Hydraulic Optimization of Foam Drilling For Maximum Drilling Rate
Bibliographic record
Abstract
Hydraulic Optimization of Foam Drilling For Maximum Drilling Rate E. Kuru; E. Kuru University of Alberta Search for other works by this author on: This Site Google Scholar O. M. Okunsebor; O. M. Okunsebor University of Alberta Search for other works by this author on: This Site Google Scholar Y. Li Y. Li University of Alberta Search for other works by this author on: This Site Google Scholar Paper presented at the SPE/IADC Underbalanced Technology Conference and Exhibition, Houston, Texas, October 2004. Paper Number: SPE-91610-MS https://doi.org/10.2118/91610-MS Published: October 11 2004 Cite View This Citation Add to Citation Manager Share Icon Share MailTo Twitter LinkedIn Get Permissions Search Site Citation Kuru, E., Okunsebor, O. M., and Y. Li. "Hydraulic Optimization of Foam Drilling For Maximum Drilling Rate." Paper presented at the SPE/IADC Underbalanced Technology Conference and Exhibition, Houston, Texas, October 2004. doi: https://doi.org/10.2118/91610-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE/IADC Managed Pressure Drilling and Underbalanced Operations Conference and Exhibition Search Advanced Search ABSTRACT The theory of hydraulic optimization of drilling with conventional (incompressible) drilling fluids is well known and has been widely practiced in the industry.Classical theory of hydraulics optimization for maximum drilling rate calls for either the use of empirical correlations or the use of optimization theory to maximize some arbitrary objective functions such as maximum bit hydraulic horsepower or jet impact force.Concept of hydraulic optimization for maximum drilling rate when drilling with foam, however, is not well investigated. Compressible nature of the foam makes the use of conventional optimization theory difficult.A transient-mechanistic model of cuttings transport with foam has been developed and numerically solved recently. In this study, the new model has been used to re-visit classical theory of hydraulic optimization (i.e. maximum bit hydraulic horsepower/jet impact force criteria).A new methodology has been suggested to determine optimum gas/liquid injection rates for maximizing drilling rate when drilling with foam while keeping the bottom hole pressure minimum.The new method can be easily used in the field to determine best combination of gas/liquid injection rates and total bit flow area (i.e. jet nozzle sizes) such that maximum drilling rate is achieved. Keywords: optimum back pressure, equation, artificial intelligence, flow rate, optimum gas liquid ratio, drilling fluids and materials, pressure loss, foam drilling, production control, drilling fluid management & disposal Subjects: Drilling Operations, Drilling Fluids and Materials, Well & Reservoir Surveillance and Monitoring, Drilling fluid management & disposal Copyright 2004, SPE/IADC Underbalanced Technology Conference and Exhibition You can access this article if you purchase or spend a download.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".