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Developing grey-box model to diagnose asphaltene stability in crude oils: Application of refractive index. Asphaltene precipitation can cause serious problems in petroleum industry while diagnosing the asphaltene stability conditions in crude oil system is still a challenge and has been subject of many investigations. To monitor and diagnose asphaltene stability, high performance intelligent approaches based bio-inspired science like artificial neural network which have been optimized by various optimization techniques have been carried out.

Production and hosting by Elsevier B. In the lifetime of petroleum industry, Asphaltene precipitation has the capability to be one of the most challenging issues in the process of petroleum production [1]. As the asphaltene deposition can occur in several places in the process of production: in the reservoir, near the wellbore, in the tubing, in surface production facilities and transportation systems, therefore it increases the expenditures and technical problems for. E-mail address: ahmadi yahoo. Peer review under responsibility of Southwest Petroleum University.

As the investigation gets deeper, the most probable place for occurrence of asphaltene deposition is near-well bore [3]. The first step for development of asphaltene precipitation model is the accurate knowledge of how asphaltene exist in the oil [4], therefore, it is useful to identify the crude composition and then explore asphaltene stability in the fluid.

There are several methods that describe crude oil composition [5]. SARA analysis is one of the simple approaches that commenced with the study of Jewell et al. This analysis divides crude into four categories: saturate, aromatic, resin, and asphaltene SARA fractions. The saturate fraction is formed of nonpolar material like: linear, branched, and cyclic saturated hydrocarbons. Aromatics are more polarizable that include one or more aromatic rings [5].

Resins are known as the fraction of the desasphalted oil that is strongly taken in surface-active materials such as Fuller's earth, alumina, or silica, and can be desorbed by a particular solvent such as pyridine or a. Recently, they are defined by scientist as the part, precipitated by addition of low-boiling alkane paraffin solvent such as normal heptane but soluble in aromatic solvent like toluene or benzene [10]. SARA classification can help us in identifying oil with the potential for asphaltene problems because it divides oil into fractions that related to asphaltene stability.

Of course Wang and Buckley emphasized that measurement of SARA fractions are considerably related to the extraction methodology [5]. Despite, there are comprehensive studies in literatures about asphaltene stability and precipitation, but scientists can't describe the real mechanism of asphaltene agglomeration, floc-culation and precipitation, yet [11—14]. Andersen [15], Fotland et al. Moreover they mention that the effect of surrounding fluid composition and pressure are more remarkable than temperature influence. Likewise, Field experience [19,20] corroborates their results.

Buckley hinted to this point that it is helpful to differentiate between surrounding fluids that can compel asphaltene precipitation and those that do not [21]. Here upon others tried to quantify oil solvent properties and they found that pressure, temperature and oil composition can change oil solvent properties and effect on asphaltene stability [22,23]. Thermo-dynamic models follow these alterations by allocating solubility parameters to oil and asphaltenes [24—26]. Colloidal models propose a colloidal suspension of asphaltene in the oil and assume that they asphaltene are stabilized by resines in the mixture [27,28].

The disperse phase of the crude oils is formed by asphaltenes, and resins, while maltenes are the continuous phase [29] and the colloidal stability of this mixture determines asphaltene precipitation [30]. Resins naturally occurring inhibitors have a considerable propensity to amalgamate with asphaltenes [14,31]. Such association specify their solubility in crude oil [32]. Even though the association between asphaltene and resins has never been irrefutably manifested [9] but some studies offered methods to indicate asphaltene stability based on presence of resin.

For example, Resin to asphaltene ratio can be applied to disclose asphaltene stability according to an idea that assumes resins impart asphal-tene stability by peptizing coating asphaltene particles [28]. Experimental observation of Fan et al. Colloidal instability index C. This index is defined below. Indeed CII is a monitoring criterion to distinguish the potential of asphaltene deposition in a crude sample [33]. De Boar [19] prepared some diagram for fast screening the risk of asphaltene precipitation.

In addition, Jamaluddin et al. Flowchart of hybrid genetic algorithm and particle swarm optimization process [42,43,53]. The refractive index has an indispensable situation in many branches of physics, biology and chemistry [37]. The refractive index RI has been manifested to describe several prominent properties of multicomponent native petroleum, like: PVT behavior and surface tension [39,40] also asphaltene precipitation [41].

Refractive index of materials varies with the wavelength. This is called dispersion [42]. Measured vs. Buckley assumed that if the London dispersion contribution to the van der Waals forces is considered as the main intermolecular interaction energy in which it London dispersion controls asphaltene precipitation, then we can use refractive index dispersion to characterize London dispersion properties [39].

Wattana et al. Although, the refractive index of light crudes can be directly assessed by common refractive-meters, but RI measurements of heavy oils and naturally bitumen are not possible, because of their turbid colors. In these cases, it is communal assumption to consider that a mixture of crude oil and a non-precipitant solvent behaves as an ideal binary mixture [44] where the crude oil is treated as a single component and the solvents are treated such as the second in the mixture.

Then the real RI value of crude oils can be achieved by applying an easy-to-use mixing rule and extrapolation data [39]. For instance, Wattana et al. When the mixture refractive index was measured, its value reflects a proportion between all the blend components and. Furthermore Buckley revealed that the paraffinic compounds are among the lowest RI substances in a crude while, asphaltenes, resins, and aromatic hydrocarbons are among the highest [21].

Heptane titration curve can be used to determine the refractive index of deasphalted crude. Recently, there is an admissible point in which the reduction of the maltene fraction refractive index can decreases the asphaltene stability in the bulk of crude oil [45]. Goual and Firoozabadi showed the temperature dependency of the refractive indices [46]. Values of RI have been applied by Feynman et al. Fan et al. Predicted and measured asphaltene. In this paper, our aim is to develop various intelligent approaches for assessment of asphaltene stability in crude oils through the relation between the experimental SARA fraction data and the refractivity index of the crude oil sample.

Evolutionary algorithms are carried out in this work to optimize on initial weights of the parameters implemented in artificial neural network. Results obtained from the developed intelligent approaches were compared with the corresponding experimental refractivity index data and discussed in further details throughout this research.

One of robust and quick approaches in engineering known as Artificial Neural Networks or ANNs, has been around for more than half of century. One of outstanding characteristics of ANN is mapping the complex targets and corresponding input variables. To achieve the performance of ANNs, following points should be considered []:. Due to previous studies of authors, multi-layer perceptron MLP with one hidden layer is recommended to model complicated issues in petroleum industry.

To figure out the number of hidden neuron, trial and error procedure was executed and decision tool was mean square error MSE and it is when the values of solutions at the neurons of target layer are very nearly approach to the corresponding actual measured data [].

Fundamentals and Applications

GA which is one the most famous sort of optimization methods is basically known with its unique characteristics which are searching very fast and optimizing efficiently, the two very important features derived from the principle of "survival of the fittest" component of natural evolution with the genetic propagation of belongings. In reality, GA functions through determining a range of zones in the objective area clarified by experts and defining concurrently and randomly a large number of likely. Additionally, the GA could theoretically and effortlessly been replaced with typical optimization procedures thanks to its initiation which is based on the notion of Darwinian natural selection and genetics in natural systems.

According to notion of 'survival of the fittest', the GA can converge towards the finest point in the arranged space soon after a series of cycling calculations. This searching pattern is based on technical tasks which are artificial mutation, crossover and selection.


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The presented algorithm is essentially run by preparing an opening population including a definite number of so-called individuals which are demonstrating the probable routes towards the preferred purpose. Turning chromosomes into encoded strings is the next step which is supposed to be precisely done. Successively, compatibility of each encoded string with the nature of the problem must be assessed by applying a fitness function.

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The production of fitness function pertinent to each chromosome is taken as criteria to come to a decision whether the related string can make an acceptable performance available. After removing weakest persons based on the already determined standards which are determined by the designer, it is the turn to operate crossover and mutation rates to yield fresh individuals with better performance.

Then, execution of the crossover action on the couple of chosen strings chromosomes to recombine them has to be tracked. It has been recommended by the prior studies that the greatest performance of the GA becomes possible when the crossover point of any two chromosomes is aimlessly set. The process is followed by shifting some random selected position to. Particle Swarm Optimization PSO as a robust and high attended population based algorithm which firstly introduced and developed by Eberhard and Kennedy [61].

The PSO method is recently being executed to unravel various engineering optimization issues where a surface or a point in a multidimensional parameter space relevant to the best outcome and must be sought. One may view this approach as an iterative calculation of the optimum location of a swarm of particles that have a flow, a direction of movement and velocity. The value and direction of the accelerations play a crucial role in calculations, and the locations of the particles in the swarm are updated iteratively implementing the below expressions [62,63]:.

Making randomly the initial population and its following evaluation are the starting steps of this hybrid. The generated error of the best individual can stop the process, if its value reaches the already stop criteria. On the other hand, the process goes on to get close as much as possible to this standard by gaining from advantages of the particle swarm optimization algorithm through simultaneous increasing the number of elites and running the chaining processes of tournament selection, cross over and mutation operations, and generating the new offspring.

Combining the effects of these two ways on each other causes generating the new population with the features of enhanced elites and offspring See Fig. Atashpaz-gargari et al. According to the previous note, this optimization algorithm is called "Imperialist Competitive Algorithm" and abbreviate in ICA [66,67]. Throughout this optimization algorithm same as other evolutionary optimization algorithms the imperialist competitive algorithm launches with initial populations called countries. Countries in the ICA are split in two types: colony and imperialist in optimization terminology, countries with the least cost which together form empires.

In the imperialistic competition procedure, imperialists make efforts to attract more colonies. As a result, during this process, the robust imperialists will be raised in the power and the vice versa about the weak ones. Each empire could collapse when the addressed empire loses all of its colonies. At the end of referred algorithm the most robust imperialist survives in the world and all the countries are colonies of this unique empire.

Throughout this stage imperialist and colonies have the same position and power [66,67]. The implementation procedures of our developed matching approach based on imperialist competitive algorithm ICA are depicted in Fig. As reported previously in the literature, four parameters including 1- Asphaltenes 2-Resins 3- Aromatics 4- Saturates could affect refractive index RI due to this fact to assess the aim of this contribution the addressed parameters were implemented as inputs of the developed sophisticated approach in order to diagnosis asphaltene stability based on refractive index RI.

These parameters were faced to the constructed network model to forecast refractive index RI as well as asphaltene stability. Same as other intelligent approaches, network model is extremely affected by various parameters which were involved in the development of the neural network approach like interconnection weights and biases. To solve successfully this issue, enormous efforts have been made to obtain optimum connection weights through network approach such as implication different population based optimization algorithms. To depict the robustness and uncertainty of the developed intelligent models, two statistical parameters were executed which are the mean square error MSE and correlation coefficient R2 expressed as following [53,54,67]:.

When the MSE closes gradually to the zero, the error of our developed network model starts declining. RI represents the average of the measured refractive index RI data. Based on previously addressed statistical performance indexes and avoid any over-fitting issue due to restriction of the implemented datasets, three layer network which has 7 neurons in hidden layer can monitor refractive index and furthermore asphaltene stability see Fig. Back propagation BP algorithm with training function called "Levenberg—Marquardt" was implemented to train the developed network model to estimate refractive index RI while it is worth mentioning that the.

To show uncertainty, integrity and effectiveness of the proposed network model and further coupled approaches, 44 data samples were faced for network training and the remaining 19 samples were put aside to be executed for testing and validating the network's performance. It is worth mentioning that the value 0. As can be seen from the addressed figure, estimated refractive indexes RI do not cover the actual trend whether overestimated or underestimated.

Another point which could be extracted from Fig. To solve successfully the addressed issues, enormous efforts have been made to improve the robustness and to decline the uncertainty of the ANN model to estimate refractive index RI by means of optimizing interconnection weights of ANN model using various optimization algorithms based on previously suggested objective function.

Optimization algorithms executed in this work are the imperialist competitive algorithm, genetic algorithm, Particle swarm optimization and hybrid of them. It is worth to highlight that the main purpose of each optimization algorithm is defined to minimize mean square error MSE and approach its value to zero.

The perspective is reinforced that simple heuristics 39 are useful to account for differences observed for asphaltenes from different 40 sources. The 44 peripheral alkane substituents yield steric repulsion inhibiting molecular association. With the 45 attractive forces in the molecular interior and the repulsive forces on the molecular exterior, 46 small aggregation numbers are predicted for nanoaggregates, as discussed below.

In contrast, an 47 archipelago architecture would give multiple binding sites in single molecules leading to gel 48 formation at low concentrations; this is never observed for asphaltenes. A decrease in alkane substitution must lead to a 53 corresponding decrease in PAH ring size. Coal-derived asphaltenes have much less alkane than 54 petroleum asphaltenes. First, coal-derived asphaltenes are from coal that lacks much alkane. This molecular population with larger 8 PAHs is thus removed from the asphaltene fraction.

Relevant issues for these nanocolloidal 21 particles are the concentration of formation and aggregation number or size. For the different 22 investigative methods, more robust results are often obtained for either the concentration of 23 24 formation or the aggregation number, generally not both. The CNAC of asphaltenes has recently been 27 addressed by both by DC-conductivity measurements and centrifugation of asphaltene-toluene 28 solutions.

Of the many techniques that have been used to investigate CNAC of asphaltenes in 29 toluene, perhaps DC-conductivity is the most robust. However, DC-conductivity is sensitive to 30 31 the very small mass fraction of asphaltene molecules that are charged in crude oil, on the order of 32 or less. It has already been shown that DC-conductivity gives the same CNAC 35 results as high-Q ultrasonic spectroscopy for the same asphaltene samples. Figure 13 shows the DC-conductivity results and centrifugation results.

Moreover, the centrifugation experiments were 46 designed to collect small nanoaggregates. One expects that asphaltenes 8 close to the far wall of the centrifuge tube should be collected. In addition, there might be a small 9 inorganic component associated with clays that gets collected. The lack of temperature dependence 19 of the CNAC indicates that nanoaggregate formation is primarily entropically driven while of 20 course the most favorable enthalpy configuration is favored.

In aqueous systems, entropically 21 driven micelle formation is common, essentially occurring due to decreased excluded volume of 22 the solvent. That is, the increase in solvent entropy upon aggregate formation is more important 23 24 than the reduction of asphaltene entropy.

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The attractive PAH is in the molecular interior while the 56 57 peripheral alkanes produce steric repulsion. Nevertheless, with entropic 4 5 formation, there can be aggregate number limits established as well. Extra large aggregates 6 might have too low an entropy favoring an optimal aggregates size. This could be an important 7 consideration for cluster formation, in that cluster size does not have molecular architecture 8 limitations.

Upon destabilization with n-heptane addition, the nanoaggregates stick to each 46 47 other upon collision. A morphological change is needed on the surface of the 49 fractal clusters to allow them to stick. This requirement of morphological change yields reaction- 50 limited aggregation. For many reasons, this 53 54 is an important parameter to determine. DC-Conductivity exhibits the critical clustering concentration of asphaltenes.

For n- 21 heptane asphaltenes, the CCC is 2. In addition the 26 effect of the C5-insoluble, C7-soluble fraction changed the CCC but primarily by a trivial 27 dilution effect. C5-insolubles flocculate with addition of n-pentane; C7-insolubles flocculate 28 with addition of n-heptane. The same trivial dilution effect applies to the CNAC. Atomic force microscopy of a Langmuir-Blodgett film of asphaltene nanoaggregates 53 on highly oriented pyrolytic graphite. A Deposited from toluene,[70] B Deposited from 54 chloroform. The dotted and solid lines represent the Guinier and Zimm approximations, 43 respectively, in the small-q domain.

The contrast between SAXS sensitivity to electron density, 44 45 and thus the polycyclic aromatic hydrocarbon PAH stack, versus the SANS sensitivity to 46 hydrogen, and thus the peripheral alkanes, gives the length scale of the interior PAH stack of 47 the nanoaggregate: approximately 1. In addition, these data sets also show 53 the existence of clusters.

In order to provide tight constraints for 29 interpretation in Fig. Not one, but two distinct nanocolloidal species are 40 41 obtained. The smaller species is a nanoaggregate of small aggregation number with an aromatic 42 core and an alkane shell. A cluster with a small aggregation number of nanoaggregates is 43 obtained. While the overall length scales for the nanospecies in Figs. For example, the sizes of the asphaltene PAH are similar, not identical. In 45 addition, proposed molecular structures must explicitly account for the energetics of ring systems 46 47 as has been discussed.

It is also important to remember that 49 there are multiple types of sizes that appear in these different studies. The DC-conductivity studies and asphaltene molecular diffusion studies are 52 53 sensitive to the hydrodynamic radius, while the centrifugation studies and the oilfield studies are 54 sensitive to the effective physical radius. Thus, even for the exact same species, different studies 55 will obtain somewhat different effective sizes.

If cluster formation is enthalpically driven, 4 5 it is hard to understand why aggregation would cease at this nano length scale. However, if 6 cluster formation is entropically driven as nanoaggregate formation is, then it makes sense that 7 there is an optimal size. Too little aggregation and the solvent entropy is too low, too much 8 aggregation and the asphaltene entropy is too low.

Asphaltenes

Indeed, studies on related inverse micelles 9 support the idea of an entropy drive for formation of nanoparticles. The observed characteristics of the Wiehe phase behavior plots can be 21 obtained via a regular solution approach presuming asphaltene nanoaggregates.

With the resolution of the 29 size of asphaltene molecules and nanocolloidal species, the gravity term can now be determined 30 31 in an equation of state. The gravity term has been aded to the Flory-Huggins Equation that has 32 been used extensively in treating asphaltene phase behavior. Julian Y. Zuo who is leading the 34 effort to use this new thermodynamic model to address a variety of major oilfield concerns.

For condensates, the relevant asphaltene volume is 48 49 the molecule, for black oils, the relevant asphaltene volume is the nanoaggregate and for mobile 50 heavy oil, the relevant asphaltene volume is the cluster.


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  • Mobile heavy oils have viscosities up to 51 roughly one thousand centipoise and can be produced conventionally. The crude oil solubility parameter for a live crude oil with its 55 56 reservoir solution gas depends on the gas-oil ratio GOR of the crude oil. The asphaltene solubility parameter can be estimated 6 without much difficulty and for evaluating asphaltene gradients in reservoirs a single parameter 7 value suffices, e.

    Many recent oilfield studies have shown the 13 utility of this combination of asphaltene nanoscience and the FHZ EoS. Figure 20 shows the 14 application of this equation of state for each of the three asphaltene species in Fig. Asphaltene gradients in three different oilfield reservoirs are shown. Left: 43 condensate with a true molecular solution of asphaltene or asphaltene-like molecules, Center: 44 low GOR black oil with asphaltene nanoaggregates, Right: mobile heavy oil with asphaltene 45 clusters. Note the larger clusters produce a gravitational gradient 50x larger than the low GOR 46 47 black oil.

    For the condensate, the GOR gradient helps create the asphaltene gradient. In all three cases, the reservoirs were shown to be in flow 51 communication by production, which is consistent with an equilibrated fluid column. And for the mobile heavy oil Fig. Most importantly, the two gradients differ by a factor of Recent data on heavy oilfields from Gulf of Mexico, 4 5 Russia, Saudi Arabia and Ecuador all exhibit the same gradients due to asphaltene clusters. Because viscosity of heavy oil depends exponentially on asphaltene 10 11 content, and oil flow rate depends inversely on viscosity the asphaltene gradients are very 12 important.

    For example, the asphaltene gradient in Fig. This has huge implications in 14 heavy oilfields around the world. Most importantly, the Yen-Mullins model not only applies to 18 asphaltenes in toluene but also applies to asphaltenes in reservoir crude oils. This auspicious 19 circumstance bodes well for many important field applications. Because asphaltene equilibration 20 is a slow process on a geologic time scale, then the implication is that these reservoirs with 21 equilibrated asphaltenes are connected without flow barriers.

    Another major success of the FHZ EoS is the ability to account for the gigantic 29 30 asphaltene gradient in a single oil column deepwater, Gulf of Mexico. Figure 21 shows the 31 asphaltene gradient, which is obvious to the eye, along with the results of the FHZ EoS 32 analysis. The gas quickly 33 migrates to the top of the reservoir and then diffuses down.

    Where the solution gas is high at the 34 top of the oil column, the asphaltenes are expelled. Towards the base of the oil column, the 35 solution gas remains low as the gas has not had sufficient time to reach the base by diffusion. This variable solution gas is 38 grossly out of equilibrium. The asphaltenes locally equilibrate according to the solution gas 39 content in the oil, but the asphaltene content is also grossly out of equilibrium when considering 40 the column as a whole.

    These are dead crude oils, the solution gas has been removed. One visually sees a 5 giant asphaltene gradient that is reproduced by the FHZ EoS using nanoaggregates. In similar oilfields with a later gas charge but where the solution gas has 8 increased diffused all the way to the bottom of the oil column, the asphaltene can be expelled in 9 10 bulk creating a tar mat at the base of the column.

    PC-SAFT modeling has recently been employed to model asphaltene gradients and 14 also offers a promising approach. Tar that formed at the base of a high GOR oil column. This asphaltene-rich tar formed 38 on a cemented sandstone, thus not at an oil-water contact. Water had nothing to do with this 39 tar mat formation. Gas diffusion into the oil destabilized the asphaltene causing phase 40 instability at the base of the column.

    Transport of asphaltenes through porous media is dependent on the existence of 44 multiple colloidally stable species. That is, destabilization of nanoaggregates can produce 45 asphaltene clusters that then create high concentrations of asphaltene towards the case of the oil 46 column cf. It is at the base of the column where the highest asphaltene 47 48 concentrations are found which can exceed the solvency of the crude oil for asphaltenes, thereby 49 inducing phase instability there.

    Nevertheless, it is important to realize that processes on 50 geologic time are slow and can involve additional complexities. Figure 23 shows that asphaltene 51 flocculation times can become quite long when the destabilization of asphaltenes is slight.

    Detection times for onset of precipitation and onset of haze for varying heptane 21 concentrations using K-1 and N-2 crude oils. The objective of the study was to evaluate the possibility of ionic liquids to be used for miscible EOR. The surface activity of [P 6 6 6 14 ] [Cl] was studied through measurements carried out to determine the IFT, density, and viscosity of an equilibrium phase formed by various mixtures of the IL [P 6 6 6 14 ] [Cl], water and dodecane. This is done since some reservoirs contain high salinity brine formation. For the binary system of water and [P 6 6 6 14 ] [Cl], the interfacial tension was reduced to1.

    When [P 6 6 6 14 ] [Cl] was added to a binary system of water and dodecane to form a tri-phasic system, the interfacial tension measure changed from Even though the interfacial tension obtained was not close to the values obtained in conventional surfactants, the results encouraged further investigations with other ILs and combination of ILs. With regards to the replacement of water with brine, it was observed that the ionic liquid in the mixture shielded any effects of the salt.

    They also observed an increase in the viscosity of the water phase when ionic liquids were added. This may be a very useful property since it could prevent the flood water from seeping through high permeability regions or fractures and thus delay high water cut production. This may also help to decrease the water-oil mobility ratio within the reservoir which may lead to more efficient oil recovery. Subsequently Lago et al [33]. A triphasic system was created between water, dodecane and [P 6 6 6 14 ] [Cl] and it was observed that there was little influence of temperature on the equilibrium compositions Hezave et al [34].

    It was observed that there was a decrease in interfacial tension up from Surprisingly when the IFT was measured again between formation brine and crude oil there was a significant decrease in IFT with only ppm of [C 12 mim] [Cl]. This reduction in IFT with low concentrations of IL in salt water compared to higher concentrations when IL in distilled water is attributed to the absence of any ion either positive or negative in the distilled water. Thus the IL molecules were incapable of arranging themselves freely at the oil-water interface because the high charge density of ILs lead to molecular repulsion.

    However, in saline water the presence of negative charges neutralize the positive surface charges of the cationic part of IL. This resulted in an easier accumulation of IL molecules at the oil-brine interface, and further reduction in IFT [34]. It was observed that at NaCl concentrations up to , ppm far higher than reservoir formation brine , the IL significantly reduces the IFT to values lower than conventional surfactants. The effects of temperature on the interfacial tension between [C 12 mim] [Cl] and crude oil was also considered for the study.

    The temperature was varied from It was noted that the minimum temperature corresponding to a minimum interfacial tension is the phase invasion temperature PIT. This can be explained as being the result of the surfactant or [C 12 mim] [Cl] adsorption onto the interface and diffusing into the oil phase, resulting in emulsion inversion as the ionic liquid content is accumulated to some extent [34] [35] [36].

    Further looked into different families of ionic liquids and their functionality in harsh reservoir conditions such as high salinity and high temperature, at which most surfactants lose their functionality. Success in this direction would boost chemical EOR applications in the reservoirs where presently no solution is available. Their results showed that all the four ILs were more effective in the presence of salinity in reducing IFT as compared to conventional surfactants.

    Asphaltene Deposition: Fundamentals, Prediction, Prevention, and Remediation - CRC Press Book

    The functionality of the ILs are seen to diminish as the temperature increased, and this was attributed to the presence of nitrogen atoms in the imidazolium and pyridinium based ILs. It was concluded that the ILs exhibited good properties in reducing IFT in harsh reservoir salinity conditions.

    However, before implementing these ILs to a field scale, further studies should be conducted to design an IL solvent which can also withstand high reservoir temperatures and also their adsorption on reservoir rocks should be studied. One of the main drawback of surfactants is their high adsorption on the reservoir rocks which leads to a change in rock wettability towards more water wet conditions thus favoring release of oil and improved recovery.

    However this property has negative impact on the economics of EOR. Therefore these new ILs as a substitute of surfactant flooding should be designed to optimize the adsorption on the reservoir rocks at the same time keeping in mind the economics of the project. Shaktivel et al [38]. The Wilhelmy plate method was used to study the surface tension and interfacial tension of aqueous solutions of the ionic liquids and crude oil systems, with and without salinity effect while considering the concentration of the ILs and also the effect of temperature on the system.

    The ionic liquids synthesized and used in this experiment are 1-butyl methylimadazolium chloride, 1-butylmethylimadazolium bromide,1-butylmethylimadazolium tetra-fluoroborate, 1-butylmethylimadazolium dihydrogen phosphate, 1-butylmethylimadazolium hydrogen sulfate, 1-butyl methyl-imadazolium hexa-fluorophosphate, 1-hexyl methylimadazolium bromide, 1-hexylmethyl-imadazolium hydrogen sulfate and 1-octylmethylimadazolium chloride. The interfacial tension of the crude oil-water systems is greatly dependent on the adsorption of IL molecules at the interface between crude oil and water.

    In this study, it was observed that the concentration of ILs also affects the interfacial tension between crude oil and water [39]. The IFT measurements at It can be inferred from the rest of the experiments that, the longer the alkyl chain length, the more effective the IL is at reducing the IFT at lower concentrations. The IFT of crude oilwater systems were also measured in the presence of ionic liquids in presence of NaCl.

    Aside from focusing on the reduction of IFT some researchers also observed the changes in rock wettability and relative permeabilities. Dahbag et al [41]. Initially, they screened different ILs based on their solubility in different brine compositions, thermal stability and IFT reduction in high salinity and hightemperature conditions. After selecting the most suitable ionic liquid, they went on to conduct several core flooding experiments at reservoir conditions using Berea sandstone cores to investigate the ability of the ILs to adsorb on rock surfaces and change their wettability.

    After the initial screening of nine ionic liquids, tetra-alkyl-ammonium sulfate was found to be the most potent ionic liquid. IFT measurements of tetraalkyl- ammonium sulfate with crude oil at different IL concentrations and high solution salinity showed a reduction in IFT even with increasing levels of salinity. Temperature and pressure had little effect on these measurements. The tendency for adsorption on rock surfaces at reservoir conditions was observed and even in high salinity ionic solution. After core flooding experiments, wettability changes were confirmed by performing contact angle measurements.

    Wettability changed from slightly oil wet to mediumwaterwet condition as the IL concentration was increased [41]. In most research works, the imidazolium family of ILs with chloride counter-ions are given maximum attention. In a study by Rodriguez- Palmeiro et al [31]. A surfactant-IL comprising of 1-dodecyl methylimidazolium cation and acetate anion [C 12 mim] [OAc] was synthesized and used for a series of dynamic interfacial tension studies in varying temperature, water salinity and some alkaline additives.

    The results obtained with the new surfactant ionic liquid were compared with the results found from the literature of similar ionic liquid but with different counter-ions which were halides chloride, bromide, and iodide. The effects of aggregation of [C 12 mim] [OAc] was investigated and it was seen to exhibit a lower critical micelle concentration and a better tendency for micellization over adsorption at the interface and lower spontaneity for micellization [31].

    Promising results were also obtained from dynamic interfacial tensions of aqueous solutions of [C 12 mim] [OAc] with crude oil various compositions. In presence of alkalis, the interfacial tension was further reduced. Results obtained from Rodriguez-Palmeiro et al. Heavy Oil dissolution and Viscosity reduction One of the challenges of the upstream petroleum industry is the recovery of heavy and extra heavy crude oil, which is estimated to be more than double the volumes of conventional light to medium crude oils discovered throughout the globe. The heavy fraction wax, asphaltenes and resinous compounds present with the crude oil are responsible for the higher viscosity and density of the crude oil which poses challenges not only in production but also in surface processing and refining [42].

    Because easily extractable lighter oil reserve is steadily decreasing, the industry is becoming rapidly dependent on economic extraction of the heavy and extraheavy oil that was previously considered uneconomical. For the purpose of heavy oils recovery, thermal methods steam injection and in-situ combustion are the most successful methods, while non-thermal methods such as miscible gas injection and solvent injection found limited success in real field scenario. The problems of transporting heavy and viscous crude oils through long distance pipelines and assuring its flow is another great challenge that sometimes make the project un-economic.

    Since the resistance to flow is originated form the oil microstructure, partial upgrading through the modification of the microstructure by heating and solvent dilution have been the most widely applied methods in pipeline transportation of heavy oils. However the high price of the diluents, difficulties in separation and recycling, availability of light oils close to heavy oil fields, and the environmental and climate specific issues put serious restrains on heavy oil dilution process.

    There is also the issue of compatibility between the crude and the solvents which may results in solids precipitation and plugging. This necessitates increasing solvent polarity [45] or use of aromatic solvents to prevent asphaltene precipitation and the resulting flowline blockage [44] , thus increasing operational cost as well as the environmental concerns.

    One of the initial works on heavy oil upgradation was tried with 1-butylmethylimidazolium chloride [BMIM] [AlCl4] ionic liquid reported by Fan et al. Further progress on the similar class of ILs, the modified versions of 1-butyl methylimidazolium tetrachloroferrate [BMIM] [FeCl 4 ], were prepared by Shaban et al [47]. Saaidet al [37]. They synthesized1-butylmethylimidazolium perchlorate, [BMIM] [ClO 4 ], and studied their effect on viscosity, density, SARA saturates, aromatics, resins and asphaltens contents, elemental compositions and molecular weight.

    The results indicated that the presence of [BMIM] [ClO 4 ] significantly changes the composition of the heavy oil which resulted in reduction of viscosity and density of the crude and improved flow ability. Sakthivel et al [38]. Investigated a set of eight different ionic liquids along with five solvents, namely heptane, toluene, decane, ethyl acetate, and hexane to assess the possible dissolution effect on heavy crude oils. Usually the treatment of heavier hydrocarbons such as asphaltene is done by aromatic solvents such as benzene, xylene, and toluene.

    Even though these aromatic solvents are efficient asphaltene dissolvers, they are however volatile and hazardous to human. This work shows that with minimal addition of ionic liquids to heavy crude oil the dissolution effect is markedly enhanced. Further research on the similar path were conducted using only ionic liquids without any solvents to identify the effect of only ionic liquids on the dissolution of heavy crude oil and asphaltenes in heavy crude oils [2] [38] [48] however the results are not so promising.

    In continuation to the previously mentioned studies, Sakthivelet al [38] [49]. UV-visible spectrophotometric techniques were used to observe absorbance intensity with respect to a particular ionic liquid for a concentration range from 10 to 70 ppm. IL content of 10 ppm was found to be adequate for nearly complete dissolution.

    Another explanation for the effective dissolution of tankbottom sludge containing ionic liquids could be due to the fact that there is an interaction between the ionic liquids and the asphaltenes which eventually breaks the asphaltene macro-structure. This is because there is an interaction between the cationic part of the ionic liquid and the heteroatomic functional groups of asphaltenes which is the major constituents of the TBS such as Sulphur, Oxygen, and Nitrogen. The heteroatoms of the asphaltenes contain at least one lone pair of electrons which are available for the ionic interaction.

    At higher concentrations of the ionic liquids, the asphaltene molecules are effectively surrounded by ILs and solvated by the interaction forces. Further studies on the interactions between asphaltenes and ionic liquids can lead to the development of an environmentally friendly inhibitor to mitigate flow assurance issues in the oilfield. Synergistic effect of ionic liquids along with brine has also been studied. Reduction of interfacial tension is more effective in presence of salt in the mixture. The above findings reveal that it may be possible to minimize the amount of organic solvents that may be required to upgrade heavy oil and tank bottom sludge and may also help in surface and subsurface flow-assurance issues by employing suitable IL-Solvent combinations.

    As discussed above the precipitation and deposition of heavy organics in crude oil like wax and asphaltenes poses great challenge during crude oil production, transportation and storage, of which the concern for asphaltene deposition is significantly higher. Agglomeration and deposition of asphaltenes can be caused due to change in pressure, temperature, pH and composition of crude oil [51]. Waxes are long chain paraffin components of crude oil and rather easy to handle, mostly by heat management, which is not the case for asphaltene.

    The chemical structure of asphaltenes is uncertain due to their complex and uncertain nature [53] [54] [54]. When asphaltenes precipitate and deposit in the reservoir, they may cause permeability and porosity reduction and also wettability alterations from water—wet to oil-wet [56] , an unwanted phenomenon which results in lowering oil relative permeability flow efficiency. It is observed that reservoirs which undergo enhanced oil recovery EOR processes like hydrocarbon gas or miscible CO 2 injection are faced with severe asphaltene problems regardless of crude oil density and viscosity.

    Therefore prior to implementing any enhanced oil recovery project, it is recommended that a careful study of the probability of asphaltene precipitation and deposition be carried out in order to consider the preventive measures or mitigation strategies [54] [57] [58].

    In the likelihood of asphaltene precipitation, chemical treatment techniques such as asphaltene inhibitors are employed to prevent the aggregation of asphaltene molecules and to enhance their stability in the crude oil. In most cases however, the solvent treatments are carried out to dissolve already precipitated asphaltene in the wellbore and surface flow lines. Some conventional asphaltene dissolvers are toluene, xylene, and benzene, however, these chemicals are flammable, carcinogenic, dangerous to handle and harmful to the environment [59]. The next generation asphaltene inhibitors are based on their surfactant characteristics and the most prominent among them is the dodecylbenzenesulphonic acid DBSA.

    These surfactants must have the ability to stabilize the suspended asphaltene colloids and also dissolve asphaltenes in the molecular level through acid-base interactions [40] [50] [60] [61] [62]. Recently, ILs have attracted attention in the area of asphaltene inhibition due to their effectiveness in dissolution of heavy crude oil, and also the ability to disperse asphaltenes in crude oils [60] [63] [64] [65].

    One of the early investigations performed by Hu and Guo [63] was on the effect of ionic liquids and amphiphiles on the inhibition of asphaltenes precipitated from CO 2 injected oil reservoirs, where miscibility between oil and CO 2 occurred. Ionic liquids with different types of cationic groups and anions were investigated, with emphasis on the effect of the cation tail lengths, head groups, cation and anion combination and the concentration of the ionic liquids.

    The studies were performed on oil with CO 2 in miscible condition above minimum miscible pressure and the asphaltene precipitation was measured quantitatively.