Bibliographic record
Abstract
Technology Focus I am not here to discuss the process of detailing the optimum completion design. However, I do believe that there is no single parameter to serve as the "rule of thumb" to judge well-completion designs for the life of the field. Earlier this year, I attended the first SPE Unconventional Reservoirs Conference at Keystone Resort and Conference Center, in Keystone, Colorado. Afterward, I attended a workshop presented by Shell Energy Canada and Calgary Research Centre. Both presentations highlighted the emerging and applied technologies in use worldwide for recovery of unconventional hydrocarbon resources. As with all conferences, I had the opportunity to engage in discussion with many world experts from various operating/service companies and academia. After thorough discussions with all parties, I have reviewed an abundant reference list on well completions that use sonic stimulation. Many were anecdotal. Some may argue this was because of the nature of the studies, in which improved production was observed after some coincidental event that may or may not have been responsible for incremental hydrocarbon production. In my opinion, all studies should be scientific, not anecdotal, so long as the sonic stimulation was applied with the intent of enhanced hydrocarbon production. Thorough discussions, backed with research on this subject, ensure that certain aspects of the well's operation, such as safety, availability, and efficient use of equipment inventory, are not overlooked. Many readers will agree that not all well completions achieve this objective. I have found that many unconventional-reservoir failures may not be a function of the manner in which they were designed, but may be simply the result of purely unknown complex reservoir-related mechanisms. I advocate that operating companies use advanced diagnostic procedures that match and predict performance to estimate reservoir potential, well deliverability, and completion efficiency accurately. I believe in focusing on some of the best practices, such as economics (i.e., net present value), as the main driver. Hence, alternative completions such as sonic stimulation may be a viable alternative to reduce workover costs and improve ultimate hydrocarbon recovery. Completions Today additional reading available at the SPE eLibrary: www.spe.org SPE 113106 • "Optimization of Completion Interval To Minimize Water Coning" by M. Tabatabaei, SPE, University of Louisiana at Lafayette, et al. SPE 113670 • "Through-Tubing Inflatable Technology Deployed on a Downhole-Tractor System Provides Real-Time Cost Savings" by Graeme M. Kelbie, SPE, Baker Oil Tools, et al. SPE 108656 • "Harsh-Environment HP/HT Gas-Condensate Production Cleanup Experiences—Kristin Field" by Arild Fosså, Expro, et al. Additional reading available at OnePetro: www.onepetro.org OTC 19341 • "Expandable Screens: Optimized Horizontal Gas Production Through Collaboration" by Alejandro Lopez Lara, Pemex, et al.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| 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) | 0.000 | 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".