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Record W4246297604 · doi:10.2118/2002-134-ea

Biologically Formed Calcium Carbonate: A Durable Plugging Agent For Enhanced Oil Recovery

2002· article· en· W4246297604 on OpenAlexaffabout
Mehdi Nemati, G. Voordouw

Bibliographic record

VenueCanadian International Petroleum Conference · 2002
Typearticle
Languageen
FieldMaterials Science
TopicCalcium Carbonate Crystallization and Inhibition
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCalcium carbonateCarbonateEnhanced oil recoveryCalciumPetroleum engineeringMaterials scienceChemical engineeringChemistryGeologyComposite materialMetallurgyEngineering

Abstract

fetched live from OpenAlex

Abstract Biological formation of calcium carbonate, using purified urease enzyme or urease enzyme produced by a bacterium isolated from a Canadian oil field, were studied in a batch system. The extent of enzymatically produced CaCO3 increased with increases in enzyme and reactant concentrations and temperature. In the presence of bacteria the quantity of produced CaCO3 was dependent on urea concentration, with the highest achieved with 15 g/L urea. Bacterial production of CaCO3 was less sensitive to temperature. Plugging studies in unconsolidated porous media indicated that in situ formation of CaCO3 could lead to a significant decrease in permeability, with the extent of plugging being dependent on the concentration of enzyme and reactants, as well as temperature. Introduction The injection of water into oil reservoirs (water flooding) is common for enhancement of oil recovery. When water is injected into a reservoir, flow is preferentially diverted into high permeability zones from which oil has already been recovered during the primary production. Increased permeability variation decreases volumetric sweep efficiency of injected water and cross flow complicates this problem by allowing flow between contrasting layers, leading to an unacceptably high ratio of produced water to oil (1). The excessive production of water can be controlled by selective plugging of high permeability areas in the reservoir. Selective plugging of the reservoir by bacterial biomass, or insoluble biopolymers produced by microorganisms has been suggested as a means to improve microscopic and volumetric sweep efficiencies within the geological formation(2–4). Recently, the use of bacterially precipitated inorganic compounds such as calcium carbonate and silica has been suggested as an effective method for selective plugging of reservoirs(2). The controlled biological formation of CaCO3 is based on the decomposition of urea to carbonate and ammonium ions by the catalytic action of urease enzyme, either introduced into the system or produced in situ by a bacterium with urease activity, and the reaction of the produced carbonate ion with calcium chloride. In the present work enzymatic and bacterial formation of calcium carbonate were studied, using urease enzyme and a bacterium isolated from a Canadian oil field. The results of plugging tests, using enzymatically formed calcium carbonate, in unconsolidated porous media system are described. Theory and Experimental Procedures The efficiency of enzymatically formed calcium carbonate in plugging of porous media was studied in a model core system. This was a modification of the system used by Ferris et al.(2), for mineral plugging studies. A schematic diagram of the system used in the present study, allowing testing of three different reaction conditions simultaneously, is shown in Figure 1. Glass columns (ID 2.5 cm and H 30 cm), packed with a mixture of sand (Dave 225 micron) and glass beads (Dave 75 micron), were used as model cores. A glass tube (ID 0.5 cm and H 55 cm) with overflow open to the atmosphere was devised in the liquid pathway to create a constant head pressure. Before initiating the plugging experiment, the designated column was connected to the peristaltic pump and distilled water was pumped into the column at a specified rotation speed of the pump.

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 categoriesInsufficient payload (model declined to judge)
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 score0.799
Threshold uncertainty score0.997

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)0.0090.000

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 head0.040
GPT teacher head0.248
Teacher spread0.207 · 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.

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

Citations2
Published2002
Admission routes2
Has abstractyes

Explore more

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