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Record W2070362098 · doi:10.2118/74665-ms

Selection and Application of a Non-Damaging Scale Inhibitor Package for Pre-Emptive Squeeze in Mungo Production Wells

2002· article· en· W2070362098 on OpenAlexaff
G. M. Graham, A. Gyani, M. M. Jordan, Catherine Strachan, Ryan P. McClure, Ian Littlehales, A. Fitzgerald

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicCalcium Carbonate Crystallization and Inhibition
Canadian institutionsNalco (Canada)
Fundersnot available
KeywordsSelection (genetic algorithm)Scale (ratio)Production (economics)ScalingEnvironmental scienceComputer scienceAgricultural engineeringPulp and paper industryEngineeringMathematicsEconomicsPhysics

Abstract

fetched live from OpenAlex

Abstract This paper presents the challenges of identifying and deploying a non-damaging non-aqueous scale inhibitor for pre-emptive squeeze into the largest dry producer in the BP-operated Mungo field. In order to pre-empt potential downhole scaling & subsequent impact on production, the Mungo asset requested a non-damaging, pre-emptive squeeze option for application prior to water breakthrough. Scale inhibitor squeezes are usually deployed post water breakthrough and when scale is predicted to form as a result of the co-mingling of incompatible produced brines. On the other hand, pre-emptive squeezes are preferred either when scaling is predicted from the start of water breakthrough or when the time required to mobilise chemicals etc. for an intervention is too long, placing production at risk. For Mungo, both these last scenarios applied: the predicted scaling tendencies were severe and immediate on water breakthrough, and the difficulty in mobilising a support vessel etc. to perform the job required careful planning and time. BP and their Mungo partners initiated a chemical selection test programme through their CMS provider to identify a non-damaging "Best in Class" chemical squeeze option for Mungo. The CMS partner with responsibility for chemical management of the Mungo asset organised an independent laboratory to screen commercially sensitive, "non-aqueous" products (non-aqueous carrier phase) from both their own product range and those of their competitors for potential application. When assessing chemical performance, clear selection criteria were issued to all the participating chemical suppliers prior to commencing any laboratory work. The chemicals were required to: (a) cause minimal formation damage (or <10% damage in core flood tests); (b) provide a maximum squeeze life (ca. 1 year was requested by the Mungo asset); (c) be compatible with the incumbent corrosion inhibitor (>95% corrosion inhibitor performance was required); and (d) be compatible with Mungo brine. Other selection criteria also included environmental category, cost, impact on facilities, practicality of deployment and proven track record. This paper focuses on the main selection criteria (a) and (b). Comparative core flooding tests presented in this paper demonstrate that only one application fell within the specification of < 10% reduction in permeability. Having selected the least damaging non-aqueous chemical, further core flood tests were designed to simulate: (a) injection into a lower permeability zone of the reservoir (or potential formation damage effects in the near wellbore region); and (b) the impact of chemical shut-in or adsorption. Two pre-emptive squeeze trials of a novel "non-aqueous" scale inhibitor have now been conducted in wells W168 and W163 on the BP Mungo field. The scale inhibitor was deployed by bullheading, using injection quality base oil as a preflush and overflush. In neither case was formation damage seen as a result of the treatment, with no change in oil or water rates pre and post-squeeze. In summary, the paper discusses how BP, Mungo partners and the CMS providers worked together to find the best technical solution to an important challenge facing many other fields and new developments, i.e. how to effectively select and deploy a non-damaging pre-emptive scale inhibition squeeze treatment. Independent testing has enabled the selection and deployment of a highly commercial "non-aqueous" application from an alternative non-CMS service provider.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.354

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 head0.009
GPT teacher head0.247
Teacher spread0.239 · 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

Citations22
Published2002
Admission routes1
Has abstractyes

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