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Record W3154138545 · doi:10.2118/163332-pa

Field Treatment To Stimulate a Deep, Sour, Tight-Gas Well Using a New, Low-Corrosion and Environmentally Friendly Fluid

2013· article· en· W3154138545 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

VenueSPE Production & Operations · 2013
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsAkzoNobel (Canada)
Fundersnot available
KeywordsSour gasEnvironmentally friendlyCorrosionHydrogen sulfideChemistryAcid gasProduced waterSulfidePetroleum engineeringEnvironmental scienceMetallurgyMaterials scienceNatural gasEnvironmental engineeringInorganic chemistrySulfurGeologyOrganic chemistry

Abstract

fetched live from OpenAlex

Summary 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, coreflood 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 flowback 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 flowback 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 hydrochloric acid (HCl) or other chelates were used, the concentrations of iron, chrome, nickel, and molybdenum in the flowback 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.107
Threshold uncertainty score0.719

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)0.0010.000

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 head0.012
GPT teacher head0.247
Teacher spread0.235 · 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