Seismic Attribute Analysis for Reservoir Description and Characterization of M-Field, Douala Sub-Basin, Cameroon
Bibliographic record
Abstract
Complexity of discontinuous reservoir units occurring within the shale-rich N’kapa Formation and the limitation of well-articulated interpretations deduced from 2D seismic data, led to a new approach of interpretation of the 3D seismic data of M-Field located offshore Douala Sub-Basin, Cameroon. The study aimed at determining the subsurface distribution of the delineated reservoir units in terms of geology, structures, stratigraphic architecture as well as the lateral and vertical distribution of each of the reservoir units across the field.Well log signatures were analyzed and interpreted to identify hydrocarbon bearing sands, which were subsequently mapped to the 3D seismic record using the generated 1D synthetic seismogram to tie the well information to the seismic volume. The delineated hydrocarbon bearing sand bodies were mapped as horizons on the 3D seismic record in addition to subsurface structural mapping to generate subsurface depth structure maps. Further still, amplitude variation surface seismic attribute analyses aid the delineation of geometry of depositional channels across the M-Field. Two horizons ( X 1 and Y 1 ) were interpreted and used to generate surfaces attribute maps. The M-Field reservoirs present stratigraphic architecture which suggests levees or confined channel sands deposit as the dominant channel deposit. X 1 and Y 1 are stratigraphic trappedhydrocarbon systems, however, while X 1 is located up-dip, Y 1 is situated on a monoclinic slope in the down dip area of X 1 , such that Y 1 stratigraphically seats on X 1 but eroded around X 1. The high amplitude associated with the delineated erosional surface likely results due to difference in acoustic properties across the interface owing todifference in age and composition of the two units. This suggests that the delineated reservoirs are two different units which are not correlateable as earlier postulate.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.001 | 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".