2022
DOI: 10.1016/j.petrol.2021.109201
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Rheological study of CO2 foamed chelating stimulation fluids under harsh reservoir conditions

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Cited by 11 publications
(7 citation statements)
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“…Under the high salinity and high temperature conditions that are observed in most reservoirs, most polymers and surfactants break down . Chelating agents are introduced as unconventional fluids to address these breakdown issues because of their distinct properties, low costs, and eco-friendliness. , During chelation, ions and molecules are chemically bonded to metal ions. To form a chelating agent, two or more different coordinate bonds must be developed between a central atom and a ligand with multiple bonds.…”
Section: Chelating Agents Effects On Seawater Fluidmentioning
confidence: 99%
See 3 more Smart Citations
“…Under the high salinity and high temperature conditions that are observed in most reservoirs, most polymers and surfactants break down . Chelating agents are introduced as unconventional fluids to address these breakdown issues because of their distinct properties, low costs, and eco-friendliness. , During chelation, ions and molecules are chemically bonded to metal ions. To form a chelating agent, two or more different coordinate bonds must be developed between a central atom and a ligand with multiple bonds.…”
Section: Chelating Agents Effects On Seawater Fluidmentioning
confidence: 99%
“…GLDA is environmentally friendly and more resistant to high temperatures and salinity. ,, Additionally, it has the ability to increase the viscosity of the stimulation fluid. An environmentally friendly stimulation fluid has been developed by adding GLDA to polymeric gel solutions .…”
Section: Chelating Agents Effects On Seawater Fluidmentioning
confidence: 99%
See 2 more Smart Citations
“…Li et al (2022) investigated the rheology properties of thickened liquid CO 2 by measuring the viscosity of thickened liquid CO 2 in different physical parameters of this prepared thickener and explained the causes of the rheological changes [ 29 ]. Kadafur et al (2022) investigated the rheology of a CO 2 foamed chelating agent, L-glutamic acid-N, N-diacetic acid (GLDA), which was conducted at 100 C, 1000 psi, 3.5 pH level, and various water salinities, resembling harsh reservoir conditions [ 30 ]. Tariq et al (2022) established a data pool, which was analyzed using four machine learning techniques: Artificial Neural Network (ANN), Decision Trees (DT), Random Forest Regressor (RFR), and K-Nearest Neighbor (KNN), and it provides a simplified ANN-based model which can be used on the fly to predict the effective bulk foam viscosity in both laboratory and field conditions [ 31 ].…”
Section: Introductionmentioning
confidence: 99%