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Record W2014221060 · doi:10.2118/163332-ms

Field Treatment to Stimulate a Deep, Sour, Tight Gas Well using a New, Low Corrosive and Environmentally Friendly Fluid

2012· article· en· W2014221060 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Chemistry and Analysis
Canadian institutionsAkzoNobel (Canada)
Fundersnot available
KeywordsSour gasEnvironmentally friendlyCorrosionHydrogen sulfideWettingSulfideChemistryCorrosion inhibitorMaterials sciencePetroleum engineeringEnvironmental scienceMetallurgyNatural gasSulfurComposite materialGeologyOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Matrix acidizing of high temperature gas wells is a difficult task, especially if these wells are sour or if they are completed with high chrome content tubulars. These harsh conditions require high loadings of corrosion inhibitors and intensifiers in addition to hydrogen sulfide scavengers and iron control agents. Selection of these chemicals to meet the strict environmental regulations adds to the difficulty in dealing with such wells. Recently, a new environmentally friendly chelating agent, glutamic acid -diacetic acid (GLDA), has been developed and extensively tested for carbonate and sandstone formations. Significant permeability improvements have been shown in previous papers over a wide range of conditions. In this paper we evaluate the results of the first field application of this chelating agent to acidize a sour, high temperature, tight gas well completed with high chrome content tubulars. Extensive laboratory studies were conducted before the treatment, including: corrosion tests, core flood experiments, compatibility tests with reservoir fluids, and reaction rate measurements using a rotating disk apparatus. The treatment started by pumping a preflush of mutual solvent and water wetting surfactant, followed by the main stage consisting of 20 wt% GLDA with a low concentration of a proper corrosion inhibitor. Following the treatment, the well was put on production, and samples of flow back fluids were collected. The concentrations of various ions were determined using ICP. Various analytical techniques were used to determine the concentration of GLDA and other organic compounds in the flow back samples. The treatment was applied in the field without encountering any operational problems. A significant increase in gas production that exceeded operator expectations was achieved. Unlike previous treatments where HCl or other chelates were used, the concentrations of iron, chrome, nickel, and molybdenum in the flow back samples were negligible, confirming low corrosion of well tubulars. Improved productivity and longer term performance results confirm the effectiveness of the new chelate as a versatile stimulation fluid.

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.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.194
Threshold uncertainty score1.000

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)0.0260.001

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 head0.007
GPT teacher head0.214
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

Quick stats

Citations12
Published2012
Admission routes1
Has abstractyes

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