Steam consumption minimization using genetic algorithm optimization method: an industrial case study

yesCondensate stabilization is a process where hydrocarbon condensate recovered from natural gas reservoirs is processed to meet the required storage, transportation, and export specifications. The process involves stabilizing of hydrocarbon liquid by separation of light hydrocarbon such as methane from the heavier hydrocarbon constituents such as propane. An industrial scale back-up condensate stabilization unit was simulated using Aspen HYSYS software and validated with the plant data. The separation process consumes significant amount of energy in form of steam. The objectives of the paper are to find the minimum steam consumption of the process and conduct sensitivity and exergy analyses on the process. The minimum steam consumption was found using genetic algorithm optimization method for both winter and summer conditions. The optimization was carried out using MATLAB software coupled with Aspen HYSYS software. The optimization involves six design variables and four constraints, such that realistic results are achieved. The results of the optimization show that savings in steam consumption is 34% as compared to the baseline process while maintaining the desired specifications. The effect of natural gas feed temperature has been investigated. The results show that steam consumption is reduced by 46% when the natural gas feed temperature changes from 17.7 to 32.7°C. Exergy analysis shows that exergy destruction of the optimized process is 37% less than the baseline process

Predicting physical properties of hydrocarbon compounds

A new, simple-to-use correlation is developed to predict physical characteristics of pure compounds and petroleum fractions when no experimental data are available on the petroleum fractions. The new correlation is based on available experimental data and uses four coefficients to correlate different variables for predicting petroleum fractions properties. The coefficients are determined numerically by a least-squares approach. The value can be determined by selecting the set of tuned coefficients for a givenproperty. The accuracy of the new correlation can be tested by comparing its average absolute deviation to experimental data reported in Danesh

Predicting water content of compressed air

It is necessary to be able to predict the water content of air and saturated air to design and apply the appropriate type of drying to the compressed air system. Relative humidity and dew point are the two methods of indicating the amount of moisture in theair. Equation (1) presented a new correlation in which four coefficients were used to correlate water content, W, and either the relative humidity (RH) or the absolute pressure. The Water content, W, in Equation (1) was given as millimeters of water per cubic meter of air, while the variable X is either the relative humidity, or, for saturated air condition, X is the absolute pressure, which can range from 100 to 1,400 kPa. T is the temperature for K for Equations (2) to (5), and the \u27tuned\u27 coefficients are obtained by a least-squares analysis of data. The experiments found that the higher the temperature, the greater is air\u27s capacity to hold water vapor, while increasing pressure reduces the ability of air to hold moisture

Simple correlation accurately predicts densities of glycol solutions

A simple-to-use correlation is developed to accurately predict the density of the most commonly used glycol solutions as a function of temperature and glycol wt% in water. The proposed correlation has very good agreement with the reported experimental data. The average absolute difference between the observed values and calculated results is 0.941 kg/m3, which is negligible compared to the actual density of aqueous glycols

Simple methodology predicts optimum pressures of multistage separators

To achieve good separation between gas and liquid mixtures from the crude oil production system and to maximize hydrocarbon liquid recovery, it is necessary to use several separation processes at decreasing pressures and to adjust the pressure set points to improve product separation and recovery at minimum cost. This study presents a simple methodology for optimizing separator pressures in the crude oil production unit. The new proposed methodology determines the optimum pressures of separators in different stages of separation and, consequently, optimizes the operating conditions. In this study, the optimum pressures of separators in a 3896 Kgmole/hr oil production unit were determined. As a result, the oil recovery was increased about 6 Kgmole/hr (80 bbl/day), and the quality of total produced oil was improved by 0.3 API

Correlation rapidly estimates pure hydrocarbons\u27 surface tension

Surface tension, an important property where wetting, foaming, emulsification and droplet formation are encountered, is used in the design of fractionators, absorbers, two phase pipelines, and in reservoir calculations. In this study, a simple correlation is developed to predict paraffin hydrocarbon surface tension as a function of molecular weight and temperature. The new correlation is suitable for the range of temperatures between –30 and 150°C and the hydrocarbon molecular weights between the range of 30 and 200, where good agreement is found between predicted and observed values