A Semiempirical Model for Rate of Penetration with Application to an Offshore Gas Field
Why this work is in the frame
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Bibliographic record
Abstract
Summary In this paper, we present an accurate semiempirical rate of penetration (ROP) predictive model for polycrystalline diamond compact (PDC) bits. Our model is inspired by the model of Bourgoyne and Young (B&Y) and follows an exponential form with 10 different drilling functions to account for various factors affecting ROP in drilling operations. We extend the B&Y model to the PDC bits and discuss that a different predictive model should be obtained for each formation. On top of the factors included in the original B&Y model, our model accounts for parameters such as downhole motor, equivalent circulating density, mechanical weight on bit (WOB), and wellbore inclination. In particular, we incorporate the effect of equilibrium cuttings bed thickness and downhole cuttings concentration in the ROP model. The parameters of the model are obtained using multiple regression analysis with the field data. The importance of obtaining a formation-based ROP model is tested and verified with field data, and an algorithm to determine the parameters for new data is provided. The model can be incorporated in a framework to obtain an optimal well plan for a new well or for prescribing optimal operational parameters for well planning and real-time drilling operations. The prediction performance of the proposed model is also evaluated in various formations for several test wells across an offshore gas field. Our results indicate that the proposed model is able to predict the drilling ROP with an accuracy of more than 90%.
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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 it