Cargando…

Dataset on modelling natural surfactant adsorption derived from non-edible seed oil (linseed oil) on sandstone reservoir rock

Surfactant flooding is adjudged one of the most promising chemicals enhanced oil recovery (cEOR) methods due to its high microscopic sweep efficiency. This surfactant shows high potential in mobilizing trapped residual oil (ganglia) through excellent lowering of the interfacial tension (IFT) between...

Descripción completa

Detalles Bibliográficos
Autores principales: Awelewa, Kehinde, Ogunkunle, Fred, Olabode, Oluwasanmi, Oni, Babalola, Abraham, Damilola, Adeleye, Samuel, Ifeanyi, Samuel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10522939/
https://www.ncbi.nlm.nih.gov/pubmed/37771710
http://dx.doi.org/10.1016/j.dib.2023.109578
_version_ 1785110458023280640
author Awelewa, Kehinde
Ogunkunle, Fred
Olabode, Oluwasanmi
Oni, Babalola
Abraham, Damilola
Adeleye, Samuel
Ifeanyi, Samuel
author_facet Awelewa, Kehinde
Ogunkunle, Fred
Olabode, Oluwasanmi
Oni, Babalola
Abraham, Damilola
Adeleye, Samuel
Ifeanyi, Samuel
author_sort Awelewa, Kehinde
collection PubMed
description Surfactant flooding is adjudged one of the most promising chemicals enhanced oil recovery (cEOR) methods due to its high microscopic sweep efficiency. This surfactant shows high potential in mobilizing trapped residual oil (ganglia) through excellent lowering of the interfacial tension (IFT) between the crude oil-aqueous interface to ultra-low values while favorably altering the wettability (oil-wet to water-wet). Surfactant adsorption is a critical factor that determines how successful this cEOR method will be as well as the project economics. Surfactant retention due to adsorption caused majorly by electrostatic forces of attraction between hydrophilic head, and the positive and negative charges of the adsorbent solid surface leading to insufficiency of the remaining surfactant concentration in the injected slug to achieve the supposed ultralow IFT needed for mobilization. This article describes the experimental data on the adsorption of a natural surfactant derived from linseed oil and the results from its adsorption isotherm modelling. This anionic surfactant (LSO-derived) has a CMC value of 2500 ppm, average fractional removal of 0.60 under a range of concentrations (500, 1000, 2000, 4000, 8000, and 12000 ppm), with the adsorption kinetics revealing that adsorption density rises as a function of time with increasing adsorbate concentrations. Five different classical adsorption isotherm models were explored- in the form three (Redlich–Peterson or R-P), two (Langmuir, Freundlich, Temkin), one (Linear-Henry) parameters models. Their characteristics adsorption parameters were calculated, with highest adsorption capacity value of 2.955mg/g obtained from the simulation using OriginPro 2021 Software. The analysis demonstrates that the R-P model provided the greatest fit as a hybrid model with the highest correlation coefficient value. The kinetic adsorption models Pseudo-First Order (PFO), Pseudo-Second Order (PSO), Pseudo-Nth Order (PNO), and Intra-Particle Diffusion (IPD), as well as their thermodynamic property model, were also examined in addition to static isotherm models. On average, using non-linear regression approach, PSO and PNO provided the best appropriate fit models under this hypothesis, with correlation values of the nth order ranging from 0.443 to 2.122 (excluding 5.847 the non-converged fit value). Prior to thermodynamic analysis, it was confirmed by the IPD with multi-linear graphical characteristics that intra-particle transport was not the only rate-limiting step in adsorption processes and proceeded spontaneously by the This model can be utilized to design a template for LSO surfactant-rock adsorption in chemical flooding schemes for EOR applications.
format Online
Article
Text
id pubmed-10522939
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-105229392023-09-28 Dataset on modelling natural surfactant adsorption derived from non-edible seed oil (linseed oil) on sandstone reservoir rock Awelewa, Kehinde Ogunkunle, Fred Olabode, Oluwasanmi Oni, Babalola Abraham, Damilola Adeleye, Samuel Ifeanyi, Samuel Data Brief Data Article Surfactant flooding is adjudged one of the most promising chemicals enhanced oil recovery (cEOR) methods due to its high microscopic sweep efficiency. This surfactant shows high potential in mobilizing trapped residual oil (ganglia) through excellent lowering of the interfacial tension (IFT) between the crude oil-aqueous interface to ultra-low values while favorably altering the wettability (oil-wet to water-wet). Surfactant adsorption is a critical factor that determines how successful this cEOR method will be as well as the project economics. Surfactant retention due to adsorption caused majorly by electrostatic forces of attraction between hydrophilic head, and the positive and negative charges of the adsorbent solid surface leading to insufficiency of the remaining surfactant concentration in the injected slug to achieve the supposed ultralow IFT needed for mobilization. This article describes the experimental data on the adsorption of a natural surfactant derived from linseed oil and the results from its adsorption isotherm modelling. This anionic surfactant (LSO-derived) has a CMC value of 2500 ppm, average fractional removal of 0.60 under a range of concentrations (500, 1000, 2000, 4000, 8000, and 12000 ppm), with the adsorption kinetics revealing that adsorption density rises as a function of time with increasing adsorbate concentrations. Five different classical adsorption isotherm models were explored- in the form three (Redlich–Peterson or R-P), two (Langmuir, Freundlich, Temkin), one (Linear-Henry) parameters models. Their characteristics adsorption parameters were calculated, with highest adsorption capacity value of 2.955mg/g obtained from the simulation using OriginPro 2021 Software. The analysis demonstrates that the R-P model provided the greatest fit as a hybrid model with the highest correlation coefficient value. The kinetic adsorption models Pseudo-First Order (PFO), Pseudo-Second Order (PSO), Pseudo-Nth Order (PNO), and Intra-Particle Diffusion (IPD), as well as their thermodynamic property model, were also examined in addition to static isotherm models. On average, using non-linear regression approach, PSO and PNO provided the best appropriate fit models under this hypothesis, with correlation values of the nth order ranging from 0.443 to 2.122 (excluding 5.847 the non-converged fit value). Prior to thermodynamic analysis, it was confirmed by the IPD with multi-linear graphical characteristics that intra-particle transport was not the only rate-limiting step in adsorption processes and proceeded spontaneously by the This model can be utilized to design a template for LSO surfactant-rock adsorption in chemical flooding schemes for EOR applications. Elsevier 2023-09-20 /pmc/articles/PMC10522939/ /pubmed/37771710 http://dx.doi.org/10.1016/j.dib.2023.109578 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Awelewa, Kehinde
Ogunkunle, Fred
Olabode, Oluwasanmi
Oni, Babalola
Abraham, Damilola
Adeleye, Samuel
Ifeanyi, Samuel
Dataset on modelling natural surfactant adsorption derived from non-edible seed oil (linseed oil) on sandstone reservoir rock
title Dataset on modelling natural surfactant adsorption derived from non-edible seed oil (linseed oil) on sandstone reservoir rock
title_full Dataset on modelling natural surfactant adsorption derived from non-edible seed oil (linseed oil) on sandstone reservoir rock
title_fullStr Dataset on modelling natural surfactant adsorption derived from non-edible seed oil (linseed oil) on sandstone reservoir rock
title_full_unstemmed Dataset on modelling natural surfactant adsorption derived from non-edible seed oil (linseed oil) on sandstone reservoir rock
title_short Dataset on modelling natural surfactant adsorption derived from non-edible seed oil (linseed oil) on sandstone reservoir rock
title_sort dataset on modelling natural surfactant adsorption derived from non-edible seed oil (linseed oil) on sandstone reservoir rock
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10522939/
https://www.ncbi.nlm.nih.gov/pubmed/37771710
http://dx.doi.org/10.1016/j.dib.2023.109578
work_keys_str_mv AT awelewakehinde datasetonmodellingnaturalsurfactantadsorptionderivedfromnonedibleseedoillinseedoilonsandstonereservoirrock
AT ogunkunlefred datasetonmodellingnaturalsurfactantadsorptionderivedfromnonedibleseedoillinseedoilonsandstonereservoirrock
AT olabodeoluwasanmi datasetonmodellingnaturalsurfactantadsorptionderivedfromnonedibleseedoillinseedoilonsandstonereservoirrock
AT onibabalola datasetonmodellingnaturalsurfactantadsorptionderivedfromnonedibleseedoillinseedoilonsandstonereservoirrock
AT abrahamdamilola datasetonmodellingnaturalsurfactantadsorptionderivedfromnonedibleseedoillinseedoilonsandstonereservoirrock
AT adeleyesamuel datasetonmodellingnaturalsurfactantadsorptionderivedfromnonedibleseedoillinseedoilonsandstonereservoirrock
AT ifeanyisamuel datasetonmodellingnaturalsurfactantadsorptionderivedfromnonedibleseedoillinseedoilonsandstonereservoirrock