Hydrophobic Polymers Flooding

Crude oil and other petroleum products are crucial to the global economy today due to increasing energy demand approximately (~1.5%) per year and significant oil remaining after primary and secondary oil recovery (~45-55% of original oil in place, OOIP), which accelerates the development of enhanced oil recovery (EOR) technologies. Polymer flooding through hydrophobically associated polyacrylamides (HAPAM) is a widely implemented EOR-technique, so they attracted much attention on both academic and industrial scales. Hydrophobically associating polyacrylamide (HAPAM) prepared by free radical emulsion polymerization of acrylamide (AM) monomer, divinyl sulfone as hydrophobic crosslinked moiety and surfmers, to chemically anchor a surfmer and hydrophobic crosslinker moiety onto the back bone of acrylamide chain. After that, polymeric nanocomposite was prepared through copolymerization of prepared HAPAM with different molar ratios of silica nanoparticles through one shot synthesis. Rheological properties for the prepared composites were evaluated. Wettability evaluation carried through quantitative and qualitative techniques where the results indicate novel polymers ability to alter rock wettability from oil-wet to water- wet

Time reduction for SLM OFDM PAPR based on adaptive genetic algorithm in 5G IoT networks

In this paper, a new peak average power and time reduction (PAPTR) based on the adaptive genetic algorithm (AGA) strategy is used in order to improve both the time reduction and PAPR value reduction for the SLM OFDM and the conventional genetic algorithm (GA) SLM-OFDM. The simulation results demonstrate that the recommended AGA technique reduces PAPR by about 3.87 dB in comparison to SLM-OFDM. Comparing the suggested AGA SLM-OFDM to the traditional GA SLM-OFDM using the same settings, a significant learning time reduction of roughly 95.56% is achieved. The PAPR of the proposed AGA SLM-OFDM is enhanced by around 3.87 dB in comparison to traditional OFDM. Also, the PAPR of the proposed AGA SLM-OFDM is roughly 0.12 dB worse than that of the conventional GA SLM-OFDM

Predicting the Compressibility Factor of Natural Gas by Using Statistical Modeling and Neural Network

Simulating the phase behavior of a reservoir fluid requires the determination of many parameters, such as gas–oil ratio and formation volume factor. The determination of such parameters requires knowledge of the critical properties and compressibility factor (Z factor). There are many techniques to determine the compressibility factor, such as experimental pressure, volume, and temperature (PVT) tests, empirical correlations, and artificial intelligence approaches. In this work, two different models based on statistical regression and multi-layer-feedforward neural network (MLFN) were developed to predict the Z factor of natural gas by utilizing the experimental data of 1079 samples with a wide range of pseudo-reduced pressure (0.12–25.8) and pseudo reduced temperature (1.3–2.4). The statistical regression model was proposed and trained in R using the “rjags” package and Markov chain Monte Carlo simulation, while the multi-layer-feedforward neural network model was postulated and trained using the “neural net” package. The neural network consists of one input layer with two anodes, three hidden layers, and one output layer. The input parameters are the ratio of pseudo-reduced pressure and the pseudo-reduced temperature of the natural hydrocarbon gas, while the output is the Z factor. The proposed statistical and MLFN models showed a positive correlation between the actual and predicted values of the Z factor, with a correlation coefficient of 0.967 and 0.979, respectively. The results from the present study show that the MLFN can lead to accurate and reliable prediction of the natural gas compressibility factor

Optimizing the Production of LNG and NGL from Arab Crudes and Wet Gases

Natural Gas Liquids (NGL) refer to a mixture of gases that consist mostly of ethane, propane, butane and pentane. The other term which closely related to NGL is Liquified Natural Gas (LNG) which refers to methane and traces of ethane. These products can be extracted by multi-stages of compression and cooling. In addition of being the main feedstock of any petrochemical industry, NGL and LNG are used widely in the industrialized countries as a major source of energy. It is expected that their future role in both the international energy market and the petrochemical industry will continue its historical gradual growing trend.This paper presents the mathematical formulation of an economic model that was developed to optimize the production of LNG and NGL. The objective function of the model is to maximize the net cash flow return of selling LNG and NGL. The explanatory variables of the model are LNG and NGL volumes and prices, oil volume and prices, the initial costs of separators, chillers, demethanizer, compressor, partial condenser and boiler, the running cost which includes cost of refrigerants, cost of steam and other continuous operating and transportion cost. The developed model should be utilized as a useful tool to help the design of an efficient processing of natural gases. A great deal of the unlimited what if questions can be answered using this model. This paper also presents a flow sheet of the natural gas processing model. Each section of the proposed production system is presented schematically. The mathematical formulation of the computation techniques used in each section are given along with all the equation derivations

Flow of Saudi Oil Emulsions in Pipelines

Flow characteristics of Saudi oil emulsions in pipelines were studied experimentally and described mathematically. The type of emulsions prepared were oil-in-water and their rheological properties were measured using HAAK viscometer at different temperatures and oil concentrations. The emulsifying agent (Triton X-100) was used to stablize the emulsions with a concentration of 0.5% by volume. Three rheological models were developed to relate the shear stress to shear rate, oil concentration and temperature. These models were used to describe the flow behavior of the emulsions in pipelines. The effects of oil concentration and temperature on the pressure required to pump such emulsions in pipelines under turbulent conditions were also studied

Synthesis and Characterization of Imidazolium-Based Ionic Liquids and Evaluating Their Performance as Asphaltene Dispersants

With the projected increase in the production of heavy oil due to the energy crisis, asphaltene-related issues are likely to come to the forefront. This leads to operational problems, safety hazards, and oil production deficiencies, resulting in huge economic losses for the petroleum industry. Therefore, in this work, we aimed to inhibit asphaltene precipitation using ionic liquid (IL) compounds. ILs with long alkyl chains can inhibit the precipitation of asphaltene molecules due to the π–π* interactions between them and the formation of hydrogen bonds. A series of imidazolium-based ionic liquids, IL-0, IL-4, IL-10, and IL-16, were synthesized with yield percents of 79, 81, 80, and 83%, respectively. The prepared materials were characterized well using FTIR, 1H-NMR, and Elemental Analysis. The surface tension, interfacial tension (IFT), and different surface parameters were investigated at different temperatures to simulate the reservoir temperature. IL-0, IL-4, IL-10, and IL-16 displayed their γcmc values at 35, 34, 31, and 32 mN/m at 303 °K, respectively. It was found that the prepared ILs are good surfactants with low values of interfacial tension. Quantum structure–activity relationships using Density Functional Theory (DFT) were used to investigate the geometry optimization electronic structures, the energy gap (ΔE), and the reactivity of the cations of the prepared ILs. The synthesized ILs were evaluated as asphaltene dispersants using two different techniques. The viscometric technique showed that the asphaltene onset precipitation was 28.5 vol.%. This percent was postponed to 42.8, 50, 78.5, and 64.3 vol.%, after adding IL-0, IL-4, IL-10, and IL-16, respectively, and the spectroscopic technique confirmed the results

Factors Affecting Sand Production from Unconsolidated Sandstone Saudi Oil and Gas Reservoir

In this work a physical model has been constructed to simulate sand production from oil and gas reservoirs. The model can accommodate unconsolidated as well as consolidated sandstone cores. The experiments were designed to investigate the effect of confining pressure, flow rate, and the displacing fluid viscosity on sand production mechanism in unconsolidated sandstone formations. Saline water (3.5% NaCl by weight), light (35° API) and heavy (27° API) crude oils were used as displacing fluids in the tests. The main goal of this study was to examine if controlling of the production rate alone can solve the problem of sand production in a Saudi oil reservoir. The oil reservoir is situated in an unconsolidated sandstone formation. A produced sand sample was obtained from this reservoir. Tests were conducted on sand packs having a similar granulomere distribution to that of the reservoir.The experimental results showed that, the magnitude of sand production from the tested porous medium is strongly affected by both flow rate and confining pressure. Sand production decreases with increasing confining pressure and/or decreasing flow rate. Only very fine particles of the porous medium are produced at high confining pressures. When water, or low viscosity crude oil are saturating the porous medium, sand production problem can be managed by controlling the flow rate. In case of saturating the porous medium by heavy crude oil, sand production mechanism becomes different and therefore, controlling only the flow rate cannot stop sand production. Hence, alternative sand control measures must be applied to control sand production in heavy crude oil reservoirs such as down hole emulsification, gravel packing, screen liners, or down hole consolidation

Beneficial Features of Biochar and Arbuscular Mycorrhiza for Improving Spinach Plant Growth, Root Morphological Traits, Physiological Properties, and Soil Enzymatic Activities

Biochar and arbuscular mycorrhizal fungi (AMF) can promote plant growth, improve soil properties, and maintain microbial activity. The effects of biochar and AMF on plant growth, root morphological traits, physiological properties, and soil enzymatic activities were studied in spinach (Spinacia oleracea L.). A pot experiment was conducted to evaluate the effect of biochar and AMF on the growth of spinach. Four treatments, a T1 control (soil without biochar), T2 biochar alone, T3 AMF alone, and T4 biochar and AMF together, were arranged in a randomized complete block design with five replications. The biochar alone had a positive effect on the growth of spinach, root morphological traits, physiological properties, and soil enzymatic activities. It significantly increased the plant growth parameters, such as the shoot length, leaf number, leaf length, leaf width, shoot fresh weight, and shoot dry weight. The root morphological traits, plant physiological attributes, and soil enzymatic activities were significantly enhanced with the biochar alone compared with the control. However, the combination of biochar and AMF had a greater impact on the increase in plant growth, root morphological traits, physiological properties, and soil enzymatic activities compared with the other treatments. The results suggested that the combined biochar and AMF led to the highest levels of spinach plant growth, microbial biomass, and soil enzymatic activity

Evaluate the Toxicity of Pyrethroid Insecticide Cypermethrin before and after Biodegradation by Lysinibacillus cresolivuorans Strain HIS7

Herein, bacterial isolate HIS7 was obtained from contaminated soil and exhibited high efficacy to degrade pyrethroid insecticide cypermethrin. The HIS7 isolate was identified as Lysinibacillus cresolivuorans based on its morphology and physiology characteristics as well as sequencing of 16S rRNA. The biodegradation percentages of 2500 ppm cypermethrin increased from 57.7% to 86.9% after optimizing the environmental factors at incubation condition (static), incubation period (8-days), temperature (35 °C), pH (7), inoculum volume (3%), and the addition of extra-carbon (glucose) and nitrogen source (NH4Cl2). In soil, L. cresolivuorans HIS7 exhibited a high potential to degrade cypermethrin, where the degradation percentage increased from 54.7 to 93.1% after 7 to 42 days, respectively. The qualitative analysis showed that the bacterial degradation of cypermethrin in the soil was time-dependent. The High-Performance Liquid Chromatography (HPLC) analysis of the soil extract showed one peak for control at retention time (R.T.) of 3.460 min and appeared three peaks after bacterial degradation at retention time (R.T.) of 2.510, 2.878, and 3.230 min. The Gas chromatography–mass spectrometry (GC–MS) analysis confirmed the successful degradation of cypermethrin by L. cresolivuorans in the soil. The toxicity of biodegraded products was assessed on the growth performance of Zea mays using seed germination and greenhouse experiment and in vitro cytotoxic effect against normal Vero cells. Data showed the toxicity of biodegraded products was noticeably decreased as compared with that of cypermethrin before degradation

Preparation and Characterization of Super-Absorbing Gel Formulated from κ-Carrageenan–Potato Peel Starch Blended Polymers

κ-carrageenan is useful for its superior gelling, hydrogel, and thickening properties. The purpose of the study was to maximize the hydrogel properties and water-absorbing capacity of κ-carrageenan by blending it with starch from potato peels to be used as safe and biodegradable water-absorbent children’s toys. The prepared materials were analyzed using FTIR and Raman spectroscopy to analyze the functional groups. Results showed that there was a shift in the characteristic peaks of starch and κ-carrageenan, which indicated their proper reaction during blend formation. In addition, samples show a peak at 1220 cm−1 corresponding to the ester sulfate groups, and at 1670 cm−1 due to the carbonyl group contained in D-galactose. SEM micrographs showed the presence of rough surface topology after blending the two polymers, with the appearance of small pores. In addition, the presence of surface cracks indicates the biodegradability of the prepared membranes that would result after enzymatic treatment. These results are supported by surface roughness results that show the surface of the κ-carrageenan/starch membranes became rougher after enzymatic treatment. The hydrophilicity of the prepared membranes was evaluated from contact angle (CA) measurements and the swelling ratio. The swelling ratio of the prepared membranes increased gradually as the starch ratio increased, reaching 150%, while the water-uptake capacity increased from 48 ± 4% for plain κ-carrageenan to 150 ± 5% for 1:2 κ-carrageenan/starch blends. The amylase enzyme showed an effective ability to degrade both the plain κ-carrageenan and κ-carrageenan/starch membranes, and release glucose units for up to 236 and 563, respectively. According to these results, these blends could be effectively used in making safe and biodegradable molded toys with superior water-absorbing capabilities