Evolution of Drilling and Completions in the Slave Point To Optimize Economics
Bibliographic record
Abstract
Summary This paper will detail the technological evolution of drilling and completion practices used to optimize the economic development of the Slave Point carbonate platform, specifically in the Evi and Otter fields in northern Alberta, Canada. The Slave Point platform was initially targeted for conventional production by means of vertical wells in the early 1980s. Success was marginal because of the unpredictability of localized porosity development. As a result, the full-scale commercial development of this resource was deemed uneconomic because of poor reservoir quality. More recently, however, horizontal-drilling and multistage-fracturing technology has allowed operators to open up lower-porosity horizons to improve flow capacity, to improve recoveries, and to allow for commercial development from zones previously deemed uneconomic. The Slave Point has a greater thickness and is less permeable than other tight-rock plays in Alberta, such as the Cardium and Viking. It produces high-quality, light oil with low water- and solution-gas-production rates. Despite high estimates of original oil in place (OIP) of approximately 3 to 10 million bbl per section, horizontal-well rates are still challenged because of the lower permeability through the pay section. In this regard, the continued deployment of innovation and technology has been critical in improving well-production performance, compressing project costs, and ultimately optimizing project economics. The focus of this paper is solely on one of the major Slave Point operators who has drilled 49 horizontal wells that account for 200 000 m (656,000 ft) drilled and 1,350 fracture stages in the Evi and Otter Slave Point fields since 2008. This operator has continually deployed advancing technologies to improve project economics. The information will be presented in terms of the influence of technology on well design, the optimization and deployment of the various technologies, and the demonstrated improvement on productivity and reserves recovery. The discussion will focus on three development phases that highlight the progression from vertical to horizontal technology: Vertical Appraisal Single-Lateral (SL) Development Dual-Lateral (DL) Development The case studies presented will demonstrate clearly the production impact from the use and application of these technologies. The methods and lessons learned through the use of DLs, openhole junctures, and openhole multistage systems can be applied to other unconventional formations.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".