Remedial Treatment Cures Induced Fracture/Formation Damages to Rejuvenate Frac’d Well
Bibliographic record
Abstract
Abstract A fracturing campaign was carried out in Adhi Gas Condensate Field to improve deliverability from selected low productivity wells, some suspected to be suffering from condensate banking. Tobra interval of Adhi12(T/K), the deepest well in the pop up structure, was hydraulically fractured successfully by placing 133,000 lbs of proppant into the formation. Well flow back was conducted yielding disappointing results contrary to the offset well experiences in the field. Despite extensive and continuous nitrogen lifting, the well produced at minimal liquid rates (50bbl/Day) with very high BS&W (80 - 90%). Polymer (Kill/Frac Fluids) induced fracture/formation damage, calcium carbonate pills (LCM) and deposition of organic scales inducing damage and a possible water block were suspected as likely factors restricting the well potential. This paper presents the investigative work, planning and implementation of a remedial treatment that helped successfully revive production from Adhi-12(T/K) Tobra, a well which failed to deliver the anticipated post frac potential. Aromatic Solvents, used in combination with concentrated organic acid and mutual solvents served to create a strong hydrophilic environment in the, now stimulated, critical matrix. Post remedial treatment production from the well resulted in up to 350 BBL/Day of fluids producing at ~60% BS&W. Nature and volume of the high percentage water however proves to be a concern. No Hydrocarbon-Water Contact at the two reservoir levels has yet been encountered in 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".