Bibliographic record
Abstract
This article, written by Assistant Technology Editor Karen Bybee, contains highlights of paper SPE 88773, "Rebirth of a Mature Carbonate Gas Pool," by K.C. Carr, SPE, and M. Fiori, BP Canada Energy Co., prepared for the 2004 Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, UAE, 10-13 October. Operation of a mature pool requires increasing cost control and infrastructure optimization and consolidation to maintain profitability. The decision to initiate this type of reservoir-management plan, sometimes described as “harvest,” is driven in part by reservoir-performance analysis and in part by commodity prices. The full-length paper presents the account of a 3.7-Tcf sour-gas pool in Alberta, Canada, and the technical impact of harvest on field operations, reservoir performance, and ultimate recovery. The combination of new production-decline analysis and a well workover with surprising results led to a complete change in reservoir interpretation. Introduction Management of mature pools is not a new challenge. In the Western Canadian basin, the surge of exploration and development activity in the 1950s and 1960s has left a legacy of very mature pools, with many of these 40- to 50-year-old pools still producing. Records show that of the 30,000 gas pools discovered in Alberta, 2,000 were discovered before 1970. In the aggregate, these pools represent 15 Tcf of remaining recoverable reserves. Each of these pools was at some point declared mature on the basis of the science of the day and treated as a harvest candidate (i.e., a pool with very limited upside where the best strategy is to control cost and produce what is left without further investment).
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 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".