Prediction of Critical Foam Velocity for Effective Cuttings Transport in Horizontal Wells
Bibliographic record
Abstract
Prediction of Critical Foam Velocity for Effective Cuttings Transport in Horizontal Wells 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/ICoTA Coiled Tubing Conference and Exhibition, Houston, Texas, March 2004. Paper Number: SPE-89324-MS https://doi.org/10.2118/89324-MS Published: March 23 2004 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Li, Yibing, and Ergun Kuru. "Prediction of Critical Foam Velocity for Effective Cuttings Transport in Horizontal Wells." Paper presented at the SPE/ICoTA Coiled Tubing Conference and Exhibition, Houston, Texas, March 2004. doi: https://doi.org/10.2118/89324-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/ICoTA Well Intervention Conference and Exhibition Search Advanced Search AbstractA mathematical model and a numerical analysis of the cuttings transport with foam in horizontal wells have been presented earlier. The model has been incorporated into a computer program and used for finding a closed form critical foam velocity (CFV) correlation.The new CFV correlation can be used to predict minimum foam flow rate required to remove, or prevent the formation of stationary cuttings beds on the low-side of the highly deviated and horizontal wells.Effects of key drilling parameters (i.e. drilling rate, annular geometry, foam quality, bottomhole pressure and temperature) on the critical foam velocity have also been investigated.Numerical examples are presented to illustrate how the CFV correlation can be used to determine required gas and liquid flow rates at the downhole conditions.IntroductionWhen planning or drilling highly deviated or horizontal wells, one of the key parameters which must be determined is the minimum drilling fluid velocity required to transport drilled cuttings up to surface and the keep hole clean. This minimum fluid velocity is called the "critical fluid velocity" (CFV).If insufficient flow rate is used, cuttings will deposit on the low side of the wellbore and form a large stationary bed which result in severe drilling problems such as high drag and torque, hole packing-off and stuck pipe. It is, therefore, crucial to know the CFV when planning and drilling a deviated well so that the adequate and economical drilling equipment can be selected and optimum parameters determined.Examples of critical fluid velocity (or critical flow rate) correlations for drilling with conventional (incompressible) drilling fluids have been presented by Luo et al.1, and Larsen et al.2Optimization of hole cleaning in horizontal wells becomes even more complex when compressible fluids such as foam and aerated mud are used as drilling fluids.Foam is favorably used as a drilling fluid in many horizontal wells because of its low density, superior cuttings transport ability and stable flow characteristics with low tendency of slug formation.3–6Good cuttings transport ability of foam has been demonstrated in the field6, although formation of stationary cuttings beds has been reported by some experimental studies.7–9In this study, a critical foam velocity (CFV) correlation has been developed by using the Li and Kuru10 model presented earlier. The effects of foam quality, borehole size, horizontal well length, bottomhole pressure (BHP), and temperature on the CFV have been analyzed and the results are presented in this paper.Mathematical Model of Cuttings Transport with Foam in Horizontal WellsRecently, Li and Kuru10 developed the transient multiphase flow model of cuttings transport with foam in horizontal wells. The brief description of the model is given in the following section.Model DescriptionThe conservation of mass relationships for foam fluid and solid phases are given by equations (1) and (2) respectively.Equations 1 and 2In equations (1) and (2), ?sf and ?ss represent the rates of change of mass of foam and solid particles per unit volume of the wellbore due to the mass transfer between layers, and sf denotes mass influx rates of water, oil and gas from the reservoir per unit volume of the wellbore. Keywords: upstream oil & gas, correlation coefficient, equation, flow rate, wellbore integrity, artificial intelligence, foam quality, coefficient, spe 89324, correction factor Subjects: Wellbore Design, Drilling Operations, Wellbore integrity, Directional drilling 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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".