Publikationer pr. år
Publikationer pr. år
Projektdetaljer
Beskrivelse
Abstract
To avoid environmental pollution, the water treatment process is really essential for reinjecting the produced water (PW) into the reservoir or discharging it into the ocean based on the discharge legislation in Oil and Gas offshore industry. Based on the new regulations established by the Danish Environmental Protection Agency, the OiW concentration should be less than 30ppm in the Danish part of the North Sea, and the total quantity of oil discharged in the ocean must be also less than 222t per year.
In this project, we intend to propose a novel advanced process control using AI-enhanced sensor fusion and investigate its application in offshore produced water treatment. The significant purpose of the project is to achieve zero-harmful discharge of the produced water treatment which contributes to decreasing the environmental impact from the oil and gas production. Hence, novel AI-enhanced sensor fusion algorithm would be considered for more accurate and reliable online monitoring of Oil-in-Water (OiW) concentration in the first step. Then, proposing a novel advanced control solution for optimizing the de-oiling hydrocyclone's performance is the other significant purpose in this project, by integrating the hydrocyclones efficiency into the feedback control loop beside the water level and pressure drop ratio (PDR) index.
Funding: Danish Hydrocarbon Research and Technology Center (DHRTC)
To avoid environmental pollution, the water treatment process is really essential for reinjecting the produced water (PW) into the reservoir or discharging it into the ocean based on the discharge legislation in Oil and Gas offshore industry. Based on the new regulations established by the Danish Environmental Protection Agency, the OiW concentration should be less than 30ppm in the Danish part of the North Sea, and the total quantity of oil discharged in the ocean must be also less than 222t per year.
In this project, we intend to propose a novel advanced process control using AI-enhanced sensor fusion and investigate its application in offshore produced water treatment. The significant purpose of the project is to achieve zero-harmful discharge of the produced water treatment which contributes to decreasing the environmental impact from the oil and gas production. Hence, novel AI-enhanced sensor fusion algorithm would be considered for more accurate and reliable online monitoring of Oil-in-Water (OiW) concentration in the first step. Then, proposing a novel advanced control solution for optimizing the de-oiling hydrocyclone's performance is the other significant purpose in this project, by integrating the hydrocyclones efficiency into the feedback control loop beside the water level and pressure drop ratio (PDR) index.
Funding: Danish Hydrocarbon Research and Technology Center (DHRTC)
| Status | Igangværende |
|---|---|
| Effektiv start/slut dato | 01/01/2022 → 31/12/2024 |
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Publikation
- 1 Konferenceartikel i proceeding
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Impact of System Initial Values on Multivariate LSTM Neural Network Performance: A Finding From a Control Process Perspective
Kashani, M., Jespersen, S. & Yang, Z., 2024, (Accepteret/In press) Proceedings of The 11th International Conference on Control, Mechatronics and Automation (ICCMA 2023) . 6 s.Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review