Bibliographic record
Abstract
Abstract Most oil fields do not produce more than 45% of the oil-in-place, even after enhanced oil recovery schemes have been applied. Most of this unproduced oil is missing because most displacement techniques by-pass significant portion of the original reserve. Finding this missing oil can lead to significant economic windfalls because the infrastructure for additional oil recovery is already in place and the cost of production is likely to be minimal. In this paper, all existing monitoring techniques, including 4D seismic and downhole seismic sensors, are reviewed. This is followed by a comprehensive review of emerging technologies in subsurface monitoring. These techniques include multi-well seismic, electrical resistivity tomography, electromagnetic and ultrasonic imaging, acoustic and fibre-optic imaging, as well as laser/infrared or MRI/NMR visualization near the wellbore region. A detailed analysis indicates that for an accurate reservoir engineering analysis, geostatistical models should have information of 1m scale. This is the only scale that would satisfy the representative elemental volume (REV) requirement of an enhanced oil recovery (EOR) system. This scale length is orders of magnitude higher than that of core samples and at least an order of magnitude lower than the conventional seismic data. This data gap constitutes the weakest link between geophysical information and reservoir engineering. Any attempt to reconstitute the reservoir without information regarding petrophysical properties and fluid saturations in the 1m level, one risks falling into the trap of multiple solutions – a typical problem of history matching through reservoir simulation. To obtain a resolution of 1m scale, one must investigate the possibility of using 50-2000 Hz seismic frequency range. While this seismic range cannot be used with vertical seismic profiles (VSP) because of the travelling distance constraints, multiwell imaging can be used with multi-component receivers. This system, in combination with borehole seismic sources, can provide one with the desired resolution. The same system can be used in combination with resistivity tomography, a method that has recently given satisfactory results for tracking ground-water contamination. The images can be further refined with acoustic and fibre-optic imaging techniques. These techniques can provide satisfactory details to track viscous fingering, wormholes, and other time-dependent properties of an active reservoir. Finally, infrared/laser or MRI/NMR imaging of a wellbore is still in its nascent state of development, but holds great promises for the future applications of real-time monitoring and eventual dynamic reservoir management.
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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".