Overcoming a Cementing Failure: Sequenced Fracturing Technique for Remedial Application
Bibliographic record
Abstract
Abstract The Cottage Grove formation is an active U.S. mid-continent play where cemented horizontal wells are traditionally stimulated by fracturing several perforation clusters simultaneously using limited entry “perf and plug” or other multi-stage completion solutions. Leaving sections of the lateral unstimulated when fracturing over a large interval can be even more severe in un-cemented completions, where the limited entry technique cannot be relied on to distribute the flow of stimulation fluids in the reservoir. Prior to the introduction of the sequenced fracturing technique, there was no solution to reliably stimulate a large un-cemented or openhole sections. This lead to potential losses of EUR in those wells where for some unplanned event, a section of the wellbore cannot be cemented or isolated with plugs. Recently, a well was drilled and unforeseen issues resulted in 3,300 feet of casing with a completely un-cemented annulus. A remedial cement job was not a feasible option and was quickly dismissed. It was decided to use a new sequenced fracturing technique to complete the stimulation without compromising EUR. This technique uses degradable fibers and multi-sized particles as a composite pill to temporarily plug the fractures and divert stimulation slurry to other regions along the wellbore. In this instance, 20 fracturing stages separated by 12 composite pills and 9 bridge plugs were pumped in sequence to optimize the number of fractures along the wellbore and maximize production. A production and radioactive tracer log run after the operation revealed that the composite pill successfully diverted the treatment fluids from areas previously fractured to previously unstimulated portions of the lateral. As a result, the entire lateral which had been left without cement was ultimately evenly stimulated. This was confirmed by a production log which showed a constant increase in oil and gas production compared to reference wells. Two hundred and six days after the well has been put on production, the well productivity has been more than 30% higher than any offset well. The design, execution and job evaluation of the treatments are detailed in this paper, and highlight the keys to the successful treatment which turned a well initially thought to be a failure into a technical and economic success.
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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 | 0.000 | 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) | 0.002 | 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".