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Record W3134987057 · doi:10.1002/cjce.24092

The impact of weighting materials on carbonate pore system and rock characteristics

2021· article· en· W3134987057 on OpenAlexvenueno aff
Hany Gamal, Vagif Suleymanov, Salaheldin Elkatatny, Abdulrauf R. Adebayo, Badr Bageri

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsGeologyIlmeniteDrilling fluidCarbonateMineralogyPermeability (electromagnetism)HematitePorosityDissolutionTarim basinPore water pressureVolume (thermodynamics)DrillingGeotechnical engineeringMaterials scienceGeochemistryChemistryMetallurgy

Abstract

fetched live from OpenAlex

Abstract The infiltration of the drilling fluids into the drilled formation causes significant alterations in the rock properties due to the interaction between the drilling fluid and the rock pore system. The objective of this study is to evaluate the impact of the most common weighting materials used in water‐based mud (WBM) on carbonate pore system and rock characteristics. Rock‐mud interaction was imposed by using a customized high‐pressure high‐temperature (HPHT) filtration test cell under 2068 kPa differential pressure and 93°C temperature to simulate downhole conditions. For filtration properties, ilmenite WBM showed the maximum values (10.9 cm 3 filtrate volume and 8.7 mm thickness), while baryte recorded the lowest filtrate volume (6.2 cm 3 ) and thickness (4.2 mm). Nuclear magnetic resonance (NMR) profiles illustrated the changes in the rock pore system due to two aspects: precipitation and dissolution. A general porosity reduction was recorded with all formulations, namely 7.5% and 10.1% for hematite and ilmenite, respectively. The rock permeability showed severe damage after mud exposure that caused the rock average pore size to decrease from macro to meso‐porous. After the mud invasion, the rock electrical resistivity showed alterations with all drilling fluids. Compressional wave velocities (Vp) showed an increasing trend that ranged from 2.52% increase for baryte‐WBM to 6.35% increase by Micromax‐WBM. A general reduction was found for shear wave velocities (Vs) after mud exposure, Micromax‐WBM showed no changes in Vs, while hematite and ilmenite showed the largest decreases of 6.71% and 5.56%, respectively.

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: Empirical
Teacher disagreement score0.189
Threshold uncertainty score0.406

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 head0.004
GPT teacher head0.168
Teacher spread0.163 · 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

Citations14
Published2021
Admission routes1
Has abstractyes

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