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Record W4367184031 · doi:10.1002/ghg.2217

Optimum chain desalination process design for treatment of high TDS brine: A case assessment for future treatment of extracted brine from Shenhua CO<sub>2</sub> storage site

2023· article· en· W4367184031 on OpenAlexaff
Hesam Bazargan Harandi, Liwei Zhang, Ali Kargari, Pang‐Chieh Sui, Yan Wang, Meiheriayi Mutailipu, Hao Lü, Qi Li

Bibliographic record

VenueGreenhouse Gases Science and Technology · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsBrineDesalinationTotal dissolved solidsMembrane distillationWater treatmentEnvironmental scienceProcess engineeringWaste managementChemistryEnvironmental engineeringMembraneEngineering

Abstract

fetched live from OpenAlex

Abstract Carbon dioxide‐enhanced water recovery (CO 2 ‐EWR) is a promising strategy for managing reservoir pressure build‐up and mitigating the risk of fault activation resulting from CO 2 injection in deep saline aquifers. CO 2 ‐EWR can also be employed for supplying the required water for different applications after a treatment stage for the produced saline water. In this study, a brief review on CO 2 ‐EWR technology and its necessities are first carried out. After that, the feasibilities, advantages, and challenges of various available treatment technologies that can potentially be used to treat high total dissolved solids (TDS) brine are comprehensively assessed. Based on comprehensive evaluation on technologies, a chain desalination process, consisting of pretreatment, main treatment, and post treatment, is proposed as a strategic path for the treatment of high TDS brine extracted from the Shenhua CCS site. It is concluded that coagulation‐flocculation and gravity filtration are needed as primary stages to remove suspended particles, while membrane distillation (MD) is selected as a suitable main treatment technology for high TDS Shenhua brine. Then, MD treatment is comprehensively discussed for a small‐scale treatment of extracted Shenhua brine assuming that the pretreated brine is free of suspended solids. After presenting the heat and mass transfer equations for direct contact membrane distillation (DCMD), a mathematical thermodynamic model is programmed in EES (Engineering Equation Solver) software to briefly analyze the performance parameters of DCMD. The results indicate that the designed DCMD, in the absence of auxiliary systems and considering the inherent temperature of extracted brine from different formations, has the capability of producing 15.1 kg m −2 hr of freshwater from the extracted brine of the Shihezi formation layer. In the case of employing the auxiliary system of flat‐plate collector (FPC) combined with heat exchanger (HX) to heat up the extracted Shenhua brine to the desired temperature of 80°C, the amounts of produced flux are enhanced by 133%, 72%, and 45% for the brine extracted from Liujiagou, Shiqianfeng, and Shihezi formations, respectively. Using the yearly solar radiation model in TRNSYS software, the maximum solar radiation on the tilted surface at the location of Shenhua project in Inner Mongolia Autonomous Region of China reaches 3800 kJ m −2 hr at 1 PM on April 1. Considering maximum solar radiation on the tilted surface, it is proved that a small‐surface FPC can supply the required energy to heat up the extracted brine from its inherent temperature to the desired temperature of 80°C. © 2023 Society of Chemical Industry and John Wiley & Sons, Ltd.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.294
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2023
Admission routes1
Has abstractyes

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