Simulation of Erosion in Drilling Tools for Oil and Gas Industry
Bibliographic record
Abstract
Abstract Erosion is a form of wear that will cause loss of material. It has been reported in the drilling tools used in the oil and gas industry, and it 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 modeling of erosion and the application of the developed models to improve the design of drilling tools. 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. Algorithms were developed for transient simulation of the erosion of any surface in 2-D geometry. Based on this, an "Erosion Simulator1" has been written, which is able, in combination with any CFD software, to simulate erosion in down-hole tools. Actual data from TESCO Corporation casing drilling tools2 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 increase in the life of the tool. Introduction Erosion is a form of material wears that occurs in Nature and several industries. This phenomenon has been reported in many areas of oil and gas operations. An example of erosion in drilling tools is the TESCO Corporation (hereinafter TESCO) "under-reamer" tool for casing drilling1 (Figures 1 and 2). Erosion in the drilling industry is important because it can lead to increase in time and cost of operation. In case of drilling tool failure due to 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 well-bore. Besides the cost of operation, erosion may be dangerous. Tool failure can cause blowout and be a potential for loss of lives. This paper focuses on erosion simulation in order to understand and predict erosion phenomena in the 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 1960's and 70's a number of important experiments had been 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 (Tilly3). Different velocities and particles can cause a different type of damage. During this time, scientists and researchers had found the relationship between erosion rate, type of material, size of particles, velocity and angle of impact.
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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".