Advances in petrochemical technology assessment

The petrochemical industry is a dynamic industry and can be seen as a network of chemicals from basic feedstock to final chemicals. The aim of this work is to identify and model long-and short-range disturbances that affect planning of the petrochemical industry. An application to the Kuwait Petrochemical Industry was performed. The major disturbance is the oil prices that affect chemical prices and consequently profit. Future chemical prices needed for planning are predicted using three forecasting models: simple time-series fitting and two causal models with oil prices, the second-order plus dead time transfer function and autoregression with an exogenous variable models. Oil prices for the causal models are first forecasted under the concept of market long cycles (K-waves) and short cycles (business or Kitchin cycles) and then used to forecast chemical prices. The forecasted chemical prices affect the planning of the petrochemical industry where different routes in the network are selected for different final product prices. It is found that including the market cycles and using the causal models for forecasting petrochemical product prices will provide possible scenarios for chemical price forecast, and then a risk-adjusted present value can be calculated.

Section: Modeling the Petrochemical Industrymentioning

confidence: 99%

Modeling and Identification of Economic Disturbances in the Planning of the Petrochemical Industry

Al-Sharrah

Alatiqi

Elkamel

2003

“…The network model approach for representing the hydrocarbon processing industry was pioneered by Stadtherr and Rudd − and colleagues, who focused initially on minimization of resource usage as a driving force and subsequently on minimization of industry cost, with studies on industrial development, , impact of new technologies, , future trends and planning, , and the effect of chemical toxicity regulations . Many variations, extensions, and applications of this initial work have subsequently appeared, a selection of which are noted here.…”

Section: Introductionmentioning

confidence: 99%

Systems Analysis of Natural Gas Liquid Resources for Chemical Manufacturing: Strategic Utilization of Ethane

Skouteris

Giannikopoulos

Edgar

et al. 2021

The increasing production of shale gas and, consequently, natural gas liquids (NGLs) provides opportunities to expand the U.S. chemical industry, leading to questions about how to best use these resources. We consider targets for the strategic use of ethane, the most abundant of the NGLs, by evaluating the impact of a potential, new catalytic dehydrogenation technology for converting ethane to ethylene and then evaluating potential, new catalytic oligomerization processes for converting ethylene to 1-butylene and to 1-octene. To conduct these evaluations, we introduce a new, nonlinear, industry-wide, optimization-based network model of the U.S. petrochemical and refining industries. Unlike previous linear models of this type, the nonlinear model accounts for changes in intermediate prices and, thus, process costs as new technology is added to the industry network. A method for propagating cost and price changes, permitting the solution of the nonlinear optimization problem as a sequence of linear problems, is developed and utilized. Using network models for this study, we account for and identify the direct and secondary consequences of introducing new technology on the rest of the industry. For each new technology evaluated, we determine the production level of the technology in the optimal industry network. By doing this over a wide range of net process cost points, a maximum adoption cost (the net process cost beyond which the technology would not be adopted) can be identified, and its sensitivity to the assumed product yield determined for each new technology can be studied. The maximum adoption costs can be viewed as targets for future catalyst research, reaction engineering, and process development work. Scenarios in which the ethane supply is constrained to current values and in which it is unconstrained are considered.

“…Rudd et al developed a cost-based model that was then used by Fathi-Afshar et al to study the introduction of new technologies into the existing network. It was also demonstrated how this model could be used for long-term industry planning and to study the impact of restrictions on the use of toxic substances. To further study this last issue, Fathi-Afshar and Yang developed a multiobjective model to seek compromise solutions using both cost- and toxicity-based objectives.…”

Section: Introductionmentioning

confidence: 99%

Geospatial Network Approach for Assessing Economic Potential of Ethylene-to-Fuel Technology in the Marcellus Shale Region

Giannikopoulos

Skouteris

Edgar

et al. 2021

The Marcellus Shale region is rich in natural gas liquids (NGLs) and a likely future hub for NGL derivatives such as ethylene. A geospatial network model of the U.S. petrochemicals and refining industry is developed and utilized to assess the potential for the adoption of a technology for oligomerization of ethylene to gasoline, or a gasoline blend stock, as a means to utilize NGL derivatives available in the region. The model is a mixed-integer linear program with the objective of minimizing the total annual cost incurred by the regional industry. Case studies in which this technology is added to the industry network model are described, and sensitivity analyses are conducted to investigate the effect of model parameters such as the prices of crude oil and ethylene. These results can be used as cost target benchmarks for this new technology. More broadly, this work demonstrates a geospatial network modeling approach for evaluating new processing technology.