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Record W1981657953 · doi:10.2118/2007-090-ea

Microbial Treatment of a Sulphide-laden Stream in a Continuous Biofilm Reactor

2007· article· en· W1981657953 on OpenAlexafffundabout
Kimberley Tang, Mehdi Nemati

Bibliographic record

VenueCanadian International Petroleum Conference · 2007
Typearticle
Languageen
FieldEngineering
TopicMetal Extraction and Bioleaching
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiofilmChemistryMicrobiologyEnvironmental scienceEnvironmental chemistryBacteriaBiology

Abstract

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Abstract Biogenic production of hydrogen sulphide in oil reservoirs subjected to water flooding is a serious concern for the oil industry. The produced sulphide contaminates the oil, gas, and the injected water. Toxicity and corrosivity of sulphide, and environmental concerns associated with the use of these sulphide-laden streams dictate the removal of sulphide prior to their use. Treatment of the contaminated streams can be achieved by physicochemical methods or through biological processes relying on the catalytic activity of sulphide-oxidizing bacteria. Compared with the conventional processes, biological treatment offers several advantages, including operation at ambient pressure and temperature, feasibility for the treatment of smaller streams, and the absence of expensive catalysts. In the present work microbial treatment of a sulphide-laden synthetic brine with a composition similar to that of a typical produced water has been studied in batch system as well as a continuous biofilm reactor. Using a sulphide-oxidizing, nitrate-reducing microbial culture originated from a Canadian oil reservoir and sand as a carrier for immobilization of the bacteria, the impacts of sulphide concentration and its volumetric loading rate on the performance of the treatment system have been investigated. Introduction The applications of sulphide biooxidation are widespread. Such applications include the removal of sulphide from gaseous Streams1, control of souring in oil reservoirs2,3, treatment of sulphide-laden wastewater4 and produced water2, as well as generation of electricity in microbial fuel cells5. There are several well established physicochemical methods for the treatment of sulphide-containing streams. These processes employ various removal techniques including chemical or physical absorption (Alkanolamine process), thermal or catalytic conversion (Claus process), and liquid phase oxidation (LO-CAT ® process) 6. Microbial oxidation of sulphide can occur through metabolic activity of different microorganisms including phototrophic and chemolithotrophic bacteria. The objective of the present work is to study the kinetics of sulphide biooxidation in a batch system and a continuous biofilm reactor, using a mixed microbial culture enriched from the produced water of a Canadian oil reservoir. This culture is shown to be dominated by Thiomicrospira sp. CVO. Experimental Procedures and Apparatus Microbial Culture and Medium The microbial culture used in this study was enriched from the produced water of a Canadian oil reservoir. Coleville synthetic brine (CSB) was used for growth and maintenance of the culture. The CSB medium, made with reverse osmosis water, contained: 119.8 mM NaCl, 2.76 mM MgSO4 •7H2O, 1.63 mM CaCl2 •2H2O, 0.37 mM NH4Cl, 0.20 mM KH2PO4, 8.29 mM NaC2H3O2 •H2O, 9.89 mM KNO3, 50 mM C4H11NO3, and 0.5 mL/L of a trace element solution consisting of 0.5 mL/L concentrated H2SO4 (98%), 13.5 mM MnSO4 •5H2O, 1.75 mM ZnSO4 •7H2O, 8.1 mM H3BO3, 0.1 mM CuSO4 •5H2O, 0.1 mM Na2MoO4 •2H2O, 0.19 mM CoCl2 •6H2O, and 3.6 mM FeCl3. All medium components except Na2S were dissolved in reverse osmosis water and the pH was adjusted to 7.5 using 2 M HCl. The medium was purged wit

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.583
Threshold uncertainty score0.950

Codex and Gemma teacher scores by category

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

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 head0.018
GPT teacher head0.237
Teacher spread0.219 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2007
Admission routes3
Has abstractyes

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