Heat exchanger fouling model and preventive maintenance scheduling tool

The crude preheat train (CPT) in a petroleum refinery consists of a set of large heat exchangers which recovers the waste heat from product streams to preheat the crude oil. In these exchangers the overall heat transfer coefficient reduces significantly during operation due to fouling. The rate of fouling is highly dependent on the properties of the crude blends being processed as well as the operating temperature and flow conditions. The objective of this paper is to develop a predictive model using statistical methods which can a priori predict the rate of the fouling and the decrease in heat transfer efficiency in a heat exchanger. A neural network based fouling model has been developed using historical plant operating data. Root mean square error (RMSE) of the predictions in tube- and shell-side outlet temperatures of 1.83% and 0.93%, respectively, with a correlation coefficient, R², of 0.98 and correct directional change (CDC) values of more than 92% show that the model is adequately accurate. A case study illustrates the methodology by which the predictive model can be used to develop a preventive maintenance scheduling tool.     

Scheduling cleaning in a crude oil preheat train subject to fouling: Incorporating desalter control

Fouling is a serious operating problem in oil refinery distillation preheat trains (PHTs) as the reduction in heat transfer effectiveness not only reduces the overall rate of heat transfer but also causes difficulty in maintaining key temperatures in the network within their defined operating envelopes. This work considers the problem of controlling the desalter inlet temperature by using hot stream bypassing, within a PHT fouling mitigation strategy based on heat exchanger cleaning. The formulation of the problem is incorporated in the PHT simulator described by Ishiyama et al. (2009) [1]. The methodology is illustrated using a case study based on an industrial network subject to fouling, where the fouling rates of heat exchangers were extracted through a data reconciliation exercise. The case study scenarios suggest that our simulation-based tool should be effective in controlling desalter inlet temperature within a fouling management strategy.     

Design of Shell-and-Tube Heat Exchangers to Achieve a Specified Operating Period in Refinery Preheat Trains

Fouling dominates the design of heat exchangers used in crude oil preheat trains. It also dominates the lifetime cost of the trains, where the most important cost factor is lost profit through reduced production. Thus, the design objective should be the identification of geometries that provide acceptable performance throughout a desired operating period. This paper suggests a new design approach for shell-and-tube heat exchangers in refinery preheat trains that uses dynamic crude oil fouling models rather than conventional fouling factors to yield designs that are capable of achieving a specified operating period between cleaning operations.     

Impact of Nonuniform Fouling on Operating Temperatures in Heat Exchanger Networks

ABSTRACT

Investigations of fouling in heat exchangers are mainly focused on two factors: commercial impact due to energy losses, and environmental impact manifested through higher CO₂ emissions. The purpose of this paper is to introduce a third factor relating to safety in operations. This paper presents two case studies, one for a hydroprocessing unit with feed/effluent heat exchangers and another for preheat train exchangers installed upstream of the atmospheric furnace in a refinery crude unit. Due to a wide range of process temperatures examined in both case studies, the heat exchangers in the network are subject to various fouling mechanisms. As illustrated in the pictures of actual tube bundles, some of the exchangers within the network are heavily fouled, while the other exchangers operate in nearly clean conditions. Detailed simulations indicate that nonuniform fouling results in heat exchanger operating temperatures that are significantly higher than those predicted by conventional analyses using uniform fouling. Higher than anticipated process fluid temperatures may result in exceeding the threshold limits for certain corrosion mechanisms and/or significantly higher than expected rates of corrosion.     

Mitigation of Crude Oil Preheat Train Fouling by Design

Fouling in crude oil preheat trains is a significant industrial problem which has restricted the application of process integration techniques such as "pinch technology" in this sector. A semiempirical fouling model for crude oil fouling developed by Panchal and co-workers allows the effects of fouling to be considered at the design stage for such networks. Application of this model at three levels--(1) design of new networks; (2) retrofitting of existing systems; and (3) identification of robust specifications for individual heat exchanger units--is discussed. The design issues are discussed using case studies illustrated by a graphical construction, the temperature field plot. Rigorous optimization of the final designs is not reported. The specification discussion describes how the crude fouling model can be incorporated into existing heat exchanger design software to identify exchanger configurations which are less likely to experience significant fouling over a range of operating conditions. This article concentrates on shell-and-tube designs, but the concepts will be applicable to other exchanger types once a suitable fouling model becomes available.     

Neuro-based formulation to predict fouling threshold in crude preheaters

For preheat exchangers of a crude distillation unit (CDU), operating in conditions such that fouling minimized is crucial. A number of semi-empirical models called “threshold fouling models” were developed by various researchers to predict crude oil fouling behavior in crude preheaters of CDUs. In this study, an artificial neural network (ANN) model has been employed to develop a set of mathematical formulations to identify regions where there is less/no fouling. The comparisons between results of the developed neuro-based formulation and three threshold fouling models showed the use of neuro-based model resulted in significant improvements in terms of predicting crude oil fouling behavior of various laboratory and plant data. The approach of developing neuro-based models to predict fouling behavior can be readily applied in CDUs to identify more accurate fouling/no-fouling operating zones leading to an enhancement in the operation of crude preheaters.     

Retrofitting Crude Oil Refinery Heat Exchanger Networks to Minimize Fouling While Maximizing Heat Recovery

Abstract

The use of fouling factors in heat exchanger design and the lack of appreciation of fouling in traditional pinch approaches have often resulted in crude preheat networks that are subject to extensive fouling. The development of thermal and pressure drop models for crude oil fouling has allowed its effects to be quantified so that techno-economic analyses can be performed and design options compared. The application of these fouling models is described here on two levels: the assessment of increasing heat recovery in stream matches (e.g., by adding extra area to exchangers) and the design of a complete network using the Modified Temperature Field Plot. Application to a refinery case study showed that, at both the exchanger and network levels, designing for maximum heat recovery (e.g., using traditional pinch approaches) results in a less efficient system over time due to fouling effects.     

Optimizing a CO2 value chain for the Norwegian Continental Shelf

This paper presents a mathematical model for designing a carbon dioxide (CO₂) value chain. Storage of CO₂ in geological formations is recognized as an important alternative for carbon abatement. When CO₂ is deposited in oil reservoirs it can sometimes be used to achieve additional oil production, enhanced oil recovery (EOR). The model determines an optimal CO₂ value chain from a fixed set of CO₂ emission points and a set of potential injection sites. It designs a transport network and chooses the best suited oil fields with EOR potential or other geological formations for storage. A net present value criterion is used. The model is illustrated by an example of a Norwegian case with 14 oil fields, two aquifers and five CO₂ sources. A sensitivity analysis is performed on the most important parameters.     

Effect of Flow Distribution in Parallel Heat Exchanger Networks: Use of Thermo-Hydraulic Channeling Model in Refinery Operation

Abstract

Parallel branches are commonly observed in industrial heat exchanger networks (HENs). Despite the important relationship between flow distribution and network efficiency, not all parallel branches comprise of flow controllers or not least, flow measurements. When the network is subject to fouling, uncontrolled flow branches can introduce undesired phenomenon such as thermo-hydraulic channeling (THC) [presented at the 2007 HEFC conference; Ishiyama et al., Effect of fouling on heat transfer, pressure drop and throughput in refinery preheat trains]. Recent analysis of crude preheat train heat exchangers has shown the need to use THC models, in particular, for situations where there is insufficient flow measurement data, especially in nonsymmetric branches. This paper revisits the THC model and highlight practical importance of the THC phenomenon through analysis of plant data. The hydraulic aspect of the analysis is strongly linked to the knowledge of deposit thermal conductivity. A case study of a section of a crude refinery HEN is used to illustrate the use of thermo-hydraulic models in data reconciliation to understand flow imbalances caused due to differences in operating conditions and fouling of heat exchangers in each branch of a parallel network.     

Evaluation of Crude Oil Heat Exchanger Network Fouling Behavior Under Aging Conditions for Scheduled Cleaning

Heat exchanger network (HEN) fouling is an endemic operational challenge prevalent in many process industries. Its impact on both plant operating cost and productivity is significant and can be compounded by aging effects of the foulant. In this paper, we model and simulate the effect of aging on tube-side fouling and cleaning dynamics in a crude oil refinery preheat train (PHT) comprising a 14-unit HEN. A prescient, HEN modeling and dynamic simulation were performed wherein the transients of fouling and aging as well as the interactions between individual units were captured. To assess the temporal effects, different crude oil deposit (gel) aging scenarios (no aging vs. slow, medial, and fast aging) in the downstream units were considered for the PHTs’ overall heat recovery, cleaning options, and operability. The results show that the deleterious impact of fouling and concomitant aging, quantified in terms of thermal resistances, was significantly reduced by fast aging as opposed to medial, slow, or no aging of the gel deposit. Faster aging rate reflected improved heat recovery and a lesser demand for and lower cost of PHT cleaning. The concomitant higher growth of coke deposit due to aging, however, resulted in greater hydraulic resistance, which is inimical to operability.     

Fouling in Crude Oil Preheat Trains: A Systematic Solution to an Old Problem

A major cause of refinery energy inefficiency is fouling in preheat trains. This has been a most challenging problem for decades, due to limited fundamental understanding of its causes, deposition mechanisms, deposit composition, and impacts on design/operations. Current heat exchanger design methodologies mostly just allow for fouling, rather than fundamentally preventing it. To address this problem in a systematic way, a large-scale interdisciplinary research project, CROF (crude oil fouling), brought together leading experts from the University of Bath, University of Cambridge, and Imperial College London and, through IHS ESDU, industry. The research, coordinated in eight subprojects blending theory, experiments, and modeling work, tackles fouling issues across all scales, from molecular to the process unit to the overall heat exchanger network, in an integrated way. To make the outcomes of the project relevant and transferable to industry, the research team is working closely with experts from many world leading oil companies. The systematic approach of the CROF project is presented. Individual subprojects are outlined, together with how they work together. Initial results are presented, indicating that a quantum progress can be achieved from such a fundamental, integrated approach. Some preliminary indications with respect to impact on industrial practice are discussed.     

Utilization of produced gas of CO2 flooding to improve oil recovery

Large amounts of mixed gas containing CO₂ and hydrocarbon would be produced during CO₂ flooding. Injecting the produced gas back to reservoir can not only make full use of CO₂, but also can reduce air contamination. Taking produced crude oil and gases with different CO₂ concentration from Jilin oilfield as examples in this paper, the phase behavior and the physical properties of live oil-gas system were measured with a visible PVT apparatus. In terms of oil viscosity reduction and swelling, the gas with high CO₂ concentration was found to be substantially effective. Furthermore, comparative slim tube tests of the oil recovery performance using the five kinds of gases under different operating pressure were conducted in one-dimensional model. Results indicate that displacement efficiency increases linearly with the increasing CO₂ content in the recycle gas; displacement efficiency increases with operating pressure under immiscible conditions. Re-injecting produced gas with relative high CO₂ concentration back to reservoir is a method both time-saving and cost-effective.     

Experimental study of syngas production from methane dry reforming with heat recovery strategy

This study employed the concept of heat recovery to design a set of reformer to facilitate the methane dry reforming (MDR), through which syngas (H₂+CO) could be generated. The MDR involves an endothermic reaction and thus additional energy is required to sustain it. According to the concept of industrial heat recovery, the energy required to facilitate the MDR was recovered from waste heat. In addition, after the reforming reaction, the waste heat inside the reformer was used for internal heat recovery to preheat the reactants (CO₂+CH₄) to reduce the amount of energy required for the reforming reaction. Regarding the parameter settings in the experiments, the CH₄ feed flow rate was set at 1–2.5 NL/min and the mole ratio for CO₂/CH₄ was set at 0.43–1.22. Subsequently, an oven was used to simulate a heat recovery environment to facilitate the dry reforming experiment. The experimental results indicated that an increase in oven temperature could increase the reforming reaction temperature and elevate the energy for the reformer. H₂ and CO production could increase when the reformer gained more energy. The high-temperature gas generated from the reforming reaction was applied to facilitate internal heat recovery of reformer and preheat the reactants; thus, the efficiency of reforming and CO₂ conversion were evidently elevated. The theoretical equilibrium analysis indicated that the thermal efficiency of reforming increased with the increase of CO₂/CH₄ molar ratio. While, the thermal efficiency of reforming by experiments decreased with the increase of the CH₄ feed rate, but increased with the increase of CO₂/CH₄. In summary, the experimental results revealed that the overall H₂ was 0.017–0.019 mol/min. In addition, the reforming efficiency was 8.76%–78.08%, the CO₂ conversion was 53.92%–96.43%, and the maximum thermal efficiency of reforming was 102.3%.     

A new graphical method to target carbon dioxide emission reductions by simultaneously aligning fuel switching,energy saving,investment cost,carbon credit,and payback time

Lowering CO₂ emissions has become one of the key drivers behind the process intensification and modification in current chemical process industries. Here, we proposed a graphical method that features simultaneous correlation between CO₂ emission reduction, fuel switching, energy saving, investment cost, carbon credit, and payback time. Such CO₂ emission reduction can be obtained by fuel switching and/or retrofitting of the heat exchanger network. We illustrate the applications of this graphical method to the crude oil preheating train that uses furnace and the palm oil refinery that uses steam boiler. In crude oil preheat train case, for example, 55% emission reduction target can be achieved at an approximately 1.15 year of payback time from the alignment of fuel switching and energy saving. Further reduction in payback time from 1.15 to 0.91 years can be obtained by adding carbon credit contribution scheme into such alignment. This illustrates the flexibility of our graphical method to provide simple and convenient way for evaluating the technical and economic variable relationship for decision‐making.     

Fouling Management of Thermal Cracking Units

ABSTRACT

Visbreakers and other thermal cracking units are thermal process units in crude oil refineries that upgrade heavy petroleum, usually residual oils produced from atmospheric or vacuum distillation of crude oil. The associated process streams of these units consist of heavy hydrocarbons with very high viscosities and impurities, resulting in fouling of the heat exchangers used to cool or heat these streams. This paper presents a practical fouling analysis for thermal cracking units in a refinery in Germany. Fouling management at this refinery was initiated as part of the refinery energy-saving program. Following similar analysis of the refinery's crude preheat trains, heat exchanger networks associated in the thermal cracking units were modeled by entering the plant monitoring data, network topology, and heat exchanger geometries into a commercial heat exchanger network simulator, SmartPM. Fouling behaviors of vacuum residue streams and thermal cracker residue streams were identified and quantified. Both chemical reaction fouling and particulate fouling mechanisms were identified to be responsible for the fouling in these streams. Dynamic fouling models were fitted and used to predict fouling of these heavy petroleum streams, which fouled on both the shell and tube sides of the shell-and-tube heat exchangers.     

Transmission network-based energy and environmental assessment of plug-in hybrid electric vehicles

The introduction of plug-in hybrid electric vehicles (PHEVs) is expected to have a significant impact on regional power systems and pollutant emissions. This paper analyzes the effects of various penetrations of PHEVs on the marginal fuel dispatch of coal, natural gas and oil, and on pollutant emissions of CO₂, NO_x, SO₂ in the New York Metropolitan Area for two battery charging scenarios in a typical summer and winter day. A model of the AC transmission network of the Northeast Power Coordinating Council (NPCC) region with 693 generators is used to realistically incorporate network constraints into an economic dispatch model. A data-based transportation model of approximately 1 million commuters in NYMA is used to determine battery charging pattern. Results show that for all penetrations of PHEVs network-constrained economic dispatch of generation is significantly more realistic than unconstrained cases. Coal, natural gas and oil units are on the margin in the winter, and only natural gas and oil units are on the margin in the summer. Hourly changes in emissions from transportation and power production are dominated by vehicular activity with significant overall emissions reductions for CO₂ and NO_x, and a slight increase for SO₂. Nighttime regulated charging produces less overall emissions than unregulated charging from when vehicles arrive home for the summer and vice versa for the winter. As PHEVs are poised to link the power and transportation sectors, data-based models combining network constraints and economic dispatch have been shown to improve understanding and facilitate control of this link.     

CSA-LSSVM model for the estimation of solubility of n-alkane in supercritical CO2

Poor solubility of substantial hydrocarbons in CO₂ has constrained the use of CO₂-EOR (enhanced oil recovery) in the modern oil recovery industry to some extent. Subsequently, it is significant to research the solubility regularity of various hydrocarbons in supercritical carbon dioxide (scCO₂) in the first place. CO₂ injection as one of the popular methodologies in light of financially and environmentally friendly has wide applications in EOR. In this paper, our objective is to estimate the solubility of n-alkanes in scCO₂. This study highlights the application of a model based on least square support vector machine for estimation of solubility of n-alkanes in scCO₂. The tuning parameters of the developed model were determined by an optimization algorithm, namely coupled simulated annealing. A set of 184 data points of solubility was used to execute the new model. To assess the accuracy and effectiveness of the developed model for prediction of experimental data, statistical and graphical techniques were used. Moreover, the outcomes were compared with the results of literature correlations to predict the solubility of alkanes. Results demonstrate that the model is precise and viable for prediction of solubility data. The resulted values of R², root-mean-square error, SD, and % average absolute relative deviation for total data points are 0.99204, 0.12862, 0.6437, and 0.7753 for overall data, respectively.     

Management of Crude Preheat Trains Subject to Fouling

Crude oil refinery preheat trains are designed to reduce energy consumption, but their operation can be hampered by fouling. Fouling behaviors vary from one refinery to the next. Effective management of preheat train operation requires inspection of historical plant performance data to determine fouling behaviors, and the exploitation of that knowledge in turn to predict future performance. Scenarios of interest can include performance based on current operating conditions, modifications such as heat exchanger retrofits, flow split control, and scheduling of cleaning actions. Historical plant monitoring data are frequently inconsistent and usually need to be subject to data reconciliation. Inadequate data reconciliation results in misleading information on fouling behavior. This article describes an approach to crude preheat train management from data reconciliation to analysis and scenario planning based around a preheat train simulator, smartPM, developed at Cambridge and IHS. The proposed methodology is illustrated through a case study that could be used as a management guideline for preheat train operations.     

A new optimization approach to energy network modeling: anthropogenic CO2 capture coupled with enhanced oil recovery

To meet next generation energy needs such as wind‐ and solar‐generated electricity, enhanced oil recovery (EOR), CO₂ capture and storage (CCS), and biofuels, the US will have to construct tens to hundreds of thousands of kilometers of new transmission lines and pipelines. Energy network models are central to optimizing these energy resources, including how best to produce, transport, and deliver energy‐related products such as oil, natural gas, electricity, and CO₂. Consequently, understanding how to model new transmission lines and pipelines is central to this process. However, current energy models use simplifying assumptions for deploying pipelines and transmission lines, leading to the design of more costly and inefficient energy networks. In this paper, we introduce a two‐stage optimization approach for modeling CCS infrastructure. We show how CO₂ pipelines with discrete capacities can be ‘linearized’ without loss of information and accuracy, therefore allowing necessarily complex energy models to be solved. We demonstrate the new approach by designing a CCS network that collects large volumes of anthropogenic CO₂ (up to 45 million tonnes of CO₂ per year) from ethylene production facilities and delivers the CO₂ to depleted oil fields to stimulate recovery through EOR. Utilization of anthropogenic CO₂ has great potential to jumpstart commercial‐scale CCS while simultaneously reducing the carbon footprint of domestic oil production. Model outputs illustrate the engineering challenge and spatial extent of CCS infrastructure, as well as the costs (or profits) of deploying CCS technology. We show that the new linearized approach is able to offer insights that other network approaches cannot reveal and how the approach can change how we develop future energy systems including transporting massive volumes of shale gas and biofuels as well as electricity transmission for wind and solar energy. Published 2012. This article is a U.S. Government work and is in the public domain in the USA.