Добірка наукової літератури з теми "Adsorption Process Modelling"

Removal of organics in water or wastewater treatment systems is often described mathematically in the form of Langmuir and Freundlich adsorption isotherms. Using these equations, it is convenient to model, e.g., the removal of organic matter in the adsorption process on an activated carbon bed. In chemical treatment processes, organic substances are frequently removed from the water or wastewater under treatment via an adsorption on the precipitation products. In this paper presented is a generalized model of the equation of a multilayer adsorption isotherm, which describes TOC removal from a solution during chemical treatment in an alkaline medium. The model also includes the nonremovable concentration of organics.

Adsorption is a commonly used procedure in environmental applications in the chemical industry. In comparison proposed mathematical models to explain batch adsorption as it relates to isotherms and kinetics, fixed-bed or column adsorption has a dearth of models to describe and forecast. While the latter is the most common alternative in practice. The current analysis begins with a brief overview of basic concepts and mathematical models used to characterize batch adsorption's mass transfer and isotherm behavior, which dominates Natural adsorption behavior in columns. Following that, the commonly used models for predicting the breakthrough curve, such as the Clark, Thomas, Adams-Bohart, and Yoon-Nelson models, are fleetingly discussed from a mathematical and process perspective. Their fundamental characteristics are also discussed, including their benefits and intrinsic flaws. This analysis can aid those who are involved in adsorption in columns in selecting or developing a correct and realistic model for their research and applications.

Process chromatography modelling for process development, design, and optimization as well as process control has been under development for decades. Still, the discussion of scientific potential and industrial applications needs is open to innovation. The discussion of next-generation modelling approaches starting from Langmuirian to steric mass action and multilayer or thermodynamic consistent real and ideal adsorption theory or colloidal particle adsorption approaches is continued.

The oligodynamic property is a lethal effect which some atoms exert over bacteria, fungi and other microorganisms. The oligodynamic property can be promoted by glass microparticles doped by zinc ionic specimens utilizing the ionic exchange processes. This study is aimed at modelling the behavior of adsorption mechanisms of the zinc ions on glass microparticles absorbent, with potential use as antimicrobial material. Aqueous solutions of zinc nitrate were used as the ionic supplying of zinc ions. The amount of zinc adsorbed on the glass was determined by spectroscopy of atomic absorption and with a mass balance analysis for each adsorption conditions. The experimental data were modeled by three Eq.s employed in adsorption kinetics studies: pseudo first order, pseudo second order and Elovich Eq.. The pseudo second order data model presented the better adjust condition. A sample of zinc glass microparticles, prepared at the finest conditions established by the kinetic model of pseudo second order, was submitted to microbiological analysis: agar diffusion test with Pseudomonas aeruginosa and Staphylococcus aureus and with Candida albicans. The glass doped with ionic zinc inhibited the growth of microorganisms in every conducted analysis.

The nitrogen production and supply processes are continuously improving in terms of efficiency, competitiveness, and cost-effectiveness, encouraged by the growing use and consequent demand in chemical industries. In this work, the PSA pilot plant for nitrogen production located at the Münster University of Applied Sciences, was analysed. The analysis was carried out experimentally in different operating conditions, in order to determine and then improve the performances of the production process. Subsequently, a mathematical model was developed in the ASPEN Adsorption software for the description of the mass transfer phenomena that occur inside the columns packed with the adsorbent material (CMS), which model was formulated by applying various hypotheses and considerations. Material and energy balances were involved, in order to generate the correct set of partial differential equations within the software. A complete representation of pressure drops and thermal effects is the result of this work. The transport phenomena and therefore the component kinetics have been assessed, but a more in-depth analysis is required and indicated at the end of this paper.

Simulated moving bed chromatography process (SMBCP) is the technical realisation of a countercurrent adsorption process through the cyclic port switching. SMB technology reduces the cost of packing material with high loading capacity and provides high purity and high recovery in a very short time. Major commodity applications have been found in the petroleum, food, biotechnology, pharmaceutical and fine chemical industries. The industrial applications bring an emergent demand to improve the SMBCP operation for higher product quality, productivity, efficiency and robustness. However, for this particular process, we encounter several challenges. Firstly, the interplay of the effects of strong nonlinearities, competition of solutes, mass transfer resistance and fluid dynamic dispersion produces steep concentration fronts. Mathematical model accounted for this particular property constitutes a serious difficulty for the solution procedure. Secondly, a dynamic SMB model consists of a set of partial differential, ordinary differential and algebraic equations, which are highly coupled. The large size is a problem due to its intensive computation when on-line optimisation and real-time control are necessary. Thirdly, the SMB unit operation exhibits complex dynamics. Process metrics for design and operation can be determined only when a cyclic steady state is reached after a certain number of switching. Achieving this steady state by solving the PDE models cycle after cycle involves expensive calculation. Studies have been carried out to solve these problems through process analysis, investigation on spatial discretisation techniques, and development of an accelerated integration scheme.Through a systematic study on the advances of SMB modelling, design and control, a set of functionally equivalent models for SMBCP are identified and summarized for their practical applications. The limitations of the existing modelling techniques in industrial applications are also identified. Furthermore, structural analysis of the existing models is conducted for a better understanding of the functionality and suitability of each model. Suggestions are given on how to choose an appropriate model with sufficient accuracy while keeping the computational demand reasonably low for real time control.Effort is made on to the systematic investigation of different numerical methods for the solution of PDEs to circumvent the steep gradients encountered in chromatographic separation. Comprehensive studies are conducted on a single column chromatographic process represented by a transport-dispersive-equilibrium linear model. Numerical solutions from the upwind-1 finite difference, wavelet-collocation, and high resolution methods are evaluated by quantitative comparisons with the analytical solution for a range of Peclet numbers. It reveals that for a PDE system with a low Peclet number, all existing numerical methods work well, but the upwind finite difference method consumes the most time for the same degree of accuracy of the numerical solution. The high resolution method provides an accurate numerical solution for a PDE system with a medium Peclet number. The wavelet collocation method is capable of catching up steep changes in the solution, and thus can be used for solving PDE models with high singularity.The advantages and disadvantages of the wavelet based approaches are further investigated through several case studies on real SMBCP system. A glucose-fructose separation process is firstly chosen with its relatively simple isotherm representations. Simulations are conducted using both wavelet collocation and upwind finite difference methods. For more complicated applications, an enantiomers separation process is selected. As the PDEs model exhibit a certain degree of singularity, wavelet collocation and high resolution methods are adopted for spatial discretisation. It is revealed that both the wavelet based approaches and high resolution methods are good candidates in terms of computation demand and prediction accuracy on the steep front. This is the first time that these two frontier numerical methods are used for such a complex SMB system models and our results are encouraging for the development of model-based online control scheme.In developing a new scheme to rapidly obtain the solution at steady state for any arbitrary initial condition, the concept of Quasi-Envelope (QE) is adopted under the consideration that a SMBCP can be treated as a pseudo-oscillatory process because of a large number of continuous switching. The scheme allows larger steps to be taken to predict the slow change of starting state within each switching. Combined with previously developed wavelet-based technique, this method is successfully applied to the simulation of a SMB sugar separation process. Investigations are also carried out on the location of proper starting point for the algorithm and on the effect of changing stepsize to the convergence of iteration method. It is found that if the starting state of Quasi-Envelope is chosen to be the same as the original function, the multivalue algorithm would require similar computational effort to achieve the steady state prediction, regardless of the integration stepsize. If using constant stepsize, launching QE later is helpful when quasi-envelope displays steep change at the start-up period. A changing stepsize produces slow convergence compared to the constant stepsize strategy, thus increasing the work load where the stepsize change is occurring. Other iteration method is required to be imposed to achieve faster convergence right from the beginning. Potential applications can be seen for other chemical engineering processes with inherent cyclic behaviour.

Simulated moving bed chromatography process (SMBCP) is the technical realisation of a countercurrent adsorption process through the cyclic port switching. SMB technology reduces the cost of packing material with high loading capacity and provides high purity and high recovery in a very short time. Major commodity applications have been found in the petroleum, food, biotechnology, pharmaceutical and fine chemical industries. The industrial applications bring an emergent demand to improve the SMBCP operation for higher product quality, productivity, efficiency and robustness. However, for this particular process, we encounter several challenges. Firstly, the interplay of the effects of strong nonlinearities, competition of solutes, mass transfer resistance and fluid dynamic dispersion produces steep concentration fronts. Mathematical model accounted for this particular property constitutes a serious difficulty for the solution procedure. Secondly, a dynamic SMB model consists of a set of partial differential, ordinary differential and algebraic equations, which are highly coupled. The large size is a problem due to its intensive computation when on-line optimisation and real-time control are necessary. Thirdly, the SMB unit operation exhibits complex dynamics. Process metrics for design and operation can be determined only when a cyclic steady state is reached after a certain number of switching. Achieving this steady state by solving the PDE models cycle after cycle involves expensive calculation. Studies have been carried out to solve these problems through process analysis, investigation on spatial discretisation techniques, and development of an accelerated integration scheme.
Through a systematic study on the advances of SMB modelling, design and control, a set of functionally equivalent models for SMBCP are identified and summarized for their practical applications. The limitations of the existing modelling techniques in industrial applications are also identified. Furthermore, structural analysis of the existing models is conducted for a better understanding of the functionality and suitability of each model. Suggestions are given on how to choose an appropriate model with sufficient accuracy while keeping the computational demand reasonably low for real time control.
Effort is made on to the systematic investigation of different numerical methods for the solution of PDEs to circumvent the steep gradients encountered in chromatographic separation. Comprehensive studies are conducted on a single column chromatographic process represented by a transport-dispersive-equilibrium linear model. Numerical solutions from the upwind-1 finite difference, wavelet-collocation, and high resolution methods are evaluated by quantitative comparisons with the analytical solution for a range of Peclet numbers. It reveals that for a PDE system with a low Peclet number, all existing numerical methods work well, but the upwind finite difference method consumes the most time for the same degree of accuracy of the numerical solution. The high resolution method provides an accurate numerical solution for a PDE system with a medium Peclet number. The wavelet collocation method is capable of catching up steep changes in the solution, and thus can be used for solving PDE models with high singularity.
The advantages and disadvantages of the wavelet based approaches are further investigated through several case studies on real SMBCP system. A glucose-fructose separation process is firstly chosen with its relatively simple isotherm representations. Simulations are conducted using both wavelet collocation and upwind finite difference methods. For more complicated applications, an enantiomers separation process is selected. As the PDEs model exhibit a certain degree of singularity, wavelet collocation and high resolution methods are adopted for spatial discretisation. It is revealed that both the wavelet based approaches and high resolution methods are good candidates in terms of computation demand and prediction accuracy on the steep front. This is the first time that these two frontier numerical methods are used for such a complex SMB system models and our results are encouraging for the development of model-based online control scheme.
In developing a new scheme to rapidly obtain the solution at steady state for any arbitrary initial condition, the concept of Quasi-Envelope (QE) is adopted under the consideration that a SMBCP can be treated as a pseudo-oscillatory process because of a large number of continuous switching. The scheme allows larger steps to be taken to predict the slow change of starting state within each switching. Combined with previously developed wavelet-based technique, this method is successfully applied to the simulation of a SMB sugar separation process. Investigations are also carried out on the location of proper starting point for the algorithm and on the effect of changing stepsize to the convergence of iteration method. It is found that if the starting state of Quasi-Envelope is chosen to be the same as the original function, the multivalue algorithm would require similar computational effort to achieve the steady state prediction, regardless of the integration stepsize. If using constant stepsize, launching QE later is helpful when quasi-envelope displays steep change at the start-up period. A changing stepsize produces slow convergence compared to the constant stepsize strategy, thus increasing the work load where the stepsize change is occurring. Other iteration method is required to be imposed to achieve faster convergence right from the beginning. Potential applications can be seen for other chemical engineering processes with inherent cyclic behaviour.

Crystallization is a key unit operation used for obtaining purified products by many process industries. The key properties of the crystalline products, such as size and shape distribution, purity and polymorphic form are controlled by the crystallization process. All these properties impact significantly the downstream operations such as drying or filtration. Therefore, monitoring and controlling this process is fundamental to ensure the quality of the final product. Process analytical technology (PAT) brings numerous new methods and opportunities in the process analytics and real time process monitoring systems, which can be integrated into the control algorithm and provide high level optimal control strategies as well as deeper understanding of the process. Process monitoring helps develop mathematical models which can, in one hand, help in better understanding the processes and consecvently the development and application of advanced control methods in order to achieve better product quality. In this work, image processing and image analysis based direct nucleation control (IA-DNC) is developed in order to investigate the evolution of the crystal properties, such as crystal size, and crystal shape distribution. The IA-DNC approach is also compared to alternative DNC techniques, in which particle number were measured by Focused Beam Reflectance Measurement (FBRM) in order to control crystal size. A control approach is introduced that control the nucleation and disappearance of crystals during cooling and heating segments related to the changes of the number of counts (measured by Particle Vision Measurment, so called PVM or combination of FBRM and PVM). The approach was applied to investigate crystallization of compounds with different behavior: potassium dihydrogen phosphate (KDP) water, contaminated KDP -water and Ascorbic acid water systems. The results demonstrate the application of imaging technique for model-free feedback control for tailoring crystal product properties. The second main aim of the thesis is to investigate and control crystallization processes in impure media in the presence of multiple impurities, with an impact on the crystal shape via growth kinetics. The broad impact of the crystal growth modifiers (impurities) on the growth kinetics is observed in real time by using in situ video imaging probe and real-time image analysis. A morphological population balance model is developed, which incorporates a multi-site, competitive adsorption mechanism of the impurities on the crystal faces. The kinetic parameters of primary nucleation, growth and impurity adsorption for a model system of potassium dihydrogen phosphate crystallization in water in the presence of two impurities, were estimated and validated with experimental results. It was demonstrated that the model can be used to describe the dynamic evolution of crystal properties, such as size and aspect ratio during crystallization for different impurity profiles in the system. Manual, feedback and hybrid feedback-feedforward control techniques are developed and investigated numerically for continuous processes, while model-based and model-free control approach for crystal shape are developed for batch processes. The developed morphological population balance model is implemented and applied in the model-based control approaches, which are suitable to describe multicomponent adsorption processes and their influence on the crystal shape. Case studies show the effectiveness of crystal growth modifiers based shape control techniques. Comparison of different control approaches shows the effectiveness of the techniques. The third part of the thesis deals with purification of crystals when adsorption of impurities on crystal surfaces and its incorporation into crystals are considered. A purification method, called competitive purity control (CPC) is proposed and investigated. A morphological population balance model, including nucleation, growth and competitive impurity adsorption kinetics is developed to describe the case when multiple impurities can adsorb competitively on the crystal surface. The model is also combined with liquid phase chemical reaction model, in order to investigate the purity control case when an additive is introduced in the system that reacts with the impurity forming a non-adsorbing reaction product. Both competitive purity control approaches proposed: the adsorption based competitive purity control (A-CPC) and the reaction based competitive purity control (R-CPC); are investigated using detailed numerical simulations then compared with the alternative widely used purification method, called recrystallization. In the last contribution chapter, an integrated process optimization of a continuous chemical reactor and crystallizer is performed and studied numerically. The purpose of this study is to show the way in which the byproduct produced in the chemical reactor may affect the crystallization process and how its negative effect can be reduced by applying integrated process optimization. Sensitivity analysis of the system was performed by considering the flow rate and the concentration of substances in the input stream of the chemical reactor as manipulated process variables. Model based integrated process optimization and the sensitivity analysis in order to obtain improved quality product in terms of crystal size, shape and purity.

Abstract The aim of this work was to formulate separation process models with both predictive capabilities and robust solution strategies. Although all separation process models should have predictive capabilities, the current literature still has multiple applications in which predictive models having the combination of a clear phenomenon base and robust solving strategy are not available. The separation process models investigated in this work were liquid-liquid phase separation and membrane separation models. The robust solving of a liquid-liquid phase separation model typically demands the solution of a phase stability analysis problem. In addition, predicting the liquid-liquid phase compositions reliably depends on robust phase stability analysis. A phase stability analysis problem has multiple feasible solutions, all of which have to be sought to ensure both the robust solving of the model and predictive process model. Finding all the solutions with a local solving method is difficult and generally inexact. Therefore, the modified bounded homotopy methods, a global solving method, were further developed to solve the problem robustly. Robust solving demanded the application of both variables and homotopy parameter bounding features and the usage of the trivial solution in the solving strategy. This was shown in multiple liquid-liquid equilibrium cases. In the context of membrane separation models, predictive capabilities are achieved with the application of a Maxwell-Stefan based model. With the Maxwell-Stefan approach, multicomponent separation can be predicted based on pure component permeation data alone. On the other hand, the solving of the model demands a robust solving strategy with application-dependent knowledge. These issues were illustrated in the separation of a H2/CO2 mixture with a high-silica MFI zeolite membrane at high pressure and low temperature. Similarly, the prediction of mixture adsorption based on pure component adsorption data alone was successfully demonstrated. In the context of membrane separation models, predictive capabilities are achieved with the application of a Maxwell-Stefan based model. With the Maxwell-Stefan approach, multicomponent separation can be predicted based on pure component permeation data alone. On the other hand, the solving of the model demands a robust solving strategy with application-dependent knowledge. These issues were illustrated in the separation of a H2/CO2 mixture with a high-silica MFI zeolite membrane at high pressure and low temperature. Similarly, the prediction of mixture adsorption based on pure component adsorption data alone was successfully demonstrated
Tiivistelmä Työn tavoitteena oli muotoilla prosessin käyttäytymisen ennustamiseen kykeneviä erotusprosessimalleja ja niiden ratkaisuun käytettäviä luotettavia strategioita. Vaikka kaikkien erotusprosessimallien tulisi olla ennustavia, on tällä hetkellä useita kohteita, joissa prosessin käyttäytymistä ei voida ennustaa siten, että käytettävissä olisi sekä ilmiöpohjainen malli että ratkaisuun soveltuva luotettava strategia. Tässä työssä erotusprosessimalleista kohteina tarkasteltiin neste-neste-erotuksen ja membraanierotuksen kuvaukseen käytettäviä malleja. Neste-neste-erotusmallien luotettava ratkaisu vaatii yleensä faasistabiilisuusongelman ratkaisua. Lisäksi faasien koostumusten luotettava ennustaminen pohjautuu faasistabiilisuusanalyysiin. Faasistabiilisuusongelmalla on useita mahdollisia ratkaisuja, jotka kaikki tulee löytää, jotta voitaisiin varmistaa luotettava mallin ratkaisu sekä prosessimallin ennustuskyvyn säilyminen. Kaikkien ratkaisujen löytäminen on sekä vaikeaa että epätarkkaa paikallisesti konvergoituvilla ratkaisumenetelmillä. Tämän vuoksi globaaleihin ratkaisumenetelmiin kuuluvia modifioituja rajoitettuja homotopiamenetelmiä kehitettiin edelleen, jotta faasistabiilisuusongelma saataisiin ratkaistua luotettavasti. Ratkaisun luotettavuus vaati sekä muuttujien että homotopiaparametrin rajoittamista ja ongelman triviaalin ratkaisun käyttöä ratkaisustrategiassa. Tämä käyttäytyminen todennettiin useissa neste-nestetasa-painoa kuvaavissa esimerkeissä. Membraanierotusta tarkasteltaessa ennustava malli voidaan muotoilla käyttämällä Maxwell-Stefan pohjaista mallia. Maxwell-Stefan lähestymistavalla voidaan ennustaa monikomponenttiseosten erotusta perustuen puhtaiden komponenttien membraanin läpäisystä saatuun mittausaineistoon. Toisaalta mallin ratkaisu vaatii luotettavan ratkaisustrategian, jossa hyötykäytetään kohteesta riippuvaa tietoa. Näitä kysymyksiä havainnollistettiin H2/CO2 seoksen erotuksessa MFI-zeoliitti-membraanilla korkeassa paineessa. Samoin seosten adsorboitumiskäyttäytymistä ennustettiin onnistuneesti pelkästään puhtaiden komponenttien adsorptiodatan pohjalta. Kokonaisuutena voidaan todeta, että tarkasteltujen erotusprosessimallien ennustavuutta voidaan parantaa yhdistämällä malli, jolla on selkeä ilmiöpohja ja luotettava ratkaisustrategia. Lisäksi mallien käytettävyys erotusprosessien suunnittelussa on parantunut työn tulosten pohjalta

The demand for high performance electronic devices is ever increasing in today's world with advent of digital technology in every field. In order to support this fast paced growth and incursion of digital technology in society, smarter, smaller integrated circuits are required at a lower cost. This primary requirement drives semiconductor industries towards the integration of larger number of smaller transistors on a given circuit area. The past decades have seen a rapid evolution of material processing and fabrication techniques, as focus shifts from submicron to sub-nanometer length scales in device configuration. As the functional feature size of an integrated circuit decreases, the threshold of defect causing impurities rises drastically. Huge amount of resources are spent in downstream and upstream processing in order to restore system from contamination upsets and in the upkeep of Ultra-High-Purity (UHP) process streams to meet these stringent requirements. Contamination once introduced into the system also drastically reduces process yield and throughput resulting in huge losses in revenue. Regular UHP fluid distribution system maintenance as well as restorative operations involve a purging operation typically known as Steady State Purge (SSP). This purge operation involves large amount of expensive UHP gas and time. Depending on the scale of the system and type of process involved this results in significant tool, process downtimes and can have a wide range of environment, health and safety (ESH) ramifications. A novel purge process, referred to as Pressure Cyclic Purge (PCP) was studied for establishing gas phase contamination control in UHP applications. In understanding the basic mechanism of this technique and to analyze its extent of application in aiding purging operations, a coupled approach involving experimental investigation and computational process modelling was used. Representative and generic distribution sections such as main supply lines and sections with laterals were contaminated with a known amount of moisture as impurity. The dynamics of the impurity transport through the system from purging with SSP as well as PCP was captured by a highly sensitive analyzer. The surface interactions between the moisture and EPSS were characterized in terms of adsorption and desorption rate constants and surface site density. A computational process model trained using experimental data was then validated and used to study the steady and cyclic purge mechanisms and predict complex purge scenarios. Industrially relevant and applicable boundary conditions and system definitions were used to increases the utility of the computational tool. Although SSP compared closely with PCP on simple systems without laterals, a drastic difference in dry-down efficiency was noticed in systems with dead volumes in the form of capped laterals. Studies on system design parameters revealed that the disparity in performance was observed to increase with larger number and surface area of dead volumes, opening a path to critical understanding of the differences in process mechanisms. Beneficial transient pressure gradient induced convective flow in the dead volumes during cyclic purge was identified to be the main factor driving the enhanced dry down rate. Similar trends were observed on using surface concentration as the purge metric. Hybrid purge schemes involving a combination of SSP and PCP were found to yield higher benefit in terms of efficient use of purge gas. Removal of strongly interacting contaminant species showed a higher benefit from use of controlled PCP scheme. Although, parametric analysis carried out on the operating factors of cyclic purge suggested that the enhancement in dry down increased with higher pressure range, it was highly conditional towards configurational factors in design and operation such as system dimensions, holding time, cycling pattern, valve loss coefficients and the complex inter coupling between them. The robustness of the process simulator allows the development of optimal purge scenarios for a given set of system parameters in order to perform a controlled purge. The benefit of using a hybrid PCP scheme was evaluated in terms of UHP purge gas and process time as a function of purity baseline required. Apart from UHP gas distribution systems, process vessels, chambers and components along the process stream are also prone to molecular contamination and pose a threat to product integrity. The dead volumes acting as areas of contaminant accumulation represent cavities or dead spaces in flow control elements such as mass flow controllers (MFCs), gauges, valves or dead spaces in process chambers. Steady purge has very little effect in cleanup of such areas and more efficient methods are necessitated to raise purge efficiency. The analysis of application of PCP is extended to such components through the development of a robust and comprehensive process simulator. The computational model applies a three dimensional physical model to analyze purge scenarios with steady and cyclic purge. The results presented pertain to any generic gas phase contaminant and electronic grade steel surfaces. Close investigation of the purge process helped elaborate the cleaning mechanism. Critical steps driving the purge process were identified as - dilution of chamber by introduction of fresh gas during re-pressurization and chamber venting during depressurization. Surface and gas phase purging of chambers with dead spaces using steady and cyclic purge were studied and compared. Cyclic purge exhibited a higher rate of dry down. The effect of system, design and purge operating parameters on surface cleaning were studied. Although higher frequency cycles and larger operating pressure ranges optimized for a given geometry are found to deliver better pressure cyclic purge (PCP) performances, the benefit is found to be contingent to a strong interplay between system parameters. PCP is found to be advantageous than steady state purge (SSP) in terms of purge gas usage and operation time in reaching a certain purity baseline. Specialty process gases supplied to the fabrication facility are typically stored in the form of liquids in enormous tanks outside the fab. Ammonia is a widely used in UHP concentrations for a variety of process including epitaxial growth, MOCVD, etching and wet processes in the semiconductor industry. The recent development in LED research has risen the demand and supply for Ammonia based compounds. Stringent baselines are maintained for the impurities associated with the manufacturing of such gases (e.g. Moisture in Ammonia). Apart from the difference in the rates of evaporation of the individual species from the storage cylinder causing accumulation of slower evaporating species, external temperature fluctuations also generate unsteady flux of desired species. When concentrations rise above this threshold additional purification or in most cases discarding large volumes of unused gas is warranted, causing loss of resources and causing ESH issues. Bulk gases are usually delivered over long lengths of large diameter pipes which produce large density of adsorption sites for contaminants to accumulate and eventually release into the gas stream. In order to establish contamination control in the gas delivery system, the surface interactions of the multispecies system with the delivery line surface was characterized. Desired concentrations of moisture in ammonia and UHP nitrogen mixtures were produced in a gas mixing section capable of delivering controlled mass flow rates to an EPSS test bed. Transient moisture profiles during adsorption and desorption tests at various test bed temperatures, mass flow rates and moisture concentration were captured by a highly sensitive analyzer. A mathematical model for single and multi-species adsorption was used in conjunction with experimental data to determinate kinetics parameters for moisture, ammonia system in EPSS surface. The results indicate competitive site binding on EPSS between ammonia and water molecules. Also, the concentration distribution of each species between surface, gas phase is interdependent and in accordance to the kinetic parameters evaluated. Back diffusion of impurity is a major source of contaminant introduction into UHP streams. Back diffusion refers to the transport of contaminants against the flow of bulk process stream. Molecular species can back diffuse from dead volumes, during mixing operations etc., simply when there is a gradient of concentration. A steady state approach was used to analyze the mechanism and effects of various geometrical and operational parameters on back diffusion. High sensitivity moisture detectors were used to capture the dynamics of contamination in a section of a generic distribution system. Results showed that back diffusion can occur through VCR fittings, joints and valves under constant purge. General trends on the effect of design parameters on back diffusion were derived from studies on various orifice sizes, system dimensions, flow rates and test moisture concentrations. Coupled parametric studies helped identify critical variable groups to perform dimensionless analysis on back diffusion of moisture. Crucial points where back diffusion can be minimized or completely eliminated are identified to help set up guidelines for cyclic and steady purge parameters without excessive use of expensive UHP gas or installation of unnecessarily large factors of safety. Wet cleaning of micro/nano sized features is a highly frequent process step in the semiconductor industry. The operation is a huge consumer of ultra-pure water and one of the main areas where process time minimization is focused. Comprehensive process model is developed to simulate the mechanism and capture the dynamics of rinsing high aspect ratio Silicon features in the nanometer scale. Rinsing of model trench, post etch contaminated with ammonium residue is studied. Mass transport mechanisms such as convection, diffusion are coupled with surface processes like adsorption and desorption. The effect of charged species on the trench surface and in the bulk, the resultant induced electric field on the rinse dynamics and decay of surface species concentration is studied. General rinsing trends and critical points in change in mechanisms were identified with critical groups such as mass transfer coefficient and desorption coefficient. The model is useful in evaluating process efficiency in terms of rinse time and DI water consumption under varying process temperature, contaminant concentration, and rinse fluid flow rate. The generic build of the model allows extension of its functionality to other impurity-substrate material couples.

A mesure que l'intérêt mondial pour les énergies renouvelables s'intensifie, la production de biogaz ne cesse de croître, car elle est une source renouvelable et propre. La technologie de séparation par adsorption modulée en pression (Pressure Swing Adsorption ou PSA) se présente alors comme une des technologies intéressantes permettant la valorisation du biogaz en biométhane. La grande flexibilité du procédé PSA est liée en une certaine manière à sa complexité avec plusieurs paramètres de design et opératoires contrôlant les performances de l’unité de séparation. L’identification de ces paramètres par une approche expérimentale est pratiquement impossible et une phase d’étude numérique est primordiale pour dimensionner l’unité, concevoir le cycle de pression et déterminer les conditions optimales de fonctionnement, avant tout essai expérimental. L’objectif général de la thèse a été centré sur le développement d’outils de simulation d’un procédé de purification de biométhane par technologie PSA.Dans un premier temps, une simulation basée sur une modélisation dynamique monodimensionnelle non isotherme a été mise en place. Elle fait appel à un modèle cinétique d’adsorption de double force motrice (bi-LDF) pour décrire les échanges de matière intragranulaires. Le choix de l’adsorbant s’est porté sur un tamis moléculaire de carbone (CMS-3K) permettant d’assurer une grande sélectivité cinétique du dioxyde de carbone vis à vis du méthane (CH4). Le cycle PSA a été optimisé pour obtenir une récupération du CH4 de 92 % avec une consommation d'énergie spécifique modérée de 0,35 kWh/Nm3, tout en respectant les spécifications de pureté d’injection dans le réseau national (97 % de CH4). Les performances obtenues sont ainsi compatibles avec une exploitation industrielle. Ce cycle est composé de cinq colonnes et de quinze étapes incluant trois équilibrages et un recyclage de gaz de purge.Le développement d’un modèle numérique multidimensionnel (3D) et multi-échelle (colonne/grain/cristal) permettrait d’estimer les limites des hypothèses et des corrélations utilisées dans les simulateurs usuels. La première étape consiste à simuler l’écoulement du gaz dans un lit d’adsorbant ayant une morphologie la plus réaliste possible. Ainsi, lors de la seconde partie du travail de thèse, un lit constitué de billes inertes a été généré numériquement par calcul DEM (modélisation par éléments discrets) pour une colonne de taille de laboratoire. L’emploi d’OpenFOAM (logiciel CFD) a permis de calculer l’écoulement tridimensionnel d’un traceur dans la colonne. En parallèle une étude expérimentale du front de percée a été menée pour un lit de mêmes dimension et caractéristiques. Les temps de percée et les coefficients de dispersion-diffusion calculés et mesurés sont similaires. Cependant la simulation présente quelques divergences de la concentration du traceur localement dans la colonne, en raison de difficultés de maillage. L’étape suivante consistera à prendre en compte des interactions grains-fluide en considérant des grains poreux d’adsorbant
As global interest in renewable energy intensifies, biogas production continues to grow as a clean, renewable source. Pressure Swing Adsorption (PSA) is considered as one of the most interesting technologies for the valorization of biogas into biomethane. The great flexibility of the PSA process is linked in some way to its complexity with several design and operating parameters which control the performance of the separation unit. The identification of these parameters by an experimental approach is practically impossible. A numerical study stage is essential for sizing the unit, designing the pressure cycle and identifying the optimal operating conditions before any experimental test.The general objective of the thesis was focused on the development of simulation tools for a biomethane purification process using PSA technology.In a first stage, a simulation based on one-dimensional non-isothermal dynamic model, where the intragranular mass transfer kinetics was modelled using a double driving force (bi-LDF) approximation, was implemented. A carbon molecular sieve (CMS-3K) was selected. This adsorbent ensures a high kinetic selectivity of carbon dioxide with respect to methane (CH4). The optimized cycle, composed of five columns and fifteen steps including three equalization steps and a purge gas recycling allowed a CH4 recovery of 92% with a moderate specific energy consumption of 0.35 kWh/Nm3 , at the same time respecting the grid injection specifications (97% CH4 purity ). The performance obtained is thus compatible with industrial operation.The development of a multidimensional (3D) and multi-scale (column/grain/crystal) numerical model would serve to evaluate the limits of the assumptions and correlations used in usual simulators. The first step consists in simulating the gas flow in an adsorbent bed having a reaslistic stacking.. Thus, an inert packed bed was numerically generated by DEM calculation (discrete element modeling) for a column of laboratory size. The use of OpenFOAM (CFD software) allowed to calculate the three-dimensional tracer gas flow in the column. In parallel an experimental study of the breakthrough curves was carried out using a bed having the same dimensions and characteristics. The breakthrough times and the dispersion-diffusion coefficients calculated and measured were similar. However the simulation showed some divergences in the concentration of the tracer locally in the column, due to difficulties in meshing. The next step will consist in taking into account grain-fluid interactions by considering porous adsorbent grains

L’azoto è uno dei prodotti principali dell’industria chimica, utilizzato principalmente per assicurare un sicuro stoccaggio di composti infiammabili. Generatori con sistemi PSA sono spesso più economici della tradizionale distillazione criogenica. I processi PSA utilizzano una colonna a letto fisso, riempita con materiale adsorbente, che adsorbe selettivamente un componente da una miscela gassosa. L’ossigeno diffonde molto più velocemente dell'azoto nei pori di setacci molecolari carboniosi. Oltre ad un ottimo materiale adsorbente, anche il design è fondamentale per la performance di un processo PSA. La fase di adsorbimento è seguita da una fase di desorbimento. Il materiale adsorbente può essere quindi riutilizzato nel ciclo seguente. L’assenza di un simulatore di processo ha reso necessario l’uso di dati sperimentali per sviluppare nuovi processi. Un tale approccio è molto costoso e lungo. Una modellazione e simulazione matematica, che consideri tutti i fenomeni di trasporto, è richiesta per una migliore comprensione dell'adsorbente sia per l'ottimizzazione del processo. La dinamica della colonna richiede la soluzione di insiemi di PDE distribuite nel tempo e nello spazio. Questo lavoro è stato svolto presso l'Università di Scienze Applicate - Münster, Germania. Argomento di questa tesi è la modellazione e simulazione di un impianto PSA per la produzione di azoto con il simulatore di processo Aspen Adsorption con l’obiettivo di permettere in futuro ottimizzazioni di processo affidabili, attendibili ed economiche basate su computazioni numeriche. E' discussa l’ottimizzazione di parametri, dati cinetici, termodinamici e di equilibrio. Il modello è affidabile, rigoroso e risponde adeguatamente a diverse condizioni al contorno. Tuttavia non è ancora pienamente soddisfacente poiché manca una rappresentazione adeguata della cinetica ovvero dei fenomeni di trasporto di materia. La messa a punto del software permetterà in futuro di indagare velocemente nuove possibilità di operazione.

This thesis describes both batch and continuous processes for water treatment by adsorption with electrochemical regeneration of the adsorbent using an airlift reactor. The process is based on the adsorption of dissolved organic pollutants onto a graphite intercalation compound (GIC) adsorbent and subsequent electrochemical regeneration of the adsorbent by anodic oxidation of the adsorbed pollutant. Batch experiments were carried out to determine the adsorption kinetics and equilibrium isotherm for a sample contaminant, the organic dye Acid Violet 17 on the GIC (Nyex®1000) adsorbent. The adsorption capacity was found to be around 1 ± 0.05 mg/g. The rate of adsorption appeared to follow pseudo-second order kinetics. The increase in the rate adsorption with temperature indicated an activation energy of around 4.2 KJ/mole, suggesting that the mechanism of adsorption was physisorption. It was demonstrated that the adsorbent could be regenerated by anodic oxidation of the adsorbed dye in a simple electrochemical cell. The GIC adsorbent recovered its initial adsorption capacity after 40 to 60 min of treatment at a current density of 10 mA/cm2, corresponding to a charge passed of 12 to 15 C/g of adsorbent. The charge passed is consistent with that expected for mineralisation of the dye suggesting that the dye was removed and destroyed with high charge efficiency. Experiments were carried out to investigate the characterisation and performance of the continuous process, where water is treated continuously in a fluidised adsorption zone and the adsorbent is circulated through a moving bed electrochemical regeneration cell. The adsorbent circulation rate, the residence time distribution (RTD) of the reactor, and water treatment performance by continuous adsorption and electrochemical regeneration were studied. The RTD behaviour could be approximated as a continuously stirred tank. It was found that greater than 90% removal at feed concentrations of up to 100 mg/L were achieved using a single pass through a large continuous treatment unit by adsorption and electrochemical regeneration with a flow rate of 0.25 L/min. In a smaller continuous treatment unit 98% removal at feed concentrations of up to 66 mg/L were achieved in a single pass with a flow rate of 0.24 L/min. Steady state and dynamic models have been developed for the continuous process performance, assuming full regeneration of the adsorbent in the moving bed electrochemical cell. Experimental data and modelled predictions (using parameters for the adsorbent circulation rate, adsorption kinetics and isotherm obtained experimentally) of the dye removal achieved were found to be in good agreement. A higher dye removal was found with a co-current PFR model, but a number of tank in series (n CSTRs) was found to give higher contaminant removal for the same total adsorption zone volume. It was also found that the predicted number of stages of batch adsorption / regeneration required to achieve 99.9% AV17 removal was halved when the adsorptive capacity of the adsorbent was doubled. Similarly the predicted number of continuous CSTR adsorption / electrochemical regeneration process units required in series to achieve 99% AV17 removal was reduced by more than two thirds when the adsorptive capacity of the adsorbent was doubled.

The adsorption of Ni(II) onto blue green marine algae (BGMA) in batch conditions is being investigated. The highest adsorption capacity of BGMA was found to be 42.056 mg/g under ideal testing conditions, where the initial Ni(II) metal ion concentration was adjusted from 25 ppm to 250 ppm. The optimal pH, biomass loading, and agitation rate for maximum Cu(II) ion removal have been determined to be 6, 2 g and 120 rpm, respectively. For the equilibrium condition, 24 hours of contact time is allowed. At room temperature, all of the experiments are conducted. The isotherm has a L shape, based on the equilibrium experimental data. It indicates that there is no considerable competition for active sites between the solvent and Ni(II). There is no strong competition between the solvent and Ni(II) for the active sites of BGMA, indicating that there is no strong competition between the two. It also suggests that the BGMA’s Ni sorption ability is restricted (II). The experimental data is validated using multiple isotherm models, and the mechanism of adsorption is then discovered, as well as the process design parameters. The Fritz-Schlunder-V isotherm model is particularly relevant in defining the mechanism of Ni(II) adsorption under the conditions used in this study, according to modelling studies. This model’s qmax of 41.89 mg/g shows that it matches experimental data more closely.

Forest fuel moisture content is an important parameter that determines fire risk and fire behaviour. An accurate prediction of moisture content is therefore of great importance in fire management. In the fire risk period, dead forest fuel moisture content changes mainly by water vapour sorption processes so its knowledge enables the development of predictive fire risk models. In the present work, the adsorption and desorption processes and equilibrium moisture content of 10-hour dead Pinus pinaster branches (diameter between 0.6 cm and 2.5 cm) were described in order to develop a moisture content prediction model for this type of fuels. Laboratorial tests were used to determine sorption curves, timelag and equilibrium moisture content for different sets of air temperature (range between 20°C and 40°C) and relative humidity (range between 10% and 90%). The sorption curves and equilibrium moisture were also modelled with forest fuels and agricultural and food products existing models. Field tests were used to evaluate the sorption and equilibrium moisture content models performance. Dead Pinus pinaster branches were collected in central Portugal through the year 2020 and 2021 on the Portuguese fire risk period (15th May to 15th October) between 12:00h and 13:00h LST. Samples with 0.6 cm to 2.5 cm diameter were collected and transported to laboratory to determine moisture content. The laboratorial drying and wetting curves of dead Pinus pinaster branches (0.6 cm to 2.5 cm diameter) show that they are not pure exponential functions, but with different timelag values until equilibrium is reached. Additionally, the results suggest no significant relationship of the timelag periods with air relative humidity but a dependence with air temperature, showing an increase in the sorption rates with temperature. In terms of sorption curves, Modified Henderson and Pabis model provide the best fitting. For this type of fuels, the representation of EMC values as a function of air relative humidity at constant temperature allowed to obtain a typical sigmoid curve. The EMC values obtained were higher for desorption process than for adsorption process, indicated the typical hysteresis effect in these processes. It was found that, besides the models used in forest fires, other EMC models are also suitable to predict fuel moisture content of dead Pinus pinaster branches, as the ones used in agricultural and food analysis.

Abstract Objective/Scope The CO2 emission is one of the main causes for the global warming and it may be controlled by sequestrating CO2 into the geological formation. The coalbed formation provides a dual advantage for CO2 sequestration as CO2 may be stored in coal forever with enhancing the coalbed methane recovery. Thus, the cost of CO2 sequestration may be offset completely or partially. The main objective of the paper was to comprehend the CO2-ECBM displacement using the three concepts viz. competitive adsorption, diffusion, and thermodynamic modelling of coal Methods, procedure, and process In this paper, the pure gas isotherm on coal for CH4, and CO2 was evaluated using manometric method. The binary gas isotherm or competitive adsorption was studied using IAST modelling. MATLAB code was developed for the solution of IAST model and Newton Raphson approach was followed. The IAST modelling was done by taking 50%/%50 mole fraction of CH4/CO2. By analyzing the binary gas isotherm, the optimum injection pressure was evaluated. On the same injection pressure, co adsorption isotherm was drawn at different mole fraction of CO2 in gas phase. Separation factor was calculated by taking ratio of CO2 and CH4 in the gas and adsorbed phase respectively. Furthermore, adsorption data was used for discussing the sorption kinetics in coal and diffusion coefficient was evaluated. Furthermore, the thermodynamic parameters were also calculated and integrated with above noted parameters for the methane displacement in CO2-ECBM process. Results, observations, and calculations The CO2-ECBM displacement is very much dependent on the competitive adsorption and diffusion process in coal. The surface potential and Henry constant are important parameters for defining the CO2-ECBM displacement. The coadsorption isotherm was drawn at the optimum injection pressure and it shows that methane displacement would be the optimum by taking 11 %/89% mole fraction of CO2 and CH4 for two temperatures i.e., 288 K, 308 K. It is identified through diffusion regime that diffusion coefficient for the binary gas isotherm is the average of the diffusion coefficients of pure CO2 and CH4. Novel/Additive information This is the first kind of study which provides the completely integrated approach for describing the methane displacement in CO2-ECBM process. This novel study promotes our understanding of the complex mechanisms of CO2-ECBM displacement process.

Research studies on the adsorption kinetics are conducted in order to determine the absorption time of heavy metals on coffee grounds from liquid. The models of adsorption kinetics and adsorption diffusion are based on mathe-matical models (Cho et al. 2005). The adsorption kinetics can provide information on the mechanisms occurring be-tween adsorbates and adsorbents and give an understanding of the adsorption process. In the mathematical modelling of processes, Lagergren’s pseudo-first- and pseudo-second-order kinetics and the intra-particle diffusion models are usually applied. The mathematical modelling has shown that the kinetics of the adsorption process of heavy metals (copper (Cu) and lead (Pb)) is more appropriately described by the Lagergren’s pseudo-second-order kinetic model. The kinetic constants (k2Cu = 0.117; k2Pb = 0,037 min−1) and the sorption process speed (k2qeCu = 0.0058–0.4975; k2qePb = 0.021–0.1661 mg/g per min) were calculated. After completing the mathematical modelling it was calculated that the Langmuir isotherm better reflects the sorption processes of copper (Cu) (R2 = 0.950), whilst the Freundlich isotherm – the sorption processes of lead (Pb) (R2 = 0.925). The difference between the mathematically modelled and experimen-tally obtained sorption capacities for removal of heavy metals on coffee grounds from aqueous solutions is 0.059–0.164 mg/l for copper and 0.004–0.285 mg/l for lead. Residual concentrations of metals in a solution showed difference of 1.01 and 0.96 mg/l, respectively.

Abstract The potential of nanoparticles, which are classified as advanced fluid material, have been unlocked for improved oil recovery in recent years such as nanoparticles-assisted waterflood process. However, there is no existing commercial reservoir simulation software that could properly model phase behaviour and transport phenomena of nanoparticles. This paper focuses on the development of a novel robust advanced simulation algorithms for nanoparticles that incorporate all the main mechanisms that have been observed for interpreting and predicting performance. The general algorithms were developed by incorporating important physico-chemical interactions that exist across nanoparticles along with the porous media and fluid: phase behaviour and flow characteristic of nanoparticles that includes aggregation, splitting and solid phase deposition. A new reaction stoichiometry was introduced to capture the aggregation process. The new algorithm was also incorporated to describe disproportionate permeability alteration and adsorption of nanoparticles, aqueous phase viscosities effect, interfacial tension reduction, and rock wettability alteration. Then, the model was tested and duly validated using several previously published experimental datasets that involved various types of nanoparticles, different chemical additives, hardness of water, wide range of water salinity and rock permeability and oil viscosity from ambient to reservoir temperature. A novel advanced simulation tool has successfully been developed to model advanced fluid material, particularly nanoparticles for improved/enhanced oil recovery. The main scripting of physics and mechanisms of nanoparticle injection are accomplished in the model and have acceptable match with various type of nanoparticles, concentration, initial wettability, solvent, stabilizer, water hardness and temperature. Reasonable matching for all experimental published data were achieved for pressure and production data. Critical parameters have been observed and should be considered as important input for laboratory experimental design. Sensitivity studies have been conducted on critical parameters and reported in the paper as the most sensitive for obtaining the matches of both pressure and production data. Observed matching parameters could be used as benchmarks for training and data validation. Prior to using in a 3D field-scale prediction in Malaysian oilfields, upscaling workflows must be established with critical parameters. For instance, some reaction rates at field-scale can be assumed to be instantaneous since the time scale for field-scale models is much larger than these reaction rates in the laboratory.

Abstract A major Malaysian offshore oilfield, which is currently operating under waterflooding for a quite long time and declining in oil production, plan to convert as chemical enhanced oil recovery (CEOR) injection. The CEOR journey started since the first oil production in year 2000 and proximate waterflooding, with research and development in determining suitable method, encouraging field trial results and a series of field development plans to maximize potential recovery above waterflooding and prolong the production field life. A comprehensive EOR study including screening, laboratory tests, pilot evaluation, and full field reservoir simulation modelling are conducted to reduce the project risks prior to the full field investment and execution. Among several EOR techniques, Alkaline-Surfactant (AS) flooding is chosen to be implemented in this field. Several CEOR key parameters have been studied and optimized in the laboratory such as chemical concentration, chemical adsorption, interfacial tension (IFT), slug size, residual oil saturation (Sor) reduction, thermal stability, flow assurance, emulsion, dilution, and a chemical injection scheme. Uncertainty analysis on CEOR process was done due to the large well spacing in the offshore environment as compared to other CEOR projects, which are onshore with shorter well spacing. The key risks and parameters such as residual oil saturation (Sorw), adsorption and interfacial tension (IFT) cut-off in the dynamic chemical simulator have been investigated via a probabilistic approach on top of deterministic method. The laboratory results from fluid-fluid and rock-fluid analyses ascertained a potential of ultra-low interfacial tension of 0.001 dyne/cm with adsorption of 0.30 mg/gr-of-rock, which translated to a 50-75% reduction in Sor after waterflooding. The results of four single well chemical tracer tests (SWCTT) on two wells validated the effectiveness of the Alkaline Surfactant by a reduction of 50-80% in Sor. The most suitable chemical formulation was found 1.0 wt. % Alkali and 0.075 wt. % Surfactant. The field trial results were thenceforth upscaled to a dynamic chemical simulation; from single well to full field modeling, resulting an optimal chemical injection of three years or almost 0.2 effective injection pore volume, coupled with six months of low salinity treated water as pre-flush and post-flush injection. The latest field development study results yield a technical potential recoverable volume of 14, 16, and 26 MMstb (above waterflooding) for low, most likely, and high cases, respectively, which translated to an additional EOR recovery factor up to 5.6 % for most-likely case by end of technical field life. Prior to the final investment decision stage, Petronas’ position was to proceed with the project based on the techno-commerciality and associated risks as per milestone review 5, albeit it came to an agreement to have differing interpretations towards the technical basis of the project in the final steering committee. Subsequently, due to the eventual plunging global crude oil price, the project was then reprioritized and adjourned correspondingly within Petronas’ upstream portfolio management. Further phased development including a producing pilot has been debated with the main objective to address key technical and business uncertainties and risks associated with applying CEOR process.

Abstract Gas injection has become one of the most investigated methods for enhanced oil recovery in unconventional reservoirs. Nonetheless, the presence of natural and induced fractures negatively impacts the gas injection efficiency due to its channeling towards nearby wells or poor coverage in the treated area due to lack of conformance. To overcome these difficulties and boost the oil recovery process by gas injection, this work presents a novel gas dispersible foam technology to improve the sweep efficiency of gas injection in unconventional IOR/EOR projects. The development and evaluation of this technology has passed through a series of laboratory assurance stages that include fluids characterization, compatibility, and extensive coreflooding tests. A modelling approach is also presented, which was validated using lab and field data taken from the implementation of the technique in an extremely low porosity, tight and naturally fractured quartz-arenite gas condensate reservoir in Colombia. The workflow herein presented encompasses interdisciplinary components such as laboratory evaluation, reservoir modeling, treatment design, and wellsite setup and execution. Laboratory testing and inter-well field applications results, along with the development and testing of a phenomenological modelling approach, demonstrate that the gas dispersible foam injection can be a high potential technique for oil and/or condensate recovery in unconventional reservoirs given its proven ability to improve the deep reservoir gas conformance and avoid the lack of gas containment during gas injection IOR/EOR in unconventional plays. Lab results in a tight naturally fractured sample, suggest that the estimated incremental oil recovery was ~36% and the effective gas mobility reduction was ~45%. This technique also exhibited less chemical adsorption losses, which contributes to better chemical emplacement and longer durability. The main results of the field application, including a progressive decrease in gas injectivity at the gas injector, a consistent reduction in GOR with an associated oil increase at the influenced producer well, and a reported treatment durability of ~ 6 months, were all properly represented by the model. Each step of the workflow herein proposed not only assures the gas-based projects success, but also allows for smaller logistics footprint at the well location, along with less water consumption, which translates into cheaper and more efficient gas injection conformance operations.