Improving Stage Isolation in Vaca Muerta Wells Through Observations from an Integrated Fiber Optic Pilot
Bibliographic record
Abstract
Abstract The productivity of an unconventional well depends on reservoir quality that can be selected but not controlled and completions that can be optimized. The challenge with improving a completion design is the lack of information about the actual downhole performance. An ultimate requirement for an effective completion is to have isolation between two adjacent stages. The observations and recommendations for improving stage isolation are made from the first integrated fiber optic (FO) pilot in Vaca Muerta. Shell conducted an integrated diagnostic pilot in Vaca Muerta that included acquisition of multiple data types, such as: permanent fiber optics installation, surface microseismic monitoring, downhole pressure gauges, mudlogging, open and cased hole logging. One of the objectives for this project was to evaluate stage isolation performance for different plug types. Stage isolation was analyzed based on the DAS and DTS interpretation in two wells equipped with permanent fiber optic cable. Complementary, isolation integrity test (IIT) was performed in three stages of each well during wireline pump down operations. These results are compared with the FO interpretations. This paper summarizes observations from the real-time monitoring of operations on two wells landed in different zones. Three solutions for stage isolation were tested in these wells. A statistical analysis of their performance is presented. The interpretation of the isolation integrity test is summarized and discussed. The isolation results between FO and IIT are cross-checked. While all stages with IIT data have good isolation based on FO interpretation, three of IIT tests indicate the lack of isolation. This discrepancy is discussed in the paper. During the execution of the pilot, observations were made about the impact of the treatment schedule on the plug performance. Modifications were implemented during execution and recommendations are made for future completions. The investigation extends to evaluating plug isolation failures using FO monitoring after pad-wide fracture stimulation. We enhance our analysis by including multifinger caliper measurements (pre and post stimulation) to assess deformation and ovality in FO-instrumented wells, aligning these observations with plug failure instances. A post-fracturing ovality difference between landing zones was identified. While plug isolation failures are often associated with ovalization, it's essential to note that no specific ovality threshold was found to reliably predicts plug isolation success. These insights deepen the understanding of stage isolation challenges across the well pad.
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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 | 0.001 |
| 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) | 0.000 | 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".