Computational Fluid Dynamics modeling applied to drilling and cleaning operations: A science mapping analysis
Bibliographic record
Abstract
The purpose of this study is to provide an overview of the main research themes developed in the last decade in the field of computational fluid dynamics applied to drilling, cleaning and related operations in the oil and gas industry. To accomplish that we propose a Science Mapping Review analysis taking into account part of the guidelines for Sys-tematic Literature Reviews available in literature and the SciMAT and VOSviewer software workflow. Finally, as part of the literature reviewed, the InOrdinatio index was applied to the documents surveyed. The search string proposed was planned to include petroleum wellbore, drilling and cleaning operation and computational fluid dynamics as the terms to the research string. The SCOPUS and Web of Science databases were used to data survey, the documents were limited to articles and proceeding conferences from 2013 to 2022 in English language. Among the results, the VOSviewer anal-ysis showed that Journal of Petroleum Science and Engineering, Journal of Natural Gas Science and Engineering and Journal of Petroleum Exploration and Production Technology are the most cited journals. On the other hand, the analy-sis using the InOrdinatio index showed that the most important journal was Journal of Petroleum Science and Engineer-ing, covering 75% of the top 20 most influential documents. The top 10 countries with the highest contributions were China, United States, Iran, Qatar, Canada, United Kingdom, Norway, Malaysia, India and Brazil. Their publications represent almost 90% of the total and more than 50% of the documents come from United States and China. Finally, concerning to the keywords, the co-occurrence analysis of keywords from VOSviewer, the conceptual structure and longitudinal analysis from SciMAT and the analysis of documents from InOrdinatio method showed similar results. According to the VOSviewer analysis, the themes with a greater impact in recent documents, from 2019 to 2022, are associated to "cutting transport", "hole cleaning", "oil field equipment", "infill drilling", "drill string", "drilling fluids" and "two phase flow" applied to multiphase flows in equipment, risers and wellbore annular in drilling and completion operations such as cutting deposition and transport in non-Newtonian drilling fluids and nanoparticles taking into account the annuli eccentricity, pipe rotation, particle characteristics and orbital motion and new geometries to improve the hole cleaning. The SciMAT analysis showed keyword related to "cutting transport” include non-spherical particle, nanoparticles and non-Newtonian flow; “hole cleaning” include granular materials, deposition, eccentric annuli, un-conventional reservoir and orbital motion; "infill drilling” include bottom hole assembly, design and operation, down-hole conditions and cutting bed; and "drilling fluids" keywords such as rheology behavior and properties. The InOrdi-natio addresses themes related to annular flow and cutting transport including CFD-DEM coupling, effect of drill pipe rotation, non-Newtonian fluids, particle shape, horizontal, inclined and bends, pipe geometry and drill pipe eccentrici-ty.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.015 | 0.012 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".