Risk-based Stochastic Optimization of Evaporation Ponds as a Cost-Effective and Environmentally-Friendly Solution for the Disposal of Oil-Produced Water

Izady, Azizallah; Nikoo, Mohammad Reza; Bakhtiari, Parnian Hashempour; Baawain, Mahad; Al-Mamari, Hilal; Msagati, Titus A.M.; Nkambule, Thabo T.I.; Al‐Maktoumi, Ali; Chen, Mingjie; Prigent, Stéphane

doi:10.1016/j.jwpe.2020.101607

Cited by 16 publications

(2 citation statements)

References 53 publications

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“…These scenarios were input to the stochastic optimization model through computing objective functions for all scenarios considering each set of decision variables. In more detail, the objective functions for this stochastic optimization model were calculated for the earlier mentioned 600 flash flood scenarios through the conditional value-at-risk (CVaR) approach (Supplementary Materials, Section S2), which is a reputable coherent risk measurement tool [67,68].…”

Section: Uncertainty Assessments By Conditional Value-at-risk (Cvar) ...mentioning

confidence: 99%

A Stochastic Conflict Resolution Optimization Model for Flood Management in Detention Basins: Application of Fuzzy Graph Model

Nematollahi

Bakhtiari

Talebbeydokhti

et al. 2022

Water

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Floods are a natural disaster of significant concern because of their considerable damages to people’s livelihood. To this extent, there is a critical need to enhance flood management techniques by establishing proper infrastructure, such as detention basins. Although intelligent models may be adopted for flood management by detention basins, there is a literature gap on the optimum design of such structures while facing flood risks. The presented study filled this research gap by introducing a methodology to obtain the optimum design of detention basins using a stochastic conflict resolution optimization model considering inflow hydrographs uncertainties. This optimization model was developed by minimizing the conditional value-at-risk (CvaR) of flood overtopping, downstream flood damage, and deficit risk of water demand, as well as the deviation of flood overtopping and downstream damage based on non-linear interval number programming (NINP), for four different outlets types via a robust optimization tool, namely the non-dominated sorting genetic algorithm-III (NSGA-III). Conflict resolution was performed using the graph model for conflict resolution (GMCR) technique, enhanced by fuzzy preferences, to comply with the authorities’ priorities. Results indicated that the proposed framework could effectively design optimum detention basins consistent with the regional and hydrological standards.

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Section: Uncertainty Assessments By Conditional Value-at-risk (Cvar) ...mentioning

confidence: 99%

A Stochastic Conflict Resolution Optimization Model for Flood Management in Detention Basins: Application of Fuzzy Graph Model

Nematollahi

Bakhtiari

Talebbeydokhti

et al. 2022

Water

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“…To date, the major physical and chemical methods developed and applied to treat ASP flooding wastewater include membrane distillation [8,9], membrane filtration [10,11], air flotation [12], electrocoagulation [13], and adsorption [14]. However, the high operating and maintenance costs are the shortcomings of these technologies, which have a negative impact on their overall performance and limit the expanded application of these technologies [15].…”

Section: Introductionmentioning

confidence: 99%

Efficiency and bacterial diversity of an improved anaerobic baffled reactor for the remediation of wastewater from alkaline-surfactant-polymer (ASP) flooding technology

Wei

Zhang

et al. 2022

PLoS ONE

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Alkaline-surfactant-polymer (ASP) flooding technology is used to maximize crude oil recovery. However, the extensive use of alkaline materials makes it difficult to treat the water used. Here, an improved multi-zone anaerobic baffled reactor (ABR) using FeSO4 as electron acceptor was employed to treat the wastewater from ASP flooding technology, and the effects on major pollutants (hydrolyzed polyacrylamide, petroleum substances, surfactants suspended solids) and associated parameters (chemical oxygen demand, viscosity) were evaluated. Gas chromatography-mass spectrometry (GC-MS) was used to follow the degradation and evolution of organic compounds while high-throughput DNA sequencing was used to determine the bacterial diversity in the ABR. The results obtained after 90 d of operation showed decreases in all parameters measured and the highest mean removal rates were obtained for petroleum substances (98.8%) and suspended solids (77.0%). Amounts of petroleum substances in the ABR effluent could meet the requirements of a national standard for oilfield reinjection water. GC-MS analysis showed that a wide range of chemicals (e.g. aromatic hydrocarbons, esters, alcohols, ketones) could be sequentially removed from the influent by each zone of ABR. The high-throughput DNA sequencing showed that the bacteria Micropruina, Saccharibacteria and Synergistaceae were involved in the degradation of pollutants in the anaerobic and anoxic reaction zones, while Rhodobacteraceae and Aliihoeflea were the main functional microorganisms in the aerobic reaction zones. The results demonstrated that the improved ABR reactor had the potential for the treatment of wastewater from ASP flooding technology.

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Optimal Water Allocation from Subsurface Dams: A Risk-Based Optimization Approach

Izady

Khorshidi

Nikoo

et al. 2021

Water Resour Manage

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Risk-based Stochastic Optimization of Evaporation Ponds as a Cost-Effective and Environmentally-Friendly Solution for the Disposal of Oil-Produced Water

Cited by 16 publications

References 53 publications

A Stochastic Conflict Resolution Optimization Model for Flood Management in Detention Basins: Application of Fuzzy Graph Model

A Stochastic Conflict Resolution Optimization Model for Flood Management in Detention Basins: Application of Fuzzy Graph Model

Efficiency and bacterial diversity of an improved anaerobic baffled reactor for the remediation of wastewater from alkaline-surfactant-polymer (ASP) flooding technology

Optimal Water Allocation from Subsurface Dams: A Risk-Based Optimization Approach

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