PREDICTING THE EFFECT OF FEEDSTOCK ON PRODUCT YIELDS AND PROPERTIES OF THE FCC PROCESS

The mechanism of petroleum refining processes are too complex, and no thorough model has yet been developed. Neural networks represent an effective alternative to mathematical modeling of refinery operations if a sufficient amount of input-output data is available. In this paper, a feed forward neural network that models the Fluid Catalytic Cracking (FCC) process will be presented. The FCC process is the workhorse of the petroleum refining industry, making small and medium sized molecules out of big ones (gasoline and distillate out of gas oils). The input-output data to the neural network was collected from the literature on pilot and commercial plant operations and were obtained from actual refineries. Several network architectures were tried and the network that best simulates the FCC process was retained. This network is able to predict yields of products of the FCC unit as well as their properties. The network consists of one hidden layer of twenty neurons, an input layer of four neurons, and an output layer of twelve neurons. The predictions of the neural network model were compared to those of a commercial simulator of the FCC process, to non-linear regression models, and to published charts. The results show that the neural network model consistently gives better predictions.     

催化裂化主分馏塔的平衡级模拟计算

提出一种新的催化裂化主分馏塔建模方法。基于油品的蒸馏数据 ,利用炼油工业中已积累的一整套经验图表和经验关联式 ,开发了一个快捷的催化裂化主分馏塔模拟系统。具有较快的模拟速度 (模拟时间不到 1min ,奔腾 13 3主机 )和满意的模拟精度 (主分馏塔温度模拟误差小于 6% ) ,为过程优化和决策提供了一条可行的有效途径     

DEVELOPMENT OF REGRESSION MODELS TO CONTROL PRODUCT YIELDS AND PROPERTIES OF THE FLUID CATALYTIC CRACKING PROCESS

Regression models for predicting product yields and properties for the Fluid Catalytic Cracking (FCC) process are presented. The feedstock properties are used as the primary correlation parameters. The models are based on data collected from various sources from the literature on pilot and commercial plants. The predictions of these models are compared to previous models and also to real data. The proposed models give consistently good predictions. These models can be used to evaluate different feeds to the FCC process and can also be integrated within general refinery mathematical programming (e.g. LP) software for planning and scheduling purposes.     

进一步降低炼油企业的能耗

我国炼油企业能耗与国外先进水平相比仍有较大差距，仍有较大节能潜力。炼油企业必须进一步采取有效的节能措施，如运用科学分析方法进行过程能量分析，抓住重点降低主要装置能耗，提高加热炉效率，降低催化裂化装置生焦率，优化生产流程，搞好装置间热联合，降低动力消耗以及采用新技术等，以进一步降低炼油企业能耗。提升企业竞争力，促进企业可持续发展。     

MODELING THE HYDROCRACKING PROCESS USING ARTIFICIAL NEURAL NETWORKS

Feed-forward neural networks that models the hydrocracking process of Arabian light vacuum gas oil are presented. The input-output data to the neural networks was obtained from actual local refineries. Several network architectures were tried and the networks that best simulate the hydrocracking process were retained. The networks are able to predict yields and properties of products of the hydrocracking unit (e.g. iC₄, nC₄, light and heavy naphtha, light and heavy ATK, Diesel, etc.). The predictions of yields and properties of various desired and undesired products at different conditions are required by refineries for process optimization, control, design, catalyst selection, and planning. The predictions of the prepared neural networks have been cross validated against data not originally used in the training process. The networks compared well against this new set of data with an average percent error always less than 8.71 for the different products of the hydrocracking unit.     

FCC烟气NOx排放影响因素及控制措施分析

氮氧化物是大气主要污染物之一。近年来,催化烟气氮氧化物控制已经成为行业关注的重点。国家在＂十二五＂期间将加大氮氧化物的控制管理,制定严格的排放标准。分析讨论现有催化裂化装置烟气氮氧化物排放现状及控制措施对催化裂化烟气脱氮具有十分重要的意义。通过分析FCC烟气NOx生成机理、控制措施以及燕山石化两套FCC烟气排放情况,得...     

RECENT ADVANCES IN FLUID CATALYTIC CRACKING PROCESS

Abstract

Fluid Catalytic Cracking (FCC) is one of the processes applied world-wide for upgrading of heavy petroleum cuts by converting them into lighter products in the gasoline, light, and heavy cycle oil ranges. Catalytic cracking process was developed in the early stages of petroleum refining. It started by utilizing chemically treated natural clays as catalysts. In the early 1960s the introduction of zeolite containing catalysts, mainly the wide pore faujasite family (X-and Y-type) has significantly contributed to the yield as well as FCC process design consideration. The overall process performance is strongly dependent the catalyst characteristics. Therefore, FCC catalyst manufacturers and researchers are continuously searching for modified catalyst characteristics (improved thermal and hydrothermal stability, higher Activity and better selectivity for high barrel-octane gasoline production). This research activity resulted in this introduction of several FCC catalyses with enhanced performance to suit the steadily increasing emand for high quality refined FCC products.

The present review is aimed at throwing a light on the FCC process with special emphasis on the recent advances made in the field of catalysts design and its impact on the whole FCC process performance as related to the production of high octane gasoline.     

21世纪的炼油技术与催化

市场对炼油工业的发展起导向和推动作用。为了满足市场需求，炼油工业开发了一系列生产清洁燃料和化工原料的新技术。重点介绍了多产异构烃的催化裂化技术(MIP)、催化汽油加氢异构脱硫降烯烃技术(RIDOS)、催化汽油选择性加氢脱硫技术(RSDS)、中压加氢生产优质柴油成套技术(RICH)、柴油超深度脱硫技术(RTS)等生产清洁燃料技术，渣油加氢处理一重油催化裂化双向组合技术(RICP)等重油深度转化技术，催化裂解和催化热裂解技术(DCC和CPP)、中压加氢改质技术(MHUG)和中压加氢裂化技术(RMC)等炼油一化工结合技术以及催化技术的集成——催化丙烯技术(SHMP)。这些新技术包含了催化新工艺和催化新材料，体现了催化技术创新对于炼油技术进步的先导作用。根据市场的需求和炼油工业的发展趋势，分析了未来催化技术发展的前景。     

催化裂化柴油深度加氢脱硫反应动力学模型的研究

以催化裂化柴油为原料,在滴流床反应器中,考察了温度、压力、空速、氢油比等操作参数对ＲＮ－１催化剂深度加氢脱硫反应活性的影响,建立了催化裂化柴油加氢脱硫反应的表观动力学模型,并在此基础上,以神经网络的计算手段研究了原料油性质对脱硫反应的影响。结果表明,神经网络系统对试验数据的处理有很好的准确性,对新原料油试验结果的预测有较好的可靠性。     

发展重油加工提高轻质产品收率

由于发动机燃料需求量增长、更为严格的环保要求和质量控制以及重质原油开采量的增加，发展重油加工，增加轻质石油产品，已成为世界炼油工业的重大问题。重油加工方案的研究表明：延迟焦化和催化裂化的组合工艺有较高的效益，而重油加氢裂化和重油催化裂化的组合工艺，可以把高含硫重油最大量地转化为轻质产品。重油催化裂化、延迟焦化和催化裂化、重油加氢裂化和重油催化裂化组合工艺是我国本世纪内重油加工发展的重点。发展重油加氢裂化近期以固定床加氢裂化为宜。     

催化裂化汽油固体碱脱硫-固定床脱臭组合工艺的开发

在对活性剂、活化剂等对固体碱脱除硫化氢性能影响研究的基础上,对催化裂化汽油固体碱脱硫-固定床脱臭组合工艺进行了实验室小试,结果表明,固体碱完全可以取代液体碱而用于催化裂化汽油的精制.相对于液体碱洗-固定床脱臭工艺,无论再生前还是再生后,固体碱脱硫-固定床脱臭组合工艺使装置运转时间延长一倍以上.介绍了该组合工艺的流程设计和工业应用.     

Numerical Simulation of Hydrodynamics and Coke Combustions in FCC Regenerator

Abstract

A gas-particle, two-phase flow-reaction model of fluid catalyst cracking (FCC) regenerators was established in this article according to the characteristics of FCC catalyst particle clusters and coke combustion reaction. Numerical simulations of the gas-particle flow behavior, heat transfer, and coke combustion process in the commercial regenerator were carried out to obtain detailed distributions of velocity, temperature, and species concentration. The fluidized processing can be well predicted, although there are still some differences between computational results and commercial data for the assumption of a mean diameter of an FCC catalyst. Obtained distributions of temperature and component concentration was also agreeable with commercial data.     

The Prediction of Wax Precipitation by Neural Network and Genetic Algorithm and Comparison With a Multisolid Model in Crude Oil Systems

Abstract

This article introduce a new implementation of the neural network and genetic programming neural network technology in petroleum engineering. An intelligent framework is developed for calculating the amount of wax precipitation in petroleum mixtures over a wide temperature range. Theoretical results and practical experience indicate that feedforward networks can approximate a wide class of function relationships very well. In this work, a conventional feedforward multilayer neural network and genetic programming neural network (GPNN) approach have been proposed to predict the amount of wax precipitation. The introduced model can predict wax precipitation through neural network and genetic algorithmic techniques. The accuracy of the method is evaluated by predicting the amount of wax precipitation of various reservoir fluids not used in the development of the models. Furthermore, the performance of the model is compared with the performance of multisolid model for wax precipitation prediction and experimental data. Results of this comparison show that the proposed method is superior, both in accuracy and generality, over the other models.     

芳烃抽提工艺的应用及研究进展

介绍芳烃抽提工艺在BTX生产、FCC原料的改善、润滑油精制等领域的应用,阐述芳烃抽提工艺萃取溶剂的选择、相平衡模拟方法及相应的研究进展,以便于芳烃抽提工艺在石油加工中得到进一步应用。     

延迟焦化在我国石油加工中的地位和前景

发展重油加工技术是目前炼油工业的突出任务之一。我国重油的轻质化将主要依仗于脱碳过程，其中延迟焦化与重油催化裂化在相当长的时间内将是我国重油加工的主要途径。延迟焦化技术成熟度较高、投资较低，在加工劣质原料、可为乙烯工业提供原料以及提高产品的柴／汽比等方面，具有其独特的优势。为了进一步发展我国的延迟焦化技术，需要在装置的大型化、生产技术的高效化、装置环境的清洁化以及石油焦的有效利用等方面继续努力。     

基于开源技术的FCC装置产品收率预测BP神经网络模型

装置产品收率的估算是前期全厂方案设计的重要环节,利用神经网络技术进行装置收率预测的效率高于传统的人工估算,也是石化项目前期设计信息化的发展方向之一.基于开源语言Python和PHP的石化项目设计前期神经网络系统,建立了一个适用于石化项目设计前期阶段的MIP工艺流化床催化裂化(FCC)装置产品收率预测的组合模型.结果表明...     

A Kinetics Lumped Model for VGO Catalytic Cracking in a Fluidized Bed Reactor

Abstract

Fluid catalytic cracking (FCC) is a process used to converted heavy petroleum products to light products such as gasoline, light fuel oil, and petroleum gas. In the fluid catalytic cracking reactor heavy gas oil is cracked into more valuable lighter hydrocarbon products. The reactor input is a mixture of hydrocarbons that makes the reaction kinetics very complicated due to the involved reactions. In this article, a four-lump model is proposed to describe the kinetics of vacuum gas–oil (VGO) cracking in the FCC process. This model is different from other models mainly in that the deposition rate of coke on catalyst can be predicted from gas–oil conversion and isolated from the C1-C4 gas yield. By this lumped model for the kinetic of cracking VGO we can also conclude that the C1-C4 gas yield increases with increasing reactor temperature, whereas the production of gasoline and coke decreases. We can also conclude that with decreasing space velocity the product yield will increase.     

STUDIES ON FLUID CATALYTIC CRACKING OF HYDROPROCESSED FEEDSTOCKS

ABSTRACT

Worldwide public concern about environment and increased demand for better quality fuels by automobile industries has necessiated developed countries like USA, UK and Japan to stipulate stringent specifications for petroleum fuel products. Fluid catalytic cracking (FCC) is a major secondary process for fuel products and quality of products coming from FCC unit depends largely on the feedstock used. FCC naphtha makes up for 30–40% gasoline in a typical refinery pool. This FCC naphtha contributes to around 90% of the gasoline pool sulphur. Hence, sulfur and nitrogen reduction have become essential for meeting the quality requirements of fuel products resulting in the growing importance for pretreatment of FCC feedstock. In the present work, studies were carried out in pilot plant on hydrotreatment of feedstock for FCC unit. The results indicate better quality products for treated feedstock vis-a-vis untreated heavy vacuum gas oils from Persian Gulf (PG) crudes. Hydroprocessing of FCC feed has helped refiners in meeting the fuel products quality especially with feedstocks, which are characterized as heavy and refractory in nature.     

炼油厂脱硫脱氨净化水的综合利用

将炼油二次加工过程中产生的含硫含氨污水经汽提脱硫脱氨后得到的净化水,代替原来使用的除盐水用于原油电脱盐装置和催化装置富气注水。经济效益显著,达到了节约用水和减少排污的目的。     

催化裂化干气中C3以上烃类总含量的在线检测

为了检测催化裂化装置所产干气中Ｃ３以上烃类的总含量，利用人工神经网络（ＡＮＮ＇ｓ）的方法建立了在线检测模型，并对影响模型检测精度的因素进行了分析。在实际生产装置上运行的结果表明，用此模型可以迅速、准确地检测出干气中Ｃ３以上烃类的总含量，可以满足在线检测的要求。