On the Accuracy of Surface Movement Measurement over a SAGD Operation in Northern Alberta through Effective Survey Design
Bibliographic record
Abstract
Abstract Surface movement over a Steam Assisted Gravity Drainage (SAGD) operation can be related to production and injection. The amount and location of surface change can indicate the location of thermal dilation within the reservoir and may provide an indication of conformance. While the deformation expected in a SAGD operation is related to the depth of the reservoir and the stratigraphy, the typical ground movement is approximately 2-5 cm/year. This represents a relatively slow inflationary process over the ground. The movement may be confused with changes that are related to seasonal ground changes including water level changes in muskeg, for instance. This work provides a description of the accuracy of Interferometric Synthetic Aperture Radar (InSAR) measurement techniques including corner reflectors and advanced point and neighbourhood algorithms designed for the measurement of ground movement in Northern Alberta. The paper will describe the application of these methods to measuring surface movement above a SAGD operation. Specifically, this article describes methods for the determination of the accuracy of ground movement estimates as derived from InSAR. An effective survey design is critical to the monitoring of ground movement. The location and availability of measurement points is crucial to the use of high resolution Synthetic Aperture Radar (SAR) satellites for monitoring. The design and implementation of a survey includes an understanding of the relationship between available infrastructure and the ground signal to be expected. However, a critical aspect of monitoring is a verification of the accuracy of the measurement provided. By using repeated observations and even a combination of satellites, we show how the measurement of accuracy can be provided on an operational basis. This work provides a novel description of the calculation of accuracy of ground movement using emerging techniques in multiple-track / multiple-satellite observation of enhanced oil recovery operations.
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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 | 0.001 | 0.001 |
| 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".