Seismic Attribute Analysis for Reservoir Description and Characterization of M-Field, Douala Sub-Basin, Cameroon
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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.
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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 | 0.001 |
| 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 it