Successful Application of Horizontal Through Pipe Petrophysical Technology to Model the Montney Formation
Bibliographic record
Abstract
Abstract Worldwide the oil and gas industry acknowledges that technology is, and will continue to be, the driving force in allowing oil and gas producers and service companies; to continue to deliver results that will improve production performance in a safe, environmentally sound and cost-effective manner. This is especially true for unconventional producers who are also faced with unlocking the technical challenges of unconventional reservoirs. To aid in evaluating the Montney liquids-rich resource play, a new through pipe well logging technology was utilized to provide reservoir formation log data through drill pipe on new horizontal wells and through casing on a vertical well. This technology was run in the 7GEN KAKWA 13-24-65-5W6 cased vertical well, then compared to open hole well logs and to core data, both standard and special core analysis. The same through drill pipe logs were run in 14 horizontal wells in the Kakwa and Karr fields. The data collected in the horizontal wells was compared to the vertical core well and to the strip log data on each well. Calibration of the vertical though casing log data to core analysis provides an accurate determination of the reservoir properties in the lateral section of the horizontal wells. The cost / benefit of utilizing through pipe technology was analyzed. The analysis took into consideration direct and indirect costs associated with data collection and risks associated with horizontal data collection. By evaluating the associated costs and risks it was determined that through pipe data acquisition provides much lower risks and costs less than other data acquisition methods.
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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".