Machine-learning-based prediction of oil recovery factor for experimental CO2-Foam chemical EOR: Implications for carbon utilization projects
Enhanced oil recovery (EOR) using CO 2 injection is promising with economic and
environmental benefits as an active climate-change mitigation approach. Nevertheless, the …
environmental benefits as an active climate-change mitigation approach. Nevertheless, the …
A review of wettability alteration by spontaneous imbibition using low-salinity water in naturally fractured reservoirs
Analysis of fluid flow in naturally fractured reservoirs (NFRs), as a highly heterogeneous and
complex system, requires a detailed study of the fracture-matrix interactions. The main …
complex system, requires a detailed study of the fracture-matrix interactions. The main …
Machine learning-aided prediction of nitrogen heterocycles in bio-oil from the pyrolysis of biomass
Nitrogen heterocyclic compounds in bio-oil (NH_Oil) made from biomass pyrolysis such as
pyrroles, pyrazines, and indoles, have a relative content of 0–30%. NH_Oil is a NO x …
pyrroles, pyrazines, and indoles, have a relative content of 0–30%. NH_Oil is a NO x …
[HTML][HTML] A robust approach to pore pressure prediction applying petrophysical log data aided by machine learning techniques
Determination of pore pressure (PP), a key reservoir parameter that is beneficial for
evaluating geomechanical parameters of the reservoir, is so important in oil and gas fields …
evaluating geomechanical parameters of the reservoir, is so important in oil and gas fields …
Artificial neural network, support vector machine, decision tree, random forest, and committee machine intelligent system help to improve performance prediction of …
A large body of experimental research supports the effectiveness of Low Salinity Water
Injection (LSWI) for enhanced oil recovery from carbonate reservoirs in laboratory scale …
Injection (LSWI) for enhanced oil recovery from carbonate reservoirs in laboratory scale …
Utilizing machine learning for flow zone indicators prediction and hydraulic flow unit classification
Reservoir characterization, essential for understanding subsurface heterogeneity, often
faces challenges due to scale-dependent variations. This study addresses this issue by …
faces challenges due to scale-dependent variations. This study addresses this issue by …
Evaluation of Reservoir Porosity and Permeability from Well Log Data Based on an Ensemble Approach: A Comprehensive Study Incorporating Experimental …
EE Nyakilla, S Guanhua, H Hongliang… - Natural Resources …, 2024 - Springer
Permeability and porosity are key parameters in reservoir characterization for understanding
hydrocarbon flow behavior. While traditional laboratory core analysis is time-consuming …
hydrocarbon flow behavior. While traditional laboratory core analysis is time-consuming …
Comparison of the performance of machine learning techniques in the prediction of employee
Human Resources' purpose is to assign the best people to the right job at the right time, train
and qualify them, and provide evaluation methods to track their performance and safeguard …
and qualify them, and provide evaluation methods to track their performance and safeguard …
Data-driven connectionist models for performance prediction of low salinity waterflooding in sandstone reservoirs
Low salinity waterflooding (LSWF) and its variants also known as smart water or ion tuned
water injection have emerged as promising enhanced oil recovery (EOR) methods. LSWF is …
water injection have emerged as promising enhanced oil recovery (EOR) methods. LSWF is …
Weather condition-based hybrid models for multiple air pollutants forecasting and minimisation
With the deterioration of air quality in recent years, the establishment of accurate and
efficient forecasting models for pollutants has become the top priority. Due to the imperfect …
efficient forecasting models for pollutants has become the top priority. Due to the imperfect …