Characterization of the Mechanisms of Debris Production to Minimize the Risk of Wellbore Instability in a Fractured Carbonate Reservoir
Bibliographic record
Abstract
ABSTRACT: The joint venture between ADNOC Sour Gas and Occidental Petroleum Corp has been producing sour gas from a carbonate reservoir in the UAE. This naturally faulted and fractured Oolitic limestone reservoir has experienced wellbore instability after five years of production, with several wells producing debris. With new wells planned in the northern part of the field, a risk assessment of wellbore instability during drilling and production is essential. This study employs 3D stress characterization to identify mechanisms causing debris production and assess wellbore stability risks. The methodology includes data integration, discrete fracture network modeling, rock mass property characterization, and numerical 3D stress modeling. Results indicate that wellbore stability is influenced by horizontal stress variability and low-strength reservoir rock due to high porosity or natural fractures. Critical drawdown pressure (CDDP) reductions lead to instability and debris production. In the northern development area, lower porosity and higher rock strength reduce instability risks, though natural fractures remain a concern. Optimizing production rates at maximum allowable drawdown pressure can mitigate debris production, but as reservoir pressure drops, instability risks increase. 1. INTRODUCTION Sour Gas has been producing from a carbonate reservoir in the UAE for a long time, but recently the producing wells encountered debris issues, prompting a 3D stress analysis and wellbore stability analysis for future developments to avoid similar problems. To better model the 3D stresses from 3D Discrete Fracture Network (DFN) model, predict locations that would be better/worse for these types of "debris failure" issues for both existing and future planned wells, whether the natural fractures do contribute to the debris production as well as wellbore stability of the planned wells in the field having potential highly depleted reservoir, the following tasks have been carried out: • Data Review, QC, and Integration. • 3D DFN Modelling. • Improve Rock Mass Property Description. • Develop Stress Model from 3D DFN Model. • Debris Wellbore Stability Evaluation. • Debris Production Prediction in the Planned Wells. The main purpose of this study was to better model the horizontal stresses, specially within the reservoir to investigate the main factors affecting debris production to prevent/minimise solid production from the planned wells to be drilled in the different part of the field.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".