Intelligent Predictor for Polymer Viscosity to Enhance Support for EOR Processes

Research into the use of polymers for enhanced oil recovery (EOR) processes has been going on for more than 6 decades and is now classified as a techno-commercially viable option. A comprehensive evaluation of the polymer's rheology is pivotal to the success of any polymer EOR process. Laboratory-based evaluation is critical to EOR success; however, it is also a time/capital consuming process. Consequently, any tool which can aid in optimizing lab tests design can bring in great value. Accordingly, in this study a novel predictive correlation for viscosity estimation of commonly used "FP 3330S" EOR polymer is presented through use of cutting-edge machine learning neural networks. Mathematical equation for polymer viscosity is developed using machine learning algorithms as a function of polymer concentration, NaCl concentration, and Ca2+ concentration. The measured input data was collected from the literature and sub-divided into training and test sets. A wide-ranging optimization was performed to select the best parameters for the neural network which includes the number of neurons, neuron layers, activation functions between multiple layers, weights, and bias. Furthermore, the Levenberg-Marquardt back-propagation algorithm was utilized to train the model. Finally, measured and estimated viscosities were compared based on error-analysis. Novel correlation is developed for the polymer that can be used in predictive mode. This established correlation can predict polymer viscosity when applied to the test dataset and outperforms other published models with average error in the range of 3-5% and coefficient of determination in excess of 0.95. Moreover, it is shown that neural networks are faster and relatively better than other machine learning algorithms explored in this study. The proposed correlation can map non-linear relationships between polymer viscosity and other rheological parameters such as molecular weight, polymer concentration, and cation concentration of polymer solution. Lastly, through machine learning validation approach, it was possible to examine feasibility of the proposed models which is not done by traditional empirical equations.

Влияние полимеров и сополимеров олефинов на турбулентное течение углеводородных жидкостей

Drag reducing additives (DRA) are widely used to increase the pipeline capacity in oil and refined products transit. Introducing DRA at a rate of 1–5 ppm results in considerable lowering of pumping energy. To predict the capability of concerned polymer as a DRA we tried to give an effectiveness theoretical justification in terms of its chemical composition. It was shown that the most effective oil-soluble polymers relate to higher poly(1-alkenes) of superhigh molecular weight (M > 106). Additionally, the nature of the solvent is of importance. 1-Hexene polymerization in the presence of Zigler–Natta catalysts gives a super high molecular weight polymer which is the most effective drag reducer among the higher poly(1-alkenes). But if environment provide some limitation in poly(1-hexene) solubility, such as temperature lowering, or asphaltene content increasing the (co)polymers of 1-octene and 1-decene become the best. Для интенсификации перекачки нефти и нефтепродуктов по магистральным трубопроводам в настоящее время широко используют противотурбулентные присадки, при введении которых в турбулентный поток в предельно малой концентрации (C = 1–5 г/м3) наблюдается уменьшение энергетических затрат на транспортировку углеводородной жидкости. С целью прогнозирования перспективы промышленного использования присадки той или иной химической природы в настоящей работе представлено теоретическое обоснование и экспериментальное подтверждение эффективности различных полимеров. Установлено, что из всех нефтерастворимых полимеров наилучшими противотурбулентными свойствами обладают высшие поли-α-олефины со сверхвысокой молекулярной массой (Мr > 1·106). Также выявлено влияние компонентного состава и термодинамического качества растворителя на эффективность присадок, причем эти факторы следует рассматривать в совокупности. Например, цепь полимера, обогащенная гексеном, при прочих равных условиях синтеза имеет большую молекулярную массу, и такой полимер в хорошем растворителе снижает сопротивление лучше своих аналогов. Тем не менее, если превалируют факторы, ограничивающие растворимость полигексена (низкая температура, обилие асфальтенов в нефти), предпочтительными оказываются полимеры и сополимеры октена и децена, имеющие более низкую температуру стеклования.

Development of poly(ethyleneimine) grafted amphiphilic copolymers: Evaluation of their cytotoxicity and ability to complex DNA

Poly(ethyleneimine) (PEI) is one of the most widely used cationic polymers for gene delivery. The high molecular weight polymer, which is commercially available, is highly efficient but also very cytotoxic. The reduction in charge density by using nonlinear architectures based on low molecular weight (LMW) PEI is a promising approach to produce safer DNA-vectors. Herein, a group of cationic graft copolymers with different composition containing a hydrophobic biocompatible backbone and LMW linear PEI (lPEI) grafts obtained by ring opening polymerization and click chemistry was studied. The self-assembly and DNA complexation behavior of these materials was analyzed by the gel retardation assay, zeta potential measurements, and dynamic light scattering. The copolymers formed positively charged particles in water with average sizes between 270 and 377 nm. After they were added to DNA in serum-free medium, these particles acquired negative/near-neutral charges and increased in size depending on the N/P ratio. All copolymers showed reduced cytotoxicity compared to the 25 kDa lPEI used as reference, but the transfection efficiency was reduced. This result suggested that the cationic segments were too small to fully condense the DNA and promote cellular uptake, even with the use of several grafts and the introduction of hydrophobic domains. The trends found in this research showed that a higher degree of hydrophobicity and a higher grafting density can enhance the interaction between the copolymers and DNA. These trends could direct further structural modifications in the search for effective and safe vectors based on this polycation.

Surfactant-Polymer Formulations for EOR in High Temperature High Salinity Carbonate Reservoirs

Harsh conditions, such as high temperature (>100 oC) and high salinity (>50,000 ppm TDS), can make the application of chemical enhanced oil recovery (EOR) challenging by causing many surfactants and polymers to degrade. Carbonate reservoirs also tend to have higher concentrations of divalent cations as well as positive surface charges that contribute to chemical degradation and surfactant adsorption. The objective of this work is to develop a surfactant-polymer (SP) formulation that can be injected with available hard brine, achieve ultra-low IFT in these harsh conditions, and yield low surfactant retention. Phase behavior experiments were performed to identify effective SP formulations. A combination of anionic and zwitterionic surfactants, cosolvents, brine, and oil was implemented in these tests. High molecular weight polymer was used in conjunction with the surfactant to provide a high viscosity and stable displacement during the chemical flood. Effective surfactant formulations were determined and five chemical floods were performed to test the oil recovery potential. The first two floods were performed using sandpacks from ground Indiana limestone while the other three floods used Indiana limestone cores. The sandpack experiments showed high oil recovery proving the effectiveness of the formulations, but the oil recovery was lower in the cores due to complex pore structure. The surfactant retention was high in the sandpacks, but it was lower in Indiana Limestone cores (0.29-0.39 mg/gm of rock). About 0.4 PV of surfactant slug was enough to achieve the oil recovery. A preflush of sodium polyacrylate improved the oil recovery.

Variable Molecular Weight Polymer Nanoparticles for Detection and Hyperthermia-Induced Chemotherapy of Colorectal Cancer

Oxaliplatin plays a significant role as a chemotherapeutic agent for the treatment of colorectal cancer (CRC); however, oxaliplatin-resistant phenotypes make further treatment challenging. Here, we have demonstrated that rapid (60 s) hyperthermia (42 °C), generated by the near-infrared stimulation of variable molecular weight nanoparticles (VMWNPs), increases the effectiveness of oxaliplatin in the oxaliplatin-resistant CRC cells. VMWNP-induced hyperthermia resulted in a higher cell death in comparison to cells exposed to chemotherapy at 42 °C for 2 h. Fluorescence from VMWNPs was observed inside cells, which allows for the detection of CRC. The work further demonstrates that the intracellular thermal dose can be determined using cell luminescence and correlated with the cell viability and response to VMWNP-induced chemotherapy. Mild heating makes oxaliplatin-resistant cancer cells responsive to chemotherapy, and the VMWNPs-induced hyperthermia can induce cell death in a few minutes, compared to classical bulk heating. The results presented here lay the foundation for photothermal polymer nanoparticles to be used for cell ablation and augmenting chemotherapy in drug-resistant colorectal cancer cells.

A Comparative Study on the Role of Polyvinylpyrrolidone Molecular Weight on the Functionalization of Various Carbon Nanotubes and Their Composites

Polyvinylidene fluoride (PVDF) nanocomposites filled with polyvinylpyrrolidone (PVP) wrapped carbon nanotubes were prepared via a solution casting technique. The effect of the molecular weight (polymer chain length) of the PVP on the ability to wrap different nanotube structures and its impact towards nanotube dispersibility in the polymer matrix was explored. The study was conducted with PVP of four different molecular weights and nanotubes of three different structures. The composites that exhibit an effective nanotube dispersion lead to a nanotube network that facilitates improved thermal, electrical, and mechanical properties. It was observed that nanotubes of different structures exhibit stable dispersions in the polymer matrix though PVP functionalization of different molecular weights, but the key is achieving an effective nanotube dispersion at low PVP concentrations. This is observed in MWNT and AP-SWNT based composites with PVP of low molecular weight, leading to a thermal conductivity enhancement of 147% and 53%, respectively, while for P3-SWNT based composites, PVP of high molecular weight yields an enhancement of 25% in thermal conductivity compared to the non-functionalized CNT-PVDF composite.

The Food Additive Xanthan Gum Drives Adaptation of the Human Gut Microbiota

The diets of industrialized countries reflect the increasing use of processed foods, often with the introduction of novel food additives. Xanthan gum is a complex polysaccharide with unique rheological properties that have established its use as a widespread stabilizer and thickening agent1. However, little is known about its direct interaction with the gut microbiota, which plays a central role in digestion of other, chemically-distinct dietary fiber polysaccharides. Here, we show that the ability to digest xanthan gum is surprisingly common in industrialized human gut microbiomes and appears to be contingent on the activity of a single bacterium that is a member of an uncultured bacterial genus in the family Ruminococcaceae. We used a combination of enrichment culture, multi-omics, and recombinant enzyme studies to identify and characterize a complete pathway in this uncultured bacterium for the degradation of xanthan gum. Our data reveal that this keystone degrader cleaves the xanthan gum backbone with a novel glycoside hydrolase family 5 (GH5) enzyme before processing the released oligosaccharides using additional enzymes. Surprisingly, some individuals harbor a Bacteroides species that is capable of consuming oligosaccharide products generated by the keystone Ruminococcaceae or a purified form of the GH5 enzyme. This Bacteroides symbiont is equipped with its own distinct enzymatic pathway to cross-feed on xanthan gum breakdown products, which still harbor the native linkage complexity in xanthan gum, but it cannot directly degrade the high molecular weight polymer. Thus, the introduction of a common food additive into the human diet in the past 50 years has promoted the establishment of a food chain involving at least two members of different phyla of gut bacteria.

PolyMaS: A new software to generate high molecular weight polymer macromolecules from repeating structural units

The Polymer Maker SMILES-based (PolyMaS) software was used to generate linear macromolecules from the repeating structural units (SRU) of polymers without limiting their length and molar mass. The SRU input is stored in the SMILES code available on the Internet. PolyMaS makes head-tail junctions to the desired length of the macromolecule.