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Record W2604919942 · doi:10.2118/185746-ms

Optimization of Metal-on-Metal Lubricants for Coil Tubing Applications

2017· article· en· W2604919942 on OpenAlexaboutno aff
Scott Sherman, Harvey Quintero, Candace Moriyama, Sebastian Sessarego, Craig Fraser

Bibliographic record

VenueSPE Western Regional Meeting · 2017
Typearticle
Languageen
FieldEngineering
TopicLubricants and Their Additives
Canadian institutionsnot available
Fundersnot available
KeywordsMechanical engineeringHammerTribologyLubricantLubricationComputer scienceElectromagnetic coilPetroleum engineeringMaterials scienceEngineering

Abstract

fetched live from OpenAlex

Abstract The development of horizontal well completion techniques has untapped a massive amount of hydrocarbon resources previously economically unreachable. Extended-reach horizontal well designs are now the rule rather than the exception and introduce a myriad of new challenges associated with downhole operations. Numerous mechanical approaches have been implemented to overcome deleterious frictional forces intrinsic to extended reach Coil Tubing (CT) interventions; cutting edge mechanical techniques rely on devices such as downhole tractors and fluid hammer tools to avoid helical buckling, and eventual CT lock-up. The most daunting factor associated with the application of these tools is the cost which is especially important in the current energy resource industry downturn. Drag-reducing agents (DRA) appear to be the common denominator in extended reach CT interventions. To date, synergistically paired metal-filming lubricants and fluid friction reducers provide a cost-effective method to enhance weight on bit (WOB) required while running in and/or pulling out of hole (RIH/POOH) CT strings. Given the dynamic nature of CT operations, carrier fluids experience extreme conditions changes (temperature, pressure and/or physicochemical), during their tubular residency time. The change in environmental conditions can result in poor dispersibility of DRA's, and therefore, render them ineffective through a lack of contact with the metal. Herein, this paper presents details of a thorough tribology and rheological analysis of commercially available DRA's in different oil field brines, and the corresponding field case studies evaluating data reproducibility. Lab testing data includes 4 ball (ASTM D4172A) testing as well as Reichert friction and wear analysis test results. The OFITE EP (extreme pressure) lubricity tester type equipment, which was originally conceived to reproduce coefficients of friction (COF) for drill string/mud simulations, has been historically included in metal-on-metal (MOM) lubricant analysis. A rapid method was implemented involving a sled and plate COF type tester. Normally used for measuring the friction between two dry surfaces, it was adapted for measuring COF of MOM lubricants currently in use during CT operations in the Western Canadian Sedimentary Basin (WCSB). Lubricity testing on the top MOM lubricant performers showed a COF reduction in the range of 11 −28%, when 150 mm/min sled speed was tested. Also, through the rheological and qualitative analysis of the carrier fluid, dispersibility appears to be improved with the addition of the fluid friction reducer. In addition to the sled-plate COF testing analysis and field case data validation, this study will include an oscillatory shear rheological analysis of the carrier fluid, by using the Haake RheoStress®6000. This will help us to understand the viscoelastic behavior and its relationship with MOM dispersibility.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.572
Threshold uncertainty score0.508

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 head0.029
GPT teacher head0.265
Teacher spread0.236 · 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 designSimulation or modeling
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

Citations7
Published2017
Admission routes1
Has abstractyes

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