Investigating Hydraulic Fracturing in Tight Gas Sand and Shale Gas Reservoirs in the Cooper Basin
Bibliographic record
Abstract
Abstract The majority of discoveries in the Cooper basin have been structural traps on regional highs, with significantly less information available from the deep tight sand and shale plays. Recently, exploration and appraisal of the large, prospective gas resources in the deep troughs began. While these plays have been known for some time (Hillis et al. 2001), data has only recently been presented detailing the unconventional targets in the Nappamerri trough (Pitkin et al. 2012). This paper focuses on unconventional reservoirs within the southern Cooper basin, specifically, a southern extension of the Nappamerri trough and the Mettika embayment, part of the Tenappera trough. Senex Energy began to review the potential of the unconventional reservoirs in its Cooper basin acreage in 2010. This paper focuses on three wells, Skipton 1, Kingston Rule 1, and Hornet 1, which were hydraulically fractured in early 2013. In the well planning stage of the project, it was identified that sufficient data needed to be collected to characterize both the formation and hydraulic fracturing behavior. The requirement for fracturing diagnostics was critical because of the complex nature of hydraulic fracturing within the Cooper basin. To manage these unknowns, the data that were collected included core testing, diagnostic injection tests on most intervals, surface tiltmeters to measure fracture azimuth and orientation, radioactive (RA) tracers to infer fracture height, and chemical tracers to estimate the flowback contribution from each stage. The results showed high treating pressures and near-wellbore pressure loss (NWBPL) in many stages of the fracture treatments. Generally, the lower the fracture gradient, the easier the job was to place and the better the reservoir quality. The RA tracers showed good containment in the one well in which they were used, with heights of 20 to 60 ft. The main barriers to height growth appeared to be changes in lithology. The surface tiltmeter results showed an azimuth that was different than expected from borehole breakout data in the basin. This has been seen in other studies in the Cooper basin. While the exact reason for this requires additional work, possible explanations are discussed within the paper.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".