Warm Solvent Research Articles

A dynamic solvent chamber propagation estimation framework using RNN for warm solvent injection in heterogeneous reservoirs

Warm solvent injection (WSI), injecting low-temperature solvent into formations to reduce the viscosity of heavy oil, is a clean technology for heavy oil production through reducing greenhouse gas emissions and water usage. The success of WSI operation depends on the uniform development and propagation of solvent chambers in reservoirs. However, reservoir heterogeneity stemming from shale barriers plays a detrimental role in the conformance of solvent chamber development and oil production rate. In this work, we developed a novel recurrent neural network (RNN)-based framework with the capability of efficiently tracking and estimating the solvent chamber positions in heterogeneous reservoirs based on only production time-series data. The developed estimation model utilizes the “sequence-to-sequence" mapping methodology to correlate observed production time-series sequence and solvent chamber edge sequence via a long short-term memory (LSTM) algorithm. The trained RNN models exhibit high accuracy, evidenced by the predicted dynamic solvent chamber locations match the corresponding true locations from numerical simulation, with a high coefficient of determination (R2) and a low mean squared error. Specifically, the achieved R2 values exceed 0.98 on both the training and testing data. The developed RNN-based workflow was tested via several cases from both regularly- and irregularly-shaped shale barriers, and the results were promising. The predicted solvent chambers showed strong agreement with those obtained from numerical simulations. The major benefits of this workflow include reducing computational time and saving overall monitoring and tracking costs for conventional techniques. The present work would provide a good demonstration of the capability of practical integration of machine learning methods in solving engineering problems.

3D conductive monolithic carbons from pyrolyzed bamboo for microfluidic self-heating system

Bamboo, like wood, is a promising natural template for biobased devices that takes advantage of its hierarchical architecture, microarray channels, anisotropic mechanical and electrical properties. Herein we report a low heat thermal treatment (HTT, 700-1000 °C) of natural bamboo specimens to obtain bamboo-based graphitic devices with thermoelectric and electrochemical properties. The preservation of the highly anisotropic architecture of three-dimensional carbon material (3D-CM) allowed adding specific thermoelectric and electrochemical properties depending on the HTT of the pristine specimens. High electric conductivity (σ, 839 S/m) was observed at 1000 °C showing a remarkable potential application as a bamboo-based working electrode. The bamboo annealed to 700 °C showed higher resistivity (ρ, 0.15 Ω m, and σ, 6.6 S/m), thermal conductivity (1.77 W/m K), and thermal heating rate (1.0 °C/s). The pyrolyzed biomass (B-700) was used as a 3D microfluidic heater to heat polar solvents (H2O and ethylene glycol) in flow mode up to their boiling points. A 2D carbon hotplate heater was built-up to warm solvent in batch mode. A complete chemical and physical characterization of the samples allowed us to determine structural and chemical compositions, cellulose crystalline structure phase transition to graphitic/turbostratic carbon, thermal and electrical conductivity of unprecedented bambootronics bio-devices.

Statistical upscaling workflow for warm solvent injection processes – Longitudinal and transverse dispersivity and thermal conductivity

Accurately simulating, upscaling, and optimizing the warm solvent injection process (WSI) is challenging due to its complex heat and mass transfer mechanisms. This manuscript presents a comprehensive two-step flow-based upscaling workflow designed explicitly for WSI simulation in heterogeneous reservoirs. The technique builds upon previous research on particle transport in single-phase flow and extends the upscaling method to incorporate multiple correlated properties relevant to the process physics. Specifically, the upscaling methodology considers the correlation between longitudinal and transverse dispersivities. The influence of scale variation on thermal conductivity is examined. The proposed statistical upscaling technique does not rely on explicit assumptions about the distribution of heterogeneity. The results highlight the directionality in dispersivity. Due to the limited temperature variation observed in the case study, upscaling thermal conductivity has little impact. The method's efficiency can be verified by coarser model simulations that capture similar fine-scale model responses with less computational run time.

Improving the extraction of guayulins from guayule stems (Parthenium argentatum A. Gray)

Guayule (Parthenium argentatum A. Gray) exploitation has so far been focused on the production of rubber, but until now was unable to compete commercially, as other guayule co-products have not been equally considered for exploitation. However, to successfully exploit one of these co-products, the guayulins, it will be necessary to establish a robust resin extraction method that maximizes the yield of guayulin compounds for downstream purification. For this purpose, different resin extraction conditions (solvent, temperature, number and time of cycles, and plant material:solvent ratio) were evaluated to select those that produced a resin with a higher guayulins yield. First, accelerated solvent extraction (ASE) was performed using three solvents (ethanol, acetonitrile, and acetone) at three different temperatures (40, 56, and 80 °C) and two cycle times (5 and 20 min) to narrow down the conditions. Then, an industrial scale process was simulated with warm solvent extraction (WSE) using acetone and acetonitrile only at five different cycle times (30, 45, 60, 120, and 180 min). Finally, WSE performance was optimized using four different plant material:solvent ratios (1:20, 1:10, 1:5, and 1:3), and three consecutive extraction cycles. Results from the ASE studies revealed, as expected, that solvent choice had the greatest influence on resin and guayulins yield and allowed to discard ethanol as a suitable extraction solvent while acetonitrile performed best for guayulin extraction. No tangible differences in resin yield were observed in WSE studies between the different process parameters, but they were differences in guayulin extraction. Short cycle times worked best with both solvents, and again, acetonitrile was more selectively extracted guayulins, especially for the polar guayulins C and D. Finally, WSE optimization showed that a 1:5 plant material:solvent ratio and two extraction cycles were the best compromise in terms of guayulins yield and time/cost effectiveness.

Efficient tracking and estimation of solvent chamber development during warm solvent injection in heterogeneous reservoirs via machine learning

Warm solvent injection (WSI) has been proposed as a promising alternative to steam-based methods for bitumen recovery, due to its potential to reduce greenhouse gas emissions and environmental footprint. It involves injecting heated vaporized solvent to reduce the viscosity of bitumen via solvent diffusion and latent heat transfer. The presence of reservoir heterogeneity caused by shale barriers is a severe concern for the success of the WSI because the conformance of solvent chamber advancement can be compromised. However, the efficient estimation and tracking methods for solvent chamber growth and propagation in heterogeneous reservoirs have not been widely investigated in the past. To fill this gap, this work proposes a novel machine learning-based approach to efficiently track solvent chamber positions in heterogeneous reservoirs for the WSI process. From a large training dataset consisting of numerous synthetic heterogeneous models and their simulation results, the input features and output parameters are extracted from oil production time-series data and the dynamic evolution of solvent chamber, respectively. A convolutional neural network (CNN) is implemented to dynamically track solvent chamber positions by correlating the extracted inputs and outputs. The estimation results are reliable and accurate for both scenarios where the shale barriers are either regularly or irregularly shaped with high conformance index (CI). Only production data is used to assess the conformance of solvent chamber advancement, which is an important consideration in operations design and real-time optimization. The presented workflow offers a novel alternative to infer the development of solvent chambers in heterogeneous reservoirs from production time-series data directly. This type of analysis could complement many existing monitoring techniques to deliver a more comprehensive inference of the distribution of shale heterogeneities in solvent-based bitumen recovery operations.

A Statistical Upscaling Workflow for Warm Solvent Injection Processes for Heterogeneous Heavy Oil Reservoirs

A Statistical Upscaling Workflow for Warm Solvent Injection Processes for Heterogeneous Heavy Oil Reservoirs

Design of warm solvent injection processes for heterogeneous heavy oil reservoirs: A hybrid workflow of multi-objective optimization and proxy models

Injection of warm solvent vapor into the formation is often considered as a cleaner alternative for heavy oil production. However, the design of relevant operational conditions is challenging, as it involves the optimization of multiple distinct objectives including oil production and solvent-oil-ratio (solvent usage efficiency). This work develops a hybrid optimization framework involving Pareto-based multiple-objective optimization (MOO) techniques for the design of warm solvent injection (WSI) operations in heterogeneous reservoirs. First, a set of synthetic models are constructed based on field data gathered from several typical Athabasca oil sands reservoirs. Models with different heterogeneity settings and the impact of solution gas on WSI production are examined. Next, non-dominated sorting genetic algorithm II (NSGA-II), is employed to optimize two operational parameters, i.e., bottom-hole pressures, based on multiple design objectives. Several proxy models are integrated into the optimization workflow to evaluate the objective functions at reduced computational costs. The performance of the proposed workflow is validated via both homogeneous and heterogeneous cases, and it is demonstrated that a set of Pareto-optimal operating conditions for different reservoir settings can be obtained. The results reveal that the optimal bottom-hole pressure of the producer should be kept at a minimum, while there is more flexibility in the injection bottom-hole pressure. Compared with other conventional optimization strategies, the proposed workflow requires fewer costly simulations and facilitates the optimization of multiple objectives simultaneously. The result demonstrated a great potential for extending the developed MOO framework to optimize operational conditions for other natural resource extraction processes.

Evaluation of the impact of pre-treatment and extraction conditions on the polyphenolic profile and antioxidant activity of Belgium apple wood

This study describes the possibilities of valorising a waste stream that originates from apple wood by mapping the reducing capacity and phenolic profile from extracts derived from apple tree (Malus domestica). This study evaluated the efficiency of warm solvent extraction (WSE) and ultrasound-assisted extraction (UAE) techniques for extracting antioxidant phenolic compounds from the bark and core wood of an apple tree cultivated in the north-eastern part of Belgium. Furthermore, the influence of the pre-treatment technique, namely, fresh, oven-dried, and freeze-dried samples, respectively, on the yield of polyphenols was studied. Fresh bark extract obtained by UAE—the most efficient extraction technique—employing acetone 60% v/v contains the highest levels of phenolic compounds as well as the highest antioxidant activity. High-performance liquid chromatographic analysis shows that phloridzin is the major compound of the identified polyphenol markers present in bark and core wood extracts. Based on the obtained results, it may be possible to produce a polyphenolic extract from apple wood at an industrial scale without extensive costs or altering the antioxidant properties. This study reveals the potential of apple tree wood residues valorisation through the recovery of phenolic compounds for food, pharmaceutical, and cosmetic applications.

Phenolic Composition, Antimicrobial and Antioxidant Properties of Belgian Apple Wood Extracts

Each year, fruit growers have hundreds of tons of bark and pruning waste. Despite their potential for chemical recycling, residues from this waste are frequently used for applications with low added value. By converting the waste stream into a valuable source, this study emphasizes waste valorisation and engenders re-use strategies for the production of higher value products. The aim of the present work is the optimization of the solvent extraction of phenolic compounds from apple trees, more specifically bark and core wood. Solvent extractions, with a varying solvent composition, are assessed based on the extraction efficiency of the total polyphenols and flavonoids (spectrophotometry). The extracts are further characterized by their antimicrobial properties and antioxidant activities. Bark extracts obtained by a 40 v/v % acetone/ water mixture presented the highest phenolic (22.84 ± 0.56 mg GAE/g DW) and flavonoid (12.16 ± 0.06 mg QC/g DW) content, and antioxidant activity (1.068 ± 0.005 mM FeSO4.7H2O/g DW for the FRAP assay), while the extract also inhibited growth of the gram-positive bacteria Enterococcus faecalis and Staphylococcus aureus by 100 %. The results indicate that warm solvent extraction (WSE) proved to be an efficient way to extract polyphenols with a high reducing ability from bark and core wood of apple trees.

Testing signal enhancement mechanisms in the dissolution NMR of acetone

In cryogenic dissolution NMR experiments, a substance of interest is allowed to rest in a strong magnetic field at cryogenic temperature, before dissolving the substance in a warm solvent, transferring it to a high-resolution NMR spectrometer, and observing the solution-state NMR spectrum. In some cases, negative enhancements of the 13C NMR signals are observed, which have been attributed to quantum-rotor-induced polarization. We show that in the case of acetone (propan-2-one) the negative signal enhancements of the methyl 13C sites may be understood by invoking conventional cross-relaxation within the methyl groups. The 1H nuclei acquire a relative large net polarization through thermal equilibration in a magnetic field at low temperature, facilitated by the methyl rotation which acts as a relaxation sink; after dissolution, the 1H magnetization slowly returns to thermal equilibrium at high temperature, in part by cross-relaxation processes, which induce a transient negative polarization of nearby 13C nuclei. We provide evidence for this mechanism experimentally and theoretically by saturating the 1H magnetization using a radiofrequency field pulse sequence before dissolution and comparing the 13C magnetization evolution after dissolution with the results obtained from a conventional 1H-13C cross relaxation model of the CH3 moieties in acetone.

Dynamic Nuclear Polarization of Long-Lived Nuclear Spin States in Methyl Groups.

We have induced hyperpolarized long-lived states in compounds containing 13C-bearing methyl groups by dynamic nuclear polarization (DNP) at cryogenic temperatures, followed by dissolution with a warm solvent. The hyperpolarized methyl long-lived states give rise to enhanced antiphase 13C NMR signals in solution, which often persist for times much longer than the 13C and 1H spin-lattice relaxation times under the same conditions. The DNP-induced effects are similar to quantum-rotor-induced polarization (QRIP) but are observed in a wider range of compounds because they do not depend critically on the height of the rotational barrier. We interpret our observations with a model in which nuclear Zeeman and methyl tunnelling reservoirs adopt an approximately uniform temperature, under DNP conditions. The generation of hyperpolarized NMR signals that persist for relatively long times in a range of methyl-bearing substances may be important for applications such as investigations of metabolism, enzymatic reactions, protein-ligand binding, drug screening, and molecular imaging.

Block Copolymer with an Extremely High Block-to-Block Interaction for a Significant Reduction of Line-Edge Fluctuations in Self-Assembled Patterns

Directed self-assembly (DSA) of block copolymers (BCPs) with a high Flory–Huggins interaction parameter (χ) provides advantages of pattern size reduction below 10 nm and improved pattern quality. Despite theoretical predictions, however, the questions of whether BCPs with a much higher χ than conventional high-χ BCPs can further improve the line edge roughness (LER) and how to overcome their extremely slow self-assembly kinetics remain unanswered. Here, we report the synthesis and assembly of poly(4vinylpyridine-b-dimethylsiloxane) BCP with an extremely high χ-parameter (estimated to be approximately 7 times higher compared to that of poly(styrene-b-dimethylsiloxane) – a conventional high-χ BCP) and achieve a markedly low 3σ line edge roughness of 0.98 nm, corresponding to 6% of its line width. Moreover, we demonstrate the successful application of an ethanol-based 60 °C warm solvent annealing treatment to address the extremely slow assembly kinetics of the extremely high-χ BCP, considerably reducing the ...

Enhancement of quantum rotor NMR signals by frequency-selective pulses

Quantum-rotor-induced polarisation (QRIP) enhancement is exhibited by substances which contain freely rotating methyl groups in the solid state, provided that the methyl groups contain a 13C nucleus. Strong signal enhancements are observed in solution NMR when the material is first equilibrated at cryogenic temperatures, then rapidly dissolved with a warm solvent and transferred into an NMR magnet. QRIP leads to strongly-enhanced 13C NMR signals, but relatively weak enhancements of the 1H signals. We show that the 1H signals suffer from a partial cancellation of degenerate contributions, which may be corrected by applying a frequency-selective π pulse to the inner peaks of the 13C multiplet prior to 1H observation.

Eliminating the Trade‐Off between the Throughput and Pattern Quality of Sub‐15 nm Directed Self‐Assembly via Warm Solvent Annealing

The directed self‐assembly (DSA) of block copolymers (BCPs) has been suggested as a promising nanofabrication solution. However, further improvements of both the pattern quality and manufacturability remain as critical challenges. Although the use of BCPs with a high Flory‐Huggins interaction parameter (χ) has been suggested as a potential solution, this practical self‐assembly route has yet to be developed due to their extremely slow self‐assembly kinetics. In this study, it is reported that warm solvent annealing (WSA) in a controlled environment can markedly improve both the self‐assembly kinetics and pattern quality. A means of avoiding the undesirable trade‐off between the quality and formation throughput of the self‐assembled patterns, which is a dilemma which arises when using the conventional solvent vapor treatment, is suggested. As a demonstration, the formation of well‐defined 13‐nm‐wide self‐assembled patterns (3σ line edge roughness of ≈2.50 nm) in treatment times of 0.5 min (for 360‐nm‐wide templates) is shown. Self‐consistent field theory (SCFT) simulation results are provided to elucidate the mechanism of the pattern quality improvement realized by WSA.

Solvent Injection Strategy for Low-Temperature Production from Fractured Viscous Oil Reservoirs

Viscous oil resources have great potential to help meet the future demand for petroleum products as conventional resources are depleted. Currently high temperature steam injection is the recovery process of choice, with high energy intensity and associated greenhouse gas emissions. The work presented here explores a low-temperature solvent-only injection strategy targeting fractured systems. The warm solvent is in the vapor phase when injected into the reservoir but will condense when it contacts the cold oil and reservoir rock (liquid extraction). After the system has reached the target operating temperature, the injected solvent remains in the vapor phase when it contacts the oil (solvent-enhanced gravity drainage). The experiments discussed in this work explore the key parameters (permeability, temperature/pressure, in situ injection rate, and solvent type) that influence each production mechanism. The primary impact of decreasing permeability is a proportional decrease in film gravity drainage rate. A decrease in temperature slows the mass transfer during the liquid extraction phase and decreases the drainage rate during the film gravity drainage phase. Increasing the in situ injection rate leads to improved liquid extraction because of higher concentration gradient in the solvent-rich liquid phase at the oil/solvent interface. Solvent type affects both mechanisms and changes the nature and amount of asphaltene precipitation. Pentane yields relatively less asphaltene precipitate than butane (18 wt % vs 11 wt % asphaltene content in residual oil). Residual oil saturation was observed to increase as permeability and/or temperature were decreased.

Leaf anatomy affects the extraction of photosynthetic pigments by DMSO

Dimethylsulfoxide (DMSO) is a widely used solvent for the extraction of chlorophylls (Chls) from leaves of higher plants. The method is preferred because the time-consuming steps of grinding and centrifuging are not required and the extracts are stable for a long time period. However, the extraction efficiency of this solvent is not comparable among plant species, whereas the particular leaf anatomical characteristics responsible for this unevenness remain unknown. In order to examine the influence of leaf anatomy on the extraction efficiency of DMSO (i.e. the concentration of Chls extracted with DMSO as % of the concentration of Chls extracted with 80% acetone), leaves of 19 plant species with different anatomical characteristics were incubated for 40 min in DMSO at 65 °C. Under these conditions, heterobaric leaves, which are characterized by the occurrence of bundle sheath extensions in the mesophyll, showed lower extraction efficiency of DMSO compared to homobaric leaves and conifer needles. Microscopical observations of DMSO incubated leaf tissues showed that bundle sheath extensions behave as anatomical barriers which prevent the diffusion of DMSO within heterobaric leaves, even after prolonged incubation with the solvent. The effect was stronger in heterobaric leaves possessing thick bundle sheath extensions. The extraction efficiency of DMSO in these leaves was improved by vacuum infiltration of the samples in the presence of warm (65 °C) solvent.

Identification and quantification of C21 steroidal saponins from radix cynanchi atrati by high‐performance liquid chromatography with evaporative light scattering detection and electrospray mass spectrometric detection

High-performance liquid chromatography coupled with electrospray tandem mass spectrometry (HPLC-ESI/MS) and evaporative light scattering detection (HPLC-ELSD), respectively, has been performed for the simultaneous identification and quantification of six C(21) steroid saponins, including cynanversicoside A, B, D, G, glaucoside C and glaucogenin C-3-O-beta-d-thevetopyranoside in Radix Cynanchi Atrati. The extraction of the C(21) steroidal saponins was performed using a B-811 Buchi Universal Extraction System in Warm Solvent Mode, and the analyte was concentrated by column chromatography before HPLC analysis. The chromatographic separation was performed on an Agilent Zorbax Extend C(18) analytical column efficiently using gradient elution with acetonitrile and water. The method was validated with acceptable linearities (r > 0.9991) and recoveries (98.2-101.3%). The limits of detection of the C(21) steroid saponins were from 0.2 microg for glaucogenin C-3-O-beta-d-thevetopyranoside to 0.5 microg for cynanversicoside B. The intra- and inter-day precisions of the method were evaluated and were less than 5.0%. The method was successfully used to analyse 20 batches of Radix Cynanchi Atrati. The content of C(21) steroid saponins in the plant material varied significantly from habitat to habitat, confirming the necessity to control the quality of Radix Cynanchi Atrati during its preparation and application in the clinic.

Generating highly polarized nuclear spins in solution using dynamic nuclear polarization

A method to generate strongly polarized nuclear spins in solution has been developed, using Dynamic Nuclear Polarization (DNP) at a temperature of 1.2 K , and at a field of 3.354 T , corresponding to an electron spin resonance frequency of 94 GHz . Trityl radicals are used to directly polarize 13 C and other low-γ nuclei. Subsequent to the DNP process, the solid sample is dissolved rapidly with a warm solvent to create a solution of molecules with highly polarized nuclear spins. Two main applications are proposed: high-resolution liquid state NMR with enhanced sensitivity, and the use of the hyperpolarized solution as an MR imaging agent.

Fuels and chemicals from sewage sludge: 1. The solvent extraction and composition of a lipid from a raw sewage sludge

With the objective of producing a low-nitrogen and low-sulphur-containing substrate for pyrolysis to liquids, the lipid fraction of a dried raw Atlanta sludge was extracted with both chloroform and toluene. Although the solvents proved equally good for extraction of lipids, toluene is preferred because the pyrolysis of any residual chloroform in the extractive could present environmental problems. In Soxhlet extraction warm solvent removed about 12 wt% lipid whereas extraction by contact with boiling solvent gave 17–18 wt% lipid. Soxhlet extraction of the sludge resulted in 99.5% rejection of nitrogen and 94% rejection of sulphur. Boiling extraction rejected 99% nitrogen and 84% sulphur. The Soxhlet extract contained 10–13% oxygen whereas boiling extraction gave a lipid containing 14–16% oxygen. On a moisture-free basis, the recovered lipid, 91%, from the separation of the toluene extract was comprised of 65% free fatty acids, 7% glyceride fatty acids and 28% unsaponifiable material. The unsaponifiable matter had a distribution of alkanes ranging from C9 to C16, n-nonane and n-pentadecane being the major hydrocarbons present. The free fatty acid esters and the glyceride fatty acid esters had a distribution of fatty acids ranging from C12 to C18. Palmitic, stearic and oleic acids appeared to be the major fatty acids present. These results are significant for the catalytic thermal liquefaction of sewage sludge lipids for the production of fuel and chemical feedstocks.

Oxidation of Cyclohexane by Lead Tetra-acetate

POSSIBLY because of displacement by apparently more attractive substrates, the reactions of lead tetra-acetate with simple paraffins has not received much attention. Earlier discussions1,2 suggested that reaction in warm solvent was not likely although the promoting effect of paraffins on the thermal decomposition of the reagent in hot acetic acid had been noted3. Recently slow reaction with alkyl and arylcyclopropanes has been reported4.