Separator Pressure Optimisation and Cost Evaluation of a Multistage Production Unit Using Genetic Algorithm

Motie, Mohadeseh; Moein, Peyman; Moghadasi, Ramin; Hadipour, Ali

doi:10.2523/19396-ms

Cited by 4 publications

(8 citation statements)

References 4 publications

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“…Now the gas condensate and volatile oil are comparable in the magnitude of realized optimization potential (0.7% and 0.9%, respectively), whereas a much lower optimization potential seems realizable for the black oil case (0.1%). The magnitude of the realizable optimization potential is notoriously dependent on the baseline; however, a comparison has previously been made by Andreasen including results from other studies. ,,, The potential for optimization in either stabilized oil export or total profit seems to be in the range of 0.1–2.0%. The defined realistic case baseline showing a potential of 0.1–0.9% seems to be very much in line with this range of optimization potentials.…”

Section: Resultsmentioning

confidence: 99%

“…Earlier studies focused on finding optimal pressure in the separators constituting the separation train (consecutive gas/liquid separators), but estimation of the optimal number of separators has also been of interest. More separation stages will increase the liquid recoverable amount, but as more and more stages are added, the incremental change decreases. , Often an optimum is found between two and four stages considering CAPEX and OPEX and, for offshore facilities, also lay out considerations.…”

Section: Introductionmentioning

confidence: 99%

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Optimization of an Oil and Gas Separation Plant for Different Reservoir Fluids Using an Evolutionary Algorithm

et al. 2021

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The optimization of an oil and gas separation plant operating revenue has been performed for different characteristic reservoir fluid types (gas condensate, volatile oil and black oil) using an evolutionary algorithm. A process simulation model mimicking a typical plant has been used as a black-box model and optimized with respect to nine design variables using the CMA-ES algorithm. The plant studied has three separation stages, including gas re-compression for each stage as well as a final gas boosting step before export. Each compression stage includes gas cooling and partial condensation

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimization of an Oil and Gas Separation Plant for Different Reservoir Fluids Using an Evolutionary Algorithm

et al. 2021

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“…In refs. [2,7,9,40] an improvement in terms of increased liquid production is explicitly stated compared to a non-optimized liquid production. The improvement observed in the present study is estimated using the difference between the base case and optimized profit cf.…”

Section: Resultsmentioning

confidence: 99%

“…2% and 8%, for crude and gas condensate, respectively. Motie et al [9] made a comprehensive study investigating the optimum separator pressure in a multistage separation train, studying the effect of the number of stages, both in terms of operating conditions, but also in terms of an NPV analysis in order to investigate to which extent the added cost of additional equipment for additional separation stages can be justified. The optimization of separator pressures was carried out by means of a genetic algorithm.…”

Section: Introductionmentioning

confidence: 99%

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Applied Process Simulation-Driven Oil and Gas Separation Plant Optimization using Surrogate Modeling and Evolutionary Algorithms

Andreasen

2019

Preprint

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In this article the optimization of a realistic oil and gas separation plant has been studied. Two different fluids are investigated and compared in terms of the optimization potential. Using Design of Computer Experiment (DACE) via Latin Hypercube Sampling (LHS) and rigorous process simulations, surrogate models using Kriging have been established for selected model responses. The surrogate models are used in combination with a variety of different evolutionary algorithms for optimizing the operating profit, mainly by maximizing the recoverable oil production. A total of 10 variables representing pressure and temperature various key places in the separation plant are optimized to maximize the operational profit. The optimization is bounded in the variables and a constraint function is included to ensure that the optimal solution allows export of oil with an RVP < 12 psia. The main finding is that, while a high pressure is preferred in the first separation stage, apparently a single optimal setting for the pressure in downstream separators does not appear to exist. In the second stage separator apparently two different, yet equally optimal, settings are revealed. In the third and final separation stage a correlation between the separator pressure and the applied inlet temperature exists, where different combinations of pressure and temperature yields equally optimal results.

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Applied Process Simulation-Driven Oil and Gas Separation Plant Optimization Using Surrogate Modeling and Evolutionary Algorithms

Andreasen¹

2020

ChemEngineering

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In this article, the optimization of a realistic oil and gas separation plant has been studied. Using Latin Hypercube Sampling (LHS) and rigorous process simulations, surrogate models using Kriging have been established for selected model responses. The surrogate models are used in combination with an evolutionary algorithm for optimizing the operating profit, mainly by maximizing the recoverable oil production. A total of 10 variables representing pressure and temperature at various key places in the separation plant are optimized to maximize the operational profit. The optimization is bounded in the variables and a constraint function is included to ensure that the optimal solution allows export of oil with a Reid Vapor Pressure (RVP) < 12 psia. The main finding is that, while a high pressure is preferred in the first separation stage, apparently a unique optimal setting for the pressure in downstream separators does not appear to exist. In the second stage separator, apparently different, yet more or less equally optimal, settings are revealed. In the third and final separation stage a correlation between the separator pressure and the applied inlet temperature exists, where different combinations of pressure and temperature yields equally optimal results.

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Separator Pressure Optimisation and Cost Evaluation of a Multistage Production Unit Using Genetic Algorithm

Cited by 4 publications

References 4 publications

Optimization of an Oil and Gas Separation Plant for Different Reservoir Fluids Using an Evolutionary Algorithm

Optimization of an Oil and Gas Separation Plant for Different Reservoir Fluids Using an Evolutionary Algorithm

Applied Process Simulation-Driven Oil and Gas Separation Plant Optimization using Surrogate Modeling and Evolutionary Algorithms

Applied Process Simulation-Driven Oil and Gas Separation Plant Optimization Using Surrogate Modeling and Evolutionary Algorithms

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