Recovery Processing Research Articles

Treatment of temporal aliasing effects in the context of next generation satellite gravimetry missions

AbstractTemporal aliasing effects have a large impact on the gravity field accuracy of current gravimetry missions and are also expected to dominate the error budget of Next Generation Gravimetry Missions (NGGMs). This paper focuses on aspects concerning their treatment in the context of Low‐Low Satellite‐to‐Satellite Tracking NGGMs. Closed‐loop full‐scale simulations are performed for a two‐pair Bender‐type Satellite Formation Flight (SFF), by taking into account error models of new generation instrument technology. The enhanced spatial sampling and error isotropy enable a further reduction of temporal aliasing errors from the processing perspective. A parameterization technique is adopted where the functional model is augmented by low‐resolution gravity field solutions coestimated at short time intervals, while the remaining higher‐resolution gravity field solution is estimated at a longer time interval. Fine‐tuning the parameterization choices leads to significant reduction of the temporal aliasing effects. The investigations reveal that the parameterization technique in case of a Bender‐type SFF can successfully mitigate aliasing effects caused by undersampling of high‐frequency atmospheric and oceanic signals, since their most significant variations can be captured by daily coestimated solutions. This amounts to a “self‐dealiasing” method that differs significantly from the classical dealiasing approach used nowadays for Gravity Recovery and Climate Experiment processing, enabling NGGMs to retrieve the complete spectrum of Earth's nontidal geophysical processes, including, for the first time, high‐frequency atmospheric and oceanic variations.

Climate impacts of oil extraction increase significantly with oilfield age

The footprint of oil typically considers combustion emissions, neglecting extraction emissions. This study shows that production declines with depletion for 25 significant oil fields, whilst emissions increase through greater energy expenditure. Record-breaking temperatures1 have induced governments to implement targets for reducing future greenhouse gas (GHG) emissions2,3. Use of oil products contributes ∼35% of global GHG emissions4, and the oil industry itself consumes 3–4% of global primary energy. Because oil resources are becoming increasingly heterogeneous, requiring different extraction and processing methods, GHG studies should evaluate oil sources using detailed project-specific data5. Unfortunately, prior oil-sector GHG analysis has largely neglected the fact that the energy intensity of producing oil can change significantly over the life of a particular oil project. Here we use decades-long time-series data from twenty-five globally significant oil fields (>1 billion barrels ultimate recovery) to model GHG emissions from oil production as a function of time. We find that volumetric oil production declines with depletion, but this depletion is accompanied by significant growth—in some cases over tenfold—in per-MJ GHG emissions. Depletion requires increased energy expenditures in drilling, oil recovery, and oil processing. Using probabilistic simulation, we derive a relationship for estimating GHG increases over time, showing an expected doubling in average emissions over 25 years. These trends have implications for long-term emissions and climate modelling, as well as for climate policy.

Selenium and molybdenum enrichment in uranium roll-front deposits of Wyoming and Colorado, USA

Sandstone uranium (U) roll-front deposits of Wyoming and Colorado (USA) are important U resources, and may provide a terrestrial source for critical accessory elements, such as selenium (Se), molybdenum (Mo), and tellurium (Te). Due to their associated toxicity, MoSeTe occurrences in roll-fronts should also be carefully monitored during U leaching and ore processing. While elevated MoSe concentrations in roll-fronts are well established, very little is known about Te occurrence in such deposits. This study aims to establish MoSeTe concentrations in Wyoming and Colorado roll-fronts, and assess the significance of these deposits in an environmental and mineral exploration context.Sampled roll-front deposits, produced by oxidized groundwater transportation through a sandstone, show high MoSe content in specific redox zones, and low Te, relative to crustal means. High Se concentrations (up to 168ppm) are restricted to a narrow band of alteration at the redox front. High Mo content (up to 115ppm) is typically associated with the reduced mineralized nose and seepage zones of the roll-front, ahead of the U orebody. Elevated trace element concentrations are likely sourced from proximal granitic intrusions, tuffaceous deposits, and local pyritic mudstones. Elevated MoSe content in the sampled roll fronts may be regarded as a contaminant in U in-situ recovery and leaching processing, and may pose an environmental threat in groundwaters and soils, so extraction should be carefully monitored. The identification of peak concentrations of MoSe can also act as a pathfinder for the redox front of a roll-front, and help to isolate the U orebody, particularly in the absence of gamma signatures.

IMPROVEMENT OF DEEP PROCESSING TECHNIQUES FOR WASTE OF STEEL-MELTING PRODUCTION. PART 1. THERMODYNAMIC ANALYSIS

The problem of using dump slag in steelmaking production as an industrial source of metallurgical raw materials still has no practical decision and it demands new approaches and ideas. Disposal of slag can be organized so that the result is not only building materials, but metal, suitable for further processing and use in recent years are shown. The purpose of the current work is theoretical study of opportunity and feasibility of steel-melting slag recovery processing to receive metal and oxide phases, which can be used in metallurgy and construction industry. The object of the experimental study was the slag from slag dumps of Zlatoust metallurgical plant (Russian Federation). The programming complex “FactSage” (version 6.4) was used for thermodynamic modeling of the recovery processes of slag dumps. Slag recovery of three diff erent compositions with diff erent content of FeO (15, 10 and 5 wt.%) was modeled. Modeling was performed for the temperature range of 750–1650 °C in step of 5 °C at the pressure gas phase, equal to 0.1 MPa. Excessive amounts of carbon were introduced into the system as a reducing agent in the modeling. The main results of the calculations carried-out for convenience of the analysis are shown in the form of dependences of various characte ristics on temperature. The modeling results show in particular that at temperatures above 1340 °C the iron is recovered and goes into the composition of the melt almost completely. Nickel and copper behave similarly. Total recovery of manganese in the composition of the molten metal during the recovery with carbon will not happen. An app reciable amount of manganese remains in the slag composition and gas even at maximum extraction of manganese in the metal. Assessment of the volumes of gaseous substances formed in the process of recovery at diff erent temperatures was carried out. The modeling results indicate that carbon monoxide will dominate the gas phase composition in all the temperature range. Information about the enthalpy change of the system depending on temperature was obtained and allows to assess the costs of thermal energy required to bring the system to the state in which recovery processes become possible.

An Alternative to Conventional Rock Fragmentation Methods Using SCDA: A Review

Global energy and material consumption are expected to rise in exponential proportions during the next few decades, generating huge demands for deep earth energy (oil/gas) recovery and mineral processing. Under such circumstances, the continuation of existing methods in rock fragmentation in such applications is questionable due to the proven adverse environmental impacts associated with them. In this regard; the possibility of using more environmentally friendly options as Soundless Chemical Demolition Agents (SCDAs) play a vital role in replacing harmful conventional rock fragmentation techniques for gas; oil and mineral recovery. This study reviews up to date research on soundless cracking demolition agent (SCDA) application on rock fracturing including its limitations and strengths, possible applications in the petroleum industry and the possibility of using existing rock fragmentation models for SCDA-based rock fragmentation; also known as fracking. Though the expansive properties of SCDAs are currently used in some demolition works, the poor usage guidelines available reflect the insufficient research carried out on its material’s behavior. SCDA is a cementitious powdery substance with quicklime (CaO) as its primary ingredient that expands upon contact with water; which results in a huge expansive pressure if this CaO hydration reaction occurs in a confined condition. So, the mechanism can be used for rock fragmentation by injecting the SCDA into boreholes of a rock mass; where the resulting expansive pressure is sufficient to create an effective fracture network in the confined rock mass around the borehole. This expansive pressure development, however, dependent on many factors, where formation water content creates a negative influence on this due to required greater degree of hydration under greater water contents and temperature creates a positive influence by accelerating the reaction. Having a precise understanding of the fracture propagation mechanisms when using SCDA is important due to the formation of complex fracture networks in rocks. Several models can be found in the literature based on the tangential and radial stresses acting on a rock mass surrounding an SCDA charged borehole. Those fracture models with quasi-static fracturing mechanism that occurs in Mode I type tensile failure show compatibility with SCDA fracturing mechanisms. The effect of borehole diameter, spacing and the arrangement on expansive pressure generation and corresponding fracture network generation is important in the SCDA fracturing process and effective handling of them would pave the way to creating an optimum fracture network in a targeted rock formation. SCDA has many potential applications in unconventional gas and oil recovery and in-situ mining in mineral processing. However, effective utilization of SCDA in such application needs much extensive research on the performance of SCDA with respect to its potential applications, particularly when considering unique issues arising in using SCDA in different applications.

Tissue recovery practices and bioburden: a systematic review.

For successful transplantation, allografts should be free of microorganisms that may cause harm to the allograft recipient. Before or during recovery and subsequent processing, tissues can become contaminated. Effective tissue recovery methods, such as minimizing recovery times (<24 h after death) and the number of experienced personnel performing recovery, are examples of factors that can affect the rate of tissue contamination at recovery. Additional factors, such as minimizing the time after asystole to recovery and the total time it takes to perform recovery, the type of recovery site, the efficacy of the skin prep performed immediately prior to recovery of tissue, and certain technical recovery procedures may also result in control of the rate of contamination. Due to the heterogeneity of reported recovery practices and experiences, it cannot be concluded if the use of other barriers and/or hygienic precautions to avoid contamination have had an effect on bioburden detected after tissue recovery. Qualified studies are lacking which indicates a need exists for evidence-based data to support methods that reduce or control bioburden.Electronic supplementary materialThe online version of this article (doi:10.1007/s10561-016-9590-5) contains supplementary material, which is available to authorized users.

New sustainable approach to reduce cassava borne environmental waste and develop biodegradable materials for food packaging applications

Abstract Transforming waste cassava into a sustainable resource requires a new approach and redesign of the current processing methodologies. Bitter cassava cultivars have been employed mainly as an emergency famine food, but could also be used as a value added material for packaging. Processing of intact bitter cassava can minimize waste, and produce low-cost added value biopolymer packaging films for targeted applications. This study developed an improved simultaneous release, recovery and cyanogenesis (SRRC) downstream processing methodology for sustainable reduction of waste and development of film packaging material using intact bitter cassava. SRRC approach produced peeled (BP) and intact (BI) bitter cassava biopolymer derivatives. BI showed significantly higher yields ensuring 16% waste decrease with no environmental impact caused by discard residues. SRRC was very effective in reducing the total cyanogen content to within Codex minimum safety limits, demonstrating that the peeling of bitter cassava process can be avoided. Transparent films were produced using the casting method from both BP and BI derivatives. BI films were more transparent and homogeneous, less soluble, less permeable to moisture, less hydrophilic, more permeable to oxygen and carbon-dioxide, sealable, lower cost, than the BP. Hence, intact bitter cassava and SRRC can be used as sustainable, safe, integrative process solution for high value-added product (e.g., packaging film) production from low-cost biobased materials.

In-Situ Recovery of Critical Technology Elements

G.U.B. Ingenieur AG in Dresden, Germany, is developing optimized in-situ extraction technologies for critical technology elements, including Rare Earth Elements (REE) Nd, Eu, Tb, Dy, and Y and Cu. We discuss some selected examples of ongoing GUB R&D projects including: (1) In-situ bioleaching of Cu shale-sandstone in an active ∼1km deep shaft mine in Poland, (2) In-situ (bio)leaching and near-surface extraction of REE from ion-adsorption clays (IAC) in Madagascar, and a new project scope (3) REE extraction from secondary phosphate streams. In-situ bioleaching of Cu from deep Cu-shale deposits in Europe allows to retrieve metals like Cu (among other metals) from deep European ore deposits at lower costs. In-situ recovery of REE from IAC deposits is important as such deposits in southern China are the main source of critical technology elements Nd, Eu, Tb, Dy and Y. REE-recovery from secondary phosphate streams is a potential major value-adding step in optimizing the phosphate recovery processing chain, yet it is essential to understand the partitioning of REEs (and NORM including U, Th and their progenies) between phosphogypsum and phosphoric acid in the fertilizer production process. We identified three main REE sinks based on existing phosphate processing chains: (1) Sand, clay and phosphoric tailings hosting ∼40-50% of total REE, (2) phosphogypsum ponds with ∼40% of total REE, and (3) phosphoric acid with dissolved ∼10-20% of total REE. In-situ recovery may potentially recover ∼80-90% of total REE from secondary streams (phosphate tailings and phosphogypsum ponds) whereas ∼10-20% of total REE may potentially be recovered from phosphoric acid and/or tailings eluate by biocomplexation of REE. Modification of the phosphate processing chain may provide additional REE extraction points. The most suitable REE extraction points may also be controlled by NORM separation. We propose a customized R&D program to develop an in-situ recovery technology for in-situ REE recovery from secondary (ex-phosphate) streams, in the framework of a joint company and/or EU-funded R&D project.

冰区溢油漂移及数值模拟方法研究综述

近年来，海上石油勘探和开发活动迅速发展，在石油的开采、储藏、运输过程中，都有可能发生溢油事故，给海洋生物和环境带来严重的危害，同时引起一定的经济损失。另外，海上溢油会经历复杂的物理化学变化，包括蒸发、溶解、乳化、扩散、光学氧化和生物降解等，使溢油性质发生改变，从而影响溢油漂移规律。尤其是在有冰海域，溢油漂移受到冰的限制与影响，溢油漂移范围更难预测，使得对溢油事故的回收处理更为困难。本文针对冰区溢油漂移规律和数值模拟方法进行研究。 In recent years, with the rapid development of offshore oil exploration activities, oil spill accident can occur in the process of oil extraction, storage and transportation, which is seriously harm to marine species and environment and causes economic losses. In addition, oil will experience com-plex physical and chemical changes, including evaporation, dissolution, emulsification, and spreading, oxidation and biological degradation. These progresses change the nature of the oil spill, and influence oil spill drift pattern. Especially in sea with ice existing, oil spill drifting is affected by the restrictions of ice, which make it more difficult to predict oil drift trajectory. Therefore, it is more difficult for oil spill recovery processing. In this paper, oil spill drift rule and numerical simulation method in water with ice covered were studied.

Nonconvex Nonsmooth Low Rank Minimization via Iteratively Reweighted Nuclear Norm.

The nuclear norm is widely used as a convex surrogate of the rank function in compressive sensing for low rank matrix recovery with its applications in image recovery and signal processing. However, solving the nuclear norm-based relaxed convex problem usually leads to a suboptimal solution of the original rank minimization problem. In this paper, we propose to use a family of nonconvex surrogates of L0-norm on the singular values of a matrix to approximate the rank function. This leads to a nonconvex nonsmooth minimization problem. Then, we propose to solve the problem by an iteratively re-weighted nuclear norm (IRNN) algorithm. IRNN iteratively solves a weighted singular value thresholding problem, which has a closed form solution due to the special properties of the nonconvex surrogate functions. We also extend IRNN to solve the nonconvex problem with two or more blocks of variables. In theory, we prove that the IRNN decreases the objective function value monotonically, and any limit point is a stationary point. Extensive experiments on both synthesized data and real images demonstrate that IRNN enhances the low rank matrix recovery compared with the state-of-the-art convex algorithms.

Novel zwitterionic surfactant derived from castor oil and its performance evaluation for oil recovery

Abstract Bio-based surfactants have attracted increasing attention due to their renewable resources and excellent surface properties. Novel zwitterionic surfactant derived from castor oil was prepared using a facile and high-yield route and its performance for oil recovery was also evaluated. The surface tension of the surfactant solution reached 30.7 mN/m at its critical micelle concentration value of 7.08 × 10 −6 mol/L. The interfacial tension between crude oil and water could be reduced to ultra-low value as 5.4 × 10 −3 mN/m at a low dosage of 0.010 g/L in aqueous solution with the absence of any extra alkali. When used as dispersant, the dispersion effectiveness of crude oil was 64.69%. Meanwhile, the bio-based surfactant demonstrated strong electrolyte tolerance, temperature resistance and thermostability, better wetting and foaming performance, which implied bio-based surfactants had great potential to replace traditional petroleum-based surfactants in petroleum industries, in particular, in enhanced oil recovery and oil spill disposal processing.

Network Design and Optimization for Multi-product, Multi-time, Multi-echelon Closed-loop Supply Chain under Uncertainty

This paper proposes the network design and optimization of a multi-product, multi-time, multi-echelon capacitated closed-loop supply chain in an uncertain environment. The uncertainty related to ill-known parameters like product demand, return volume, fraction of parts recovered for different product recovery processes, purchasing cost, transportation cost, inventory cost, processing, and set-up cost at facility centers is handled with fuzzy numbers. A fuzzy mixed-integer linear programming model is proposed to decide optimally the location and allocation of products/parts at each facility, number of products to be remanufactured, number of parts to be purchased from external suppliers and inventory level of products/parts in order to maximize the profit to the organization. The proposed solution methodology is able to generate a balanced solution between the feasibility degree and the degree of satisfaction of the decision maker. The proposed model has been tested with an illustrative example.

Improving processing by adaption to conditional geostatistical simulation of block compositions

One of the key usages of geostatistics has long been the prediction of the spatial structure of orebodies. This is used for the evaluation of resources and/or reserves and for further planning of the mining and beneficiation process schedule. For most applications, and until quite recently, metal grade has been regarded as the central property of study and the main objective has been to distinguish between ore and waste. However, recently other properties have come into focus through better analytical methods, such as automated mineralogy (see e.g. Fandrich et al. 2007), and new geostatistical methods considering more complex information, such as kriging of compositions (Pawlowsky-Glahn and Olea, 2004). Two ores with the same chemical composition can have totally different mineralogies and microfabrics, which will result in different recoveries, energy requirements, or reagent consumptions, thus yielding very different mass streams. An ore is thus no longer understood as represented by a single value element, but through a complex microfabric (Hagni, 2008). This perspective allows quantitative insight into relevant properties of different ore and gangue minerals (Sutherland and Gottlieb, 1991), potentially containing poison elements or phases (e.g. Houot, 1983) that modify the efficiency of downstream processing steps or require additional treatment. Accordingly, processing choices have become more complex. Grade-based studies allow a mere ‘beneficiate-or-dump’ decision. With the advent of these analytical and methodological advances, it is possible to better adapt processing to the ore mined due to a more profound understanding of the processing required. For instance, good knowledge of microfabric properties can reduce energy consumption, if overgrinding is avoided, which also results in improved recovery by avoiding losses due to poor liberation (Wills and Napier-Munn, 2006). Similarly, accurate information on mineral composition may permit the specification of a cut-off in any separation technique (magnetic, electrostatic, or density-based), optimally weighting recovery and further processing costs. Or depending on the proportion of fines generated during milling, desliming might or might not be necessary. Finally, different concentrations of chemicals might be needed for an optimal flotation process as a function of the composition of the concentrate. These Improving processing by adaption to conditional geostatistical simulation of block compositions

Profit Analysis and Supply Chain Planning Model for Closed-Loop Supply Chain in Fashion Industry

In recent decades, due to market growth and use of synthetic fiber, the fashion industry faces a rapid increase of CO2 emission throughout the production cycle and raises environmental issues in recovery processing. This study proposes a closed-loop supply chain (CLSC) structure in fashion industry and develops its planning model as multi-objective mixed integer linear programming to find an optimal trade-off between CLSC profit and CO2 emission. The planning model is associated with the profit analysis of each member in CLSC to find the optimal price of products on CLSC network. The model determines optimal production, transportation, and inventory quantities on CLSC network. The proposed models are validated using numerical experiments and sensitivity analyses, and from the results some managerial insights are addressed.

The Production Status and Treatment for Rural Solid Waste in Hainan Province

According to the characteristics of rural household garbage and the realistic conditions of rural areas in Hainan Province, and based on the experience of the rural household garbage processing, this paper discusses the rural garbage recovery processing pattern, funds and management of Hainan province and other relevant problems, in order to provide suggestions and comments about the processing of rural household garbage for Hainan as a tourist province.

Controlled separation of low temperature coal tar based on solvent extraction–column chromatography

The heavy tar (H-tar) of low temperature coal tar was collected from a low temperature carbonization plant in Shanbei. H-tar was separated into eight fractions by silica-gel column chromatography (SGCC) with a binary eluent of n-hexane and ethyl acetate (EA). A series of alkanes (C14–C28), phenolic compounds and aromatic nitrogen species were fractionated from H-tar by SGCC and analyzed by gas chromatography–mass spectrometry (GC–MS). Most of the GC–MS detectable phenolic compounds are phenol, cresol, xylenol, C3–C4 alkyl phenols, indanols, naphthalenols, methyl naphthalenols, benzenediols, fluorenols, phenanthrols and pyrenol, among which cresol is the most abundant one and pyrenol is the largest molecular weight one. According to the change rule of phenolic compounds with the polarity of eluting solvents, the solvent extraction–column chromatography (SECC) device and crude phenol recovery processing have been designed and developed, which could realize the separation of neutral oil, pitch and crude phenol from low temperature coal tar.

The Potential of Enhanced Oil Recovery by Micellar/Polymer Flooding in Heterogeneous Reservoirs

The performance prediction of a micellar polymer flood in a complex reservoir requires an accurate model that represents the reservoir features, chemical properties, and displacement mechanisms that affect the flood performance. First, this article provides a comprehensive comparison of micellar polymer flood with other recovery techniques, such as waterflooding, polymer flooding, and surfactant flooding. Then, the article states the successful evidences of micellar polymer flooding in a highly heterogeneous oil field in Vietnam. The results indicate that waterflooding is only efficient for homogeneous reservoirs and it is necessary to apply chemical flooding for highly heterogeneous reservoirs in tertiary hydrocarbon recovery processing. A significant value of increasing oil recovery is a reliable evidence for the worth of micellar polymer flooding.

Research of Drainage Gas Recovery Technology in Gas Wells

Drainage gas recovery technology is the main method of gas recovery process in gas field, which has domestically and internationally been the main gas recovery processing measure in later stage of gas field production. In this context, produced water or condensate liquid will not be carried out of pit shaft by natural gas with the gradual drop of gas reservoir pressure and natural gas flow velocity, thus they will remain in pit shaft and form the so-called “gas well gathered liquid”. This fluid severely affects natural gas output and leads to the decline of oil field economic benefits, thus drainage gas recovery measure must be taken to increase gas well or even gas field output. It becomes the primary problem to be solved to select the best drainage gas recovery measure which can maximize gas field benefits and optimize gas well safety.

Rolling of cast Al‐SiCp particulate metal matrix composites and strip mechanical properties

AbstractThermomechanical physical simulation is applied to get the optimum hot rolling parameters of aluminium silicon carbide composites. Wrought Al 6061 and 6082 – Silicon carbide particulate (SiCp) metal matrix composite strips are prepared by stir‐casting followed by sequential rolling assisted with intermediate heat treatment to allow crystallization recovery and further processing. SiCp are used in two microgrit grades; namely F500 and F800. The reinforcing particulates are used after surface oxidation and 0.3% Mg is added during melting and stirring for loss substitution. With the pre‐treatments applied, SiCp are successfully inserted in the Al matrix, better wetting between particles and matrix, better particles distribution, less agglomeration and minimized reactions between SiC particles. Thermo‐mechanical simulation as a tool for physical simulation indicates that rolling at 450°C using a rate of 1 s–1 rate represent suitable rolling conditions. Successive hot rolling resulted in decreasing void percent and SiCp agglomeration. Hence, enhanced mechanical properties are achieved.

Theoretical and experimental analysis of bed-to-wall heat transfer in heat recovery processing

The accurate prediction of heat transfer behavior in packed bed is of great importance to the design and operation of this kind of facility. In this paper, heat transfer between packed bed and adjacent wall in heat recovery processing is investigated theoretically and experimentally. A bed-to-wall heat transfer model is presented with consideration of two essential components including particle-to-wall contact heat transfer and heat conduction through the thermal penetration layer. Details of model parameter determination are provided. Through comprehensive sensitivity analysis of those parameters, it is shown that particle temperature, particle residence time and particle diameter are critical parameters to heat transfer coefficient. Besides, surface roughness, solid thermal conductivity and environmental gas species are all influencing factors of the overall heat transfer coefficient. In particular, a dimensionless particle residence time is introduced to characterize the combining effect of residence time, effective thermal conductivity and wall contact heat transfer. Meanwhile, a revised simplified formula for calculating particle contact heat transfer coefficient is correlated as well, which provides better prediction than the one widely adopted in previous studies. Furthermore, experimental heat transfer test on an industrial packed bed char cooler is performed for validating the model predicting capability in heat recovery process. The systematical test on a bench scale packed bed heat exchanger has also been carried out. Parametric analysis of the experimental data is consistent with the conclusions drawn from the model analysis section. The model provides good predicting accuracy on the overall heat transfer coefficient from the bench scale facility as well as data from the field test by correlating 95% of the measured data within ±20%. The implementation of the proposed model shows good prediction of heat transfer coefficient in packed bed for heat recovery purpose. It is recommended that the model can be applied in industrial design.