Successful Acid Treatments in Horizontal Openholes Using Dynamic Diversion and Downhole Mixing—An In-Depth Postjob Evaluation
Bibliographic record
Abstract
Abstract This paper discusses a relatively new acid-stimulation process that uses dynamic fluid energy to divert flow into a specific fracture point in the well, which can initiate and accurately place a fracture. The acid-stimulation process often uses two independent fluid streams: one in the pipe and one in the annulus. With this process, two different fluids can be mixed downhole with high energy to form a homogenous mixture. Four such treatments in four openhole, horizontal wells were performed in one formation. The first well was acidfractured with coiled tubing to replace many small fractures along the open hole. The second well was acid-fractured with coiled tubing, but downhole mixing concepts were used to provide in-situ generation of CO2 foam. Fewer, yet larger, fractures were placed in this well. The third and fourth wells were treated with acid using rotating and nonrotating jetting tools while mixing the acid with CO2 downhole. Many small, near-wellbore fractures were expected in these wells. Investigating the mechanism that may have contributed to these successes in the field is important. Laboratory tests were performed to analyze the jetting mechanism exposed to rock. The findings of these tests are reported in this paper.
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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 | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".