Geomechanical Considerations when Planning SAGD Wells, a Case Study from Cuba
Bibliographic record
Abstract
Abstract This article is the first part of the geomechanical calculations performed in order to optimize the drilling and production operations of the first horizontal wells with target formation M in the Boca de Jaruco field, Republic of Cuba. Here, the analyzed data included regional geology, tectonics and stratigraphy, different types of well logging, the pressure curves while steam operations, core samples and drilling history. The outcome of this part of the work is the assessment of the current stress regime, stress directions and the stability windows for the planned wells. Moreover, the program of additional studies and logs acquisition was elaborated, as at this stage there is not enough data to confidently quantify the stress state, the core samples are not yet tested for rock's deformation and strength properties, and it is hardly possible to find carbonate bitumen deposits under development anywhere in the world which are analogous to the Boca de Jaruco field (with the sole exception of Grosmont in Northern Alberta, Canada). After the wells are drilled (presumably by the end of 2019) and the required information is collected (such as mechanical core testing under elevated temperatures, image logs in the deviated boreholes, etc.), the second part of the work is to be performed, which would include the analysis of the drilling results and the assessment of the cap rock behavior, pore pressure and porosity-permeability changes due to steam injection.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".