Bibliographic record
Abstract
Optimization of Hole Cleaning in Vertical Wells Using Foam Yibing Li; Yibing Li University of Alberta Search for other works by this author on: This Site Google Scholar Ergun Kuru Ergun Kuru University of Alberta Search for other works by this author on: This Site Google Scholar Paper presented at the SPE International Thermal Operations and Heavy Oil Symposium and Western Regional Meeting, Bakersfield, California, March 2004. Paper Number: SPE-86927-MS https://doi.org/10.2118/86927-MS Published: March 16 2004 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Li, Yibing, and Ergun Kuru. "Optimization of Hole Cleaning in Vertical Wells Using Foam." Paper presented at the SPE International Thermal Operations and Heavy Oil Symposium and Western Regional Meeting, Bakersfield, California, March 2004. doi: https://doi.org/10.2118/86927-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu nav search search input Search input auto suggest search filter All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE Western Regional Meeting Search Advanced Search AbstractA mathematical model of the cuttings transport with foam in vertical wells has been developed and numerically solved recently.In this study, based on the earlier solution, a numerical wellbore simulator has been developed and used for optimization of drilling hydraulic parameters (i.e. determine optimum values of foam flow rate, back pressure, foam quality, etc.) for effective cuttings transport with foam in vertical wells.Effects of key drilling parameters (i.e. drilling rate, annular geometry, formation fluid influx, etc.) on the efficiency of cuttings transport have also been investigated.A series of simplified hole cleaning charts have been developed which enable the optimum hole cleaning parameters to be determined at the rig site.IntroductionAdvantages of foam drilling including improved drilling rates, elimination of lost circulation and formation damage, stable flow regime with no slug, enhancement of bit performance, capability of handling formation water influx, and potential to save drilling cost are well documented in the drilling literature1–6.The best foam drilling practice requires effective transport of cuttings while keeping the circulating bottomhole pressure (CBHP) at minimum. Controlling the foam quality is an essential task to achieve these goals. Foam becomes unstable at the very high foam qualities.7–9 A critical foam quality (CFQ) needs to be specified at the top of the well to be able to continue drilling without allowing the foam breaking into a mist (i.e. maximum allowable foam quality at the surface).Various definitions of critical foam flow rates (required for effective cuttings transport) are found in the literature 8–10.Most of the previous research on foam drilling hydraulics focused on finding the minimum volumetric flow rate required for cuttings transport without paying much attention to the actual value of the CBHP8–10. Other hydraulic optimization programs refer to conditions to achieve minimum bottomhole pressure without paying much attention to the efficiency of the cuttings transport.11 A comprehensive approach of foam drilling optimization considering both the cuttings transport efficiency while minimizing CBHP is, therefore, needed.Other problems such as lack of criterion for choosing the optimum annular back pressure and determining maximum allowable foam flow rate to avoid wellbore instability rate also exist.In this study, hydraulic optimization of underbalanced drilling (UBD) with foam is defined as a problem which requires finding the best combination of annular back pressure, gas and liquid injection rates which would yield minimum CBHP and cuttings concentration while drilling at maximum allowable drilling rate.There are many drilling variables which would affect the CBHP, but only four of these variables (i.e. annular back pressure, gas and liquid injection rates, and drilling rate) are normally controllable at the surface and, therefore, can be considered as the most influential factors on the hydraulic optimization of foam drilling.In this paper, by using a recently-developed foam drilling model12, we also introduced guidelines for selecting optimum back pressure and gas/liquid injection rates. The findings of this study are not limited to only foam drilling. A similar approach can also be used for other types of UBD operations where a gas-liquid system is used, especially if the bubble flow or dispersed bubble flow regime is anticipated.Modeling of Cuttings Transport with FoamFoam is considered as a homogenous mixture of liquid (as a continuous phase) and gas (as a dispersed phase). Foam has a good ability of transporting cuttings even in the laminar flow regime. The gaseous phase in foam contributes to foam quality and helps to form texture which holds the solids and prevents them from falling. In multiphase flow, however, the liquid is considered as the main medium to lift the cuttings while the effect of gas on cuttings transport is not considered significant. Keywords: foam drilling, optimum foam velocity, back pressure, drilling rate, efficiency, bhp, well depth, production control, upstream oil & gas, production monitoring Subjects: Drilling Operations, Well & Reservoir Surveillance and Monitoring, Production logging This content is only available via PDF. 2004. Society of Petroleum Engineers 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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".