Publications and Projects
Enhancement of CO2 viscosity prediction using advanced intelligent methods: Application to carbon capture and storage
Geoenergy Science and Engineering
https://doi.org/10.1016/j.geoen.2023.211727
This study is the most comprehensive investigation of CO2 viscosity measurement to date, using eleven intelligent models; unlike most of the literature models, the density of CO2 is not used as an input parameter in the models; the best model's results are compared with the most recent experimentally derived correlations; it was shown that machine learning approaches not previously employed in studies outperform the model previously used in the literature; and instead of employing classic evolutionary approaches, two newly discovered optimization techniques (i.e., BAT and GOA) were applied. The performance of decision trees and random forest techniques is better than that of previously introduced best models for CO2 viscosity prediction, such as multi-layer perceptron, radial basis function, and adaptive neuro-fuzzy inference systems, according to the results of this paper, which rank decision trees and random forest algorithms as the first and second-best algorithms among eleven methodologies studied. The final result of the decision trees method outperformed a current and most updated correlation for CO2 viscosity prediction so far, as seen in various charts.
A clustering approach for EOS lumping — Using evolutionary-based metaheuristic optimization algorithms
Journal of petroleum science and engineering
https://doi.org/10.1016/j.petrol.2021.109149
It is always desirable to keep the number of components in compositional simulation low due to the high CPU time and storage space requirement; on the other hand, the model's accuracy in describing the phase behavior decreases with reducing the number of components. As a result, an optimal lumping approach is needed to group the components to attain high accuracy in the least amount of time. This paper's main objective is to find the best lumping scheme to maintain the split model's accuracy and reach an optimal lumped model in the least amount of time. In accordance with this purpose, five different evolutionary-based metaheuristic optimization algorithms known as genetic algorithm (GA), differential evolution (DE), harmony search (HS), imperialist competitive algorithm (ICA), and shuffled-frog leaping algorithm (SFLA) are incorporated into the objective function developed to cluster heavy fractions using the k-means algorithm. To find the optimal algorithm, the best cost of the objective function and the number of function evaluations (NFE) have been compared, and the final results were substantiated using flash calculation outputs, such as density, viscosity, phase diagram, and Wilson plot. The results indicate that the proposed algorithms are capable of finding the optimal lumped model with high accuracy for all reservoir samples tested in this study. This study also marked ICA as the best evolutionary-based optimization algorithm that can be used in clustering problems.
The Effect of Blending Polymeric and Phosphonate Scale Inhibitors on Fluid/Fluid and Rock/Fluid Interactions: A Comprehensive Experimental and Theoretical Study
SPE Journal
https://doi.org/10.2118/210583-PA
Using seawater or engineered water to inject into oil formations can cause inorganic scaling, such as calcium sulfate, barium sulfate, and strontium sulfate. These scales may clog pore throats and limit production. Scale inhibitor (SI) squeeze treatment reduces inorganic scaling and improves oil recovery. Chemical compounds called SIs suppress or delay mineral scaling. SIs fall into two categories, each with its own mechanism. Most polymeric inhibitors impede nucleation, whereas phosphonate SIs deform crystal formation. The oil and gas industry now uses a fixed mixture of these inhibitors to maximize all inhibition mechanisms. However, the impact of blended SIs on fluid/fluid and rock/fluid interactions has not been addressed.
The influence of seawater mixing ratio on calcium, strontium, and barium sulfate saturation indices is medium, low, and very low, respectively, but the effect on the amount of scale precipitation is very high, high, and low for the scales indicated. This adds to the fact that barium takes precedence in scale formation, and its presence may affect the other two scales, but calcium ions have barely any effect on barite formation. Moreover, the results show a positive synergistic effect of SIs blend on sulfate scale mitigation. However, this positive figure completely depends on the concentration of phosphonate SI for calcium and strontium sulfate, while the positive synergy exists at all concentrations of phosphonate SIs for barium sulfate. Moreover, SIs could lower the water/oil/rock contact angle by 10° on average and make it more water wet. Same enhanced results have been achieved for interfacial tension by adding SIs, reducing by 8 dynes/cm on average. It is worth noting that the interfacial tension and contact angle measurements are unaffected by the synergistic action of SIs mixing. The results of coreflooding experiments substantiate the effectiveness of SIs and show 8 and 45% permeability reduction for injection of seawater with and without SIs on two different core samples, respectively. For the first time in a sulfate scaling system, this work investigates the copresence of barite, celestite, and anhydrite against a wide range of blending SI concentrations. Based on the results, it is derived that the presence of all three sulfate scales undoubtedly affect the quantity of each scale’s precipitation and the efficacy of SIs.
I'm a paragraph. Click here to add your own text and edit me. It’s easy. Just click “Edit Text” or double click me to add your own content and make changes to the font. Feel free to drag and drop me anywhere you like on your page. I’m a great place for you to tell a story and let your users know a little more about you.
Algal Biorefinery: A potential Solution in Food-Energy-Water-Environment Nexus
Sustainable Energy & Fuels
https://doi.org/10.1039/D1SE01740C
Despite the great potential in wastewater treatment, CO2 bio-fixation, food, and bioenergy production, microalgae is not economically viable on a large commercial scale and, as a unifying solution to all sectors, has been less addressed. This study provides an updated review on microalgae to investigate the interaction between the Food-Energy-Water-Environment (FEWE) sectors and to understand how to manage their challenges effectively. Concerns about food, energy and water security, as well as challenges such as climate change, local agrochemical manufacturing, the threat of synthetic pigments, non-degradable plastic and surfactant, thermal pollution, and demand for livestock and aquafeed need a model that can respond the goals of these four sectors simultaneously. A biorefinery platform as a cost-effective and innovative solution for the FEWE Nexus has been proposed. To reduce costs, waste streams and effluent flue gas from plants should be fed into the cultivation media, making the biorefinery platform location sensitive. This review summarized the techniques to convert microalgae into different types of biofuels, heat, electricity, and other value-added products such as bioplastics, pigments, surfactants, cosmetics, and food products. Therefore, all the conditions in the biorefinery platform should be optimized to solve the interrelated challenges and present a sustainable framework alongside some approaches to improve efficiency.
Effect of engineered water and scale inhibitor concentration on the adsorption performance of gypsum inhibitors on multi-walled carbon nanotubes and crushed sandstone
Canadian Journal of Chemical Engineering
https://doi.org/10.1002/cjce.24914
​The study reveals that the copresence of calcium and magnesium ions improves the gypsum inhibition efficiency of scale
inhibitors (SIs) at low concentrations to a maximum of 79%. However, this effect
is reversed or neutral at higher SI concentrations. The study also shows that the
presence of monovalent ions reduces the adsorption of SIs by multi-walled carbon
nanotubes (MWCNTs). Removing sodium ions from seawater while leaving calcium and magnesium ions intact increases MWCNTs’ adsorption capability to
93%. This is because monovalent cations attach to the adsorbent surface and block
the active sites, whereas divalent cations act as a bridge between MWCNT and
SIs. The study establishes that the behaviour of SIs regarding adsorption on
MWCNT and crushed sandstone depends on various factors, including molecule
size, calcium toleration of the SIs, point of zero charge, and solution
pH. Understanding these factors can improve the effectiveness of SIs, reduce
chemical costs, and prolong the life of oil wells.
