Simulation of Erosion in Drilling Tools for the Oil and Gas Industry
Bibliographic record
Abstract
Abstract Erosion is a form of wear that has been found on the drilling tools used in the oil and gas industry that can, in some cases, severely shorten the life of the tools. In spite of its importance, there has been virtually no attention paid to it in drilling engineering research. This paper focuses on the modelling of erosion and the application of the developed models to improve the design of drilling tools. The mechanism of erosion, which is controlled primarily by the impact velocity and angle, has been formulated based on experimental and theoretical work done in material science. These algorithms were developed for transient simulations of the erosion of any surface in 2D geometry. Based on these, an "Erosion Simulator(1)" has been written, which is able, in combination with any computational fluid dynamics (CFD) software, to simulate erosion in downhole tools. Actual data from TESCO Corporation casing drilling tools(2) has been used to calibrate the physics of the process and validate the software. The simulator has been used to modify the geometry of the under-reamer casing-drilling tool, which resulted in a substantial decrease in erosion rate and therefore an increase in the tool's life. Introduction Erosion, as a form of material wear, has been reported in many areas of the oil and gas industry. An example of erosion in drilling tools is the TESCO Corporation (hereinafter TESCO) "underreamer" tool used in casing drilling(1) (see Figures 1 and 2). Erosion in the drilling industry is important because it can lead to an increase in time and cost of operation. In the case of drilling tool failure from erosion, eroded parts must be replaced. This will cause unexpected extra rig time in order to pull out the drill string and run it with new parts into the wellbore. Besides the cost of operation, erosion may be dangerous. Tool failure can cause a blowoutand be a potential for loss of lives. This paper focuses on an erosion simulation in order to understand and predict erosion phenomena in drilling tools, with the ultimate goal of improving tool design and extending its life. History of Erosion Research Erosion (i.e., a form of wear) occurs when fluid containing solid particles impacts a solid surface. The intensity of erosion is commonly measured as a specific weight loss (rate of material removal from the surface) and expressed as Er (the weight of material removed by unit weight of impacting particles). During the 1960s and 1970s, a number of important experiments were done in the area of metal wear that laid the foundation for the current understanding of the phenomena. Erosion experiments during that period covered impact velocities up to 550 m/s and particle sizes of up to 1,000 μm [Tilly(3)]. Different velocities and particles can cause different types of damage. During this time, scientists and researchers determined the relationship between erosion rate, the type of material, size of particles, velocity, and angle of impact.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".