Alpine Field Simultaneous Angle Dependent Inversion
Bibliographic record
Abstract
Abstract Simultaneous angle dependent inversion was performed on three angle stacks from the Alpine Field, located east of the NPRA in Alaska. Additionally, post-stack inversion was carried out on the near angle stack (utilizing the P-impedance log data as is), and on the far angle stack (utilizing elastic impedance generated at a range of 25 to 45 degrees). The results of the work helped the interpreters to better characterize the distribution of the reservoir in the field, and was used to facilitate well planning and reserves estimation. The inverted results suggest that the main Alpine C sand extends farther to the north than the seismic data alone indicate. This is verified by a new well which encountered the predicted thickness of reservoir sand. This allows the team to target an additional 20 million barrels of reserves. Figure 1: Map of the Alaskan North Slope, showing the location of Alpine Field.(Available in full paper) Introduction The Alpine Field on Alaska's North Slope (Figure 1) is jointly being developed by ConocoPhillips Alaska and Anadarko Petroleum Corp. The field currently produces at 100,000 barrels of oil per day, with a planned production increase to 130,000 barrels per day by 2005. The field produces mainly from the Alpine C sands, in the Late Jurassic aged Upper Kingak Formation. In order to reach the production increase, proper well planning and placement of development wells needs to be accomplished. One of the tools relied upon to reach this goal is simultaneous angle dependent inversion. This utilizes the AVO aspects of the reservoir rocks to better delineate the reservoirs. Crossplot analysis of the log data shows that post-stack seismic inversion of the full-stack or near-stack volume alone is not sufficient to discriminate the reservoir sands from the adjacent shales. There is a large overlap of the P-impedance values in the two lithologies. Description and Application of Processes Commercially available software is utilized to perform the simultaneous angle dependent inversion, which is essentially a pre-stack inversion methodology utilizing full Zoeppritz modeling and Aki-Richards approximations for some of the elastic impedance log generation. Figure 2 shows the seismic coverage and well logs that were employed in the study. The methodology is as follows. First, the horizons that are going to be used as constraints need to be interpolated/extrapolated to every trace. Next, meticulous stretching and squeezing of the logs needs to be performed to tie the well logs in time to the seismic data. The tied logs are then used to extract wavelets around every well also as in a multi-well mode to obtain an average wavelet. The wavelet estimation is performed on the near angle stack. Elastic impedance generation is done for each well to match the angle range for the mid-angle and far-angle stacks. The single-well and multi-well wavelet estimation is then carried out for the mid-angle stack and far-angle stack, utilizing the appropriate elastic impedance log data. Note that in this case, high-order anisotropic velocity analysis had been performed on each angle stack to line up events.
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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".