Multiple Proppant Fracturing of Horizontal Wellbores in a Chalk Formation: Evolving the Process in the Valhall Field
Bibliographic record
Abstract
Summary Oil production from this chalk field has been improved significantly over the last 3 years using multiple proppant fractures placed from horizontal completions. Following early successes, the engineering effort focused on increasing value through engineering innovation and increased productivity. This paper describes, through case histories and field data, advances made in the design and execution of these completions over 13 wells in the Valhall field. Wellbore completion activities and stimulation are performed now as a stand-alone process. Using specialized large-diameter coiled-tubing (CT) equipment allows ongoing drilling operations to be performed concurrently. This has reduced daily spread costs significantly while bringing wells on production in a much-reduced time frame. This lower cost environment also has allowed innovative field procedures to be developed resulting in further improvements such as proppant plugs for isolation between stimulation zones, novel bottomhole assemblies (BHA's) for perforating, and treatments using recycled proppant to minimize waste. Productivity is the driver for economic success. Treatmentdesign requirements have evolved through laboratory testing to account for longer-term downhole-operating conditions below the bubblepoint while also improving initial conductivity. Field data to date through production logging operations have confirmed the hydrocarbon contribution from each fracture. This is used to validate the effectiveness of each treatment. Normalized well productivities continue to improve and the challenge is to maintain the rate of evolution through the improved application of new and existing technologies.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 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".