics simulations, we scrutinize the behavior of the brine solutions. Our findings reveal that both low salinity and low-salinity surfactant solutions induce a gradual shift in rock wettability toward a more water-wet state.

Predicting CO2 trapping in deep saline aquifers using optimized long short-term memory.

A sustainable environment by decreasing fossil fuel utilization and anthropogenic greenhouse gases is a globally main goal due to climate change and serious air pollution. Carbon dioxide (CO2) is a heat-trapping (greenhouse) that is released into the earth's atmosphere from natural processes, such as volcanic respiration and eruptions, as well as human activities, such as burning fossil fuels and deforestation. Due to this fact, underground carbon storage (UCS) is a promising technology to cut carbon emissions.

Evaluating the Applications of Dendritic Neuron Model with Metaheuristic Optimization Algorithms for Crude-Oil-Production Forecasting.

The forecasting and prediction of crude oil are necessary in enabling governments to compile their economic plans. Artificial neural networks (ANN) have been widely used in different forecasting and prediction applications, including in the oil industry. The dendritic neural regression (DNR) model is an ANNs that has showed promising performance in time-series prediction.

Advance artificial time series forecasting model for oil production using neuro fuzzy-based slime mould algorithm.

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 new improved version of the adaptive neuro-fuzzy inference system (ANFIS). This model is improved by using an optimization algorithm, the slime mould algorithm (SMA).