Analysis of time-lapse data from the Alba Field 4C/4D seismic survey
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The 1998 Alba 3D Ocean Bottom Cable (OBC) survey was designed to accomplish multiple objectives. The primary goal was to image low impedance reservoir sands with converted wave (PS) reflections; one important secondary goal was to image fluid movement by comparing the OBC data with a 1989 streamer survey. Modelling shows that a strong original oil–water contact reflector should be visible throughout much of the field and that water saturation changes should be observable by analysing the time-lapse differences between the 1989 streamer data and 1998 OBC survey. Differences between the 1989 and 1998 seismic field data confirm that fluid changes are clearly visible near several producing and injector wells. However, extracting additional quantitative saturation information from the seismic data has proven difficult, possibly because of: (a) complex interaction between the fluids, sands and shales within the Alba reservoir; (b) moderate to poor repeatability of the seismic response to reservoir fluids. The focus of this paper is the acquisition and analysis of Alba time-lapse data. We show that production- and injection-related effects are predicted by modelling and observed in the data and then we make an attempt to relate these effects quantitatively to oil production and water injection. Despite the challenges in using the Alba time-lapse data quantitatively, the data have been successfully used qualitatively for well planning risk assessment and for guiding reservoir simulation efforts. Lessons from this work will be used in any future time-lapse surveys at Alba.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it