Hweeung Kwon

Forecasting Naphtha Price Crack Using Multiple Regression Analysis

Abstract The price of naphtha depends on that of crude oil as naphtha is produced by refining crude oil. Naphtha plays an important role as one of basic petrochemicals for downstream products. Large fluctuation of naphtha price has been intensified along with recent political unrest of Middle East Asia and the growing naphtha demand in developing countries. Thus forecasting naphtha price is becoming more uncertain. The development of models for forecasting naphtha crack (price difference between naphtha and crude oil) will help minimize any loss from naphtha price variations. This study is concerned with the derivation of a set of major parameters affecting naphtha prices and the identification of the most dominating factors. We proposed a model for forecasting naphtha crack based on statistical approach and multiple regression analysis, and R 2 was 651. .Naphtha price depends mainly on Asia supply and demand of naphtha as well as naphtha substitute and margin. Actual and predicted variations of naphtha crack were also analyzed. The proposed modeling approach can be extended to forecast prices of other downstream chemicals such as LPG and NGL.

Kriging models for forecasting crude unit overhead corrosion

Crude unit overhead corrosion is a major issue in the refinery field. However, the corrosion models in the literature are difficult to apply to real refinery processes due to the characteristics of corrosion. We propose a Kriging model, an advanced statistical tool for geostatistics, to forecast the corrosion rate in a real refinery plant. Instead of spatial coordinates, the proposed model employs the non-spatial coordinates of six key corrosion variables: H2S, Cl−, Fe2+, NH3, pH, and flowrate. The Kriging model is compared with two well-known forecasting models, multiple linear regression and an artificial neural network. To overcome the insufficiency of the number of data sets measured in the plant to use the six non-spatial coordinates, the significance probability is applied to reduce the dimensions from six to four. Among all the developed models in this paper, the Kriging model with four corrosion variables showed the best forecasting performance.

Optimization of Petrochemical Process Planning using Naphtha Price Forecasting and Process Modeling

Abstract A naphtha price forecasting model based on the time series method is developed to predict the monthly variation of naphtha price using statistics. We used the model to forecast future naphtha prices by looking at historical time series data from January 2008 to September 2011. After forecasting, we perform the normalization of the observed period and implement a simulation using the price forecasting model. In order to check the accuracy of the model, the predicted naphtha price variations are compared with the actual naphtha variation. If the predicted variation of the normalized naphtha price has the same trend as the actual naphtha variation, our prediction value is called “T.” Otherwise, the predicted value is called “F.” The accuracy of the predicted value is relatively higher than the price forecasting for other products such as crude oil. As a result, our model is useful to industry decision-makers for forecasting the price of naphtha.

Forecasting of naphtha demand and supply using time serial data causal analysis

Abstract Naphtha is an important resource used to produce petrochemical products. Historically, petrochemical companies have been keen to the variations of naphtha prices as it has had great effects on their profits. Naphtha price is closely aligned with crude oil price. In particular, more directly, supply and demand of naphtha affect its price fluctuations. This research is focused to propose an approach for forecasting supply and demand of naphtha, with an emphasis on key affecting factors such as the margin of petrochemical companies and the use of alternative raw material. The demand of naphtha is estimated on the basis of the margin and operation rate of a petrochemical plant, while its supply is affected by operation rate of refinery. Modeling of forecasting naphtha supply/demand, based on time series method, is developed along with absolute errors derived from a statistical analysis; the model at present time is used to forecast future supply/demand over historical time series data from March 2010 to September 2012. Key set of affecting factors are identified by combined heuristic and statistical analysis and a set of equations correlating between those factors are set up. The proposed model was validated by actual data for the underlying period, which should be useful to forecast the price of naphtha

Development of a safety education system for SMB operation

Abstract The para-xylene separation which is one of vary important base material among industrial other technique mainly is used early on crystallization method. But Recently absorption separation process by SMB(Simulated Moving Bed) about energy saving process is on the way to general trend. This paper describes the development of an operator-education program for SMB (Simulated Moving Bed), aiming at educating operators efficient and sage operation as well as preventing accidents such as explosion, fire and toxic material release, most of which result from the lack of understanding of processes. SMB education system is a network-based program to be used in a client/server environment. It is a two or three dimensional virtual process operation system for SMB process, using flash and 3D MAX. The system provides operators with visual-friendly education procedures for SMB processes with an emphasis on process knowledge and safety. In this study, operator received periodic education which is helpful to understand the safety about process and operation. This study contribute to prevent the accident to be expected that workers mistake process operation.

A novel system dynamics model for forecasting naphtha price

Fluctuations in naphtha price are directly related to the profit of petrochemical companies. Thus, forecasting of naphtha price is becoming increasingly important. To respond to this need, a naphtha crack (the price gap between naphtha and crude oil) forecasting model is developed herein. The objective of this study was to design a reasonable forecasting model that is immediately available and can be used to develop various naphtha supply strategies. However, it is very difficult to forecast a price value with a high accuracy. Therefore, the proposed model focuses not on the price value but on the direction of the crack. These considerations are vital to a company’s decision-making process. In addition, a system dynamics model that considers causal relations is proposed. It was developed based on heuristics, statistical analysis, seasonal effects, and relationships between factors that affect naphtha price, and it exhibits an accuracy rate of 84%-95% in forecasting of the naphtha crack three months in advance.

A multistream heat exchanger model with enthalpy feasibility

Abstract A temperature feasibility constraint is an important part of multistream heat exchanger (MSHE) modeling. However, temperature feasibility of an MSHE model makes a numerical issue when a physical property package is used to obtain highly accurate temperature-enthalpy relationships in equation-oriented modeling environment. To resolve the issue, this study proposes a new MSHE model with enthalpy feasibility using the fact that enthalpy is a monotonically increasing function of temperature. A natural gas liquefaction process, called a single mixed refrigeration process, is optimized using the proposed MSHE model under an equation-oriented modeling environment with a physical property package as a case study.

Analysis of air blast effect for explosives in a large scale detonation

Open Burning/Open Detonation (OB/OD) has been widely used for demilitarization of expired explosives. However, OB/OD effects a variety of hazardous damages to environment. Therefore, using incinerators to treat expired explosives is required instead of OB/OD. To guarantee the safety of these demilitarization methods, the blast wave of the explosives should be previously recognized to evaluate the impact of detonations. Although various materials are used to produce explosives, most researches have focused on trinitrotoluene (TNT). Other representative explosives such as research department explosives (RDX) and high melting explosives (HMX) are seldom studied in the literature. Therefore, our aim was to understand the blast wave of three materials under different geometry throughout simulations. To improve accuracy and reduce computational time, a zoning technique with Euler-Lagrange coupling method was used. Due to limitations and difficulties of detonation experiments, simulations were verified by theoretical models. In case of semi-confined bunker, the simulation results were compared with experimental data, showing a close match. As a result, cylinder type is the safest incinerator among semi-confined bunker, cylinder, and cube incinerators, in terms of the blast wave.

Web-based multi-dimensional education system for the simulated moving bed process

This paper describes the development of an operator-education program for a simulated moving bed (SMB) pilot plant that separates para-xylene isomer from mixed xylenes. The education program was motivated from reliable and safe operations for a newly developed SMB technology, in particular, a priori education on preventing accidents such as explosion, fire and toxic material release, most of which result from the lack of understanding of the processes being operated. This SMB process education program has overall SMB process description, sixteen operating screen and response procedure for accident of leak and explosion. The proposed system was implemented based on client/server architecture in company-wise LAN environment and applied previously operator heuristics. In addition, it features multi-dimensional animation for virtual reality of process flow, using multi-media techniques. Operators are expected to benefit from education that is free of time and space constraints. The education system for the pilot plant will contribute to keeping the full scale SMB operation workforce performing at a high level of proficiency as well as refreshing the operational skills of senior operators.