Completion and Stimulation Design Evolution in Tight Chalk Formations in Offshore Norway
Bibliographic record
Abstract
Abstract Lower completion and acid stimulation design for low permeability chalk formations in a series of North Sea Fields were modified from historical/legacy approaches, to improve well performance for both production and injection purposes. The modifications include 1) a stimulation change from high-rate matrix acidizing to acid fracturing, and 2) optimization of ball-activated sliding sleeve design. The improvement in well performance was validated with actual productivity comparison to offset wells. Further improvements are being developed for future extended reach wells. A ball-activated sliding sleeve completion was chosen for the new, improved, horizontal well completion. Sleeve spacing, the number of sleeves and port sizes were subsequently optimized over the targeted stimulated lateral length by pipe flow modeling and by limited-entry design methods. Optimization of acid fracturing designs was achieved after incorporating critical findings from various laboratory tests that include rotating disk tests, acid-etched fracture conductivity tests, and gel shear history simulator tests. The new acid fracturing treatment designs were generated with the help of numerical simulation that were continuously fine-tuned based on new observations made during treatments and rigorous analysis of bottomhole injection pressures during the treatment. As a result of the lower completion design optimization process, different size nozzles were introduced into the sliding sleeves to treat up to 5 sleeves per stimulation stage with effective fluid diversion. This allowed 1) using available pumping weather windows effectively in the offshore environment, 2) reducing or eliminating time-consuming wireline perforation runs, 3) limiting the acid exposure to mitigate ball/seat zonal isolation events (i.e., dissolvable balls are not compatible with acid). The new and improved acid fracturing design enabled a reduction of the number of gel/acid cycles from 5 to 3 which reduced stimulation cost without losing stimulation effectiveness. The new design also resulted in productivity enhancements depending on the well location within the structure. The largest performance improvement was observed on wells that were placed further down-flank where reservoir rock is stronger and permeabilities are lower. These wells require more intensive acid fracturing treatment to generate economical and sustainable production rates. Finally, these wells also tend to require less restimulation frequency with time. This type of analysis work has not been presented previously and it optimizes lower completion for acid fracturing stimulation on a well-by-well basis. Further improvement is expected as stimulation designs and completion technology continue to evolve.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".