Petrophysical Properties’ Evaluation for Reservoir Characterization of AK Field, Onshore Eastern Niger Delta, Southern Nigeria
Bibliographic record
Abstract
In this study, well log derived petrophysical parameters of four (4) delineated clastic reservoirs in AK field, located onshore eastern Niger Delta have been effectively employed to characterize and assess hydrocarbon prospect potential of the field. Wireline well log data, such as gamma ray, resistivity log suite, Compensated Neutron Log (CNL) and Formation Density Compensated (FDC) were studied and analyzed for qualitative and quantitative evaluation of the formation units in the field. Lithologic discrimination aided the identification of sandy units, while fluid identification and discrimination defined the hydrocarbon saturated reservoir units in the field. Other derived parameters such as porosity, permeability, water saturation, hydrocarbon saturation, Net To Gross (NTG), net hydrocarbon pay, Bulk Volume Water (BVW) among others were employed to quantitatively characterize the delineated reservoir units, especially to establish their hydrocarbon potential. Four (4) sandy reservoir units, A1, A2, A3 and A4 which ranged in thickness from about 60-350 ft were identified from four exploratory wells AK-01, AK-02, AK-03 and AK 04 to be hydrocarbon bearing. The clastic reservoirs presented medium to relatively high formation porosity (0.27-0.38), low to average permeability value (61.6-685.5 mD) and significant to high hydrocarbon saturation (0.42-0.97). A plot of true formation resistivity values (Rt) against water saturation (Sw) indicate that all reservoir units encountered in well AK-01 are oil saturated. However, only reservoir sands A1 and A2 are predominantly oil reservoirs in well AK02 while sands A3 and A4 plot in oil and water field. In well AK-03, reservoir A1 contains only oil while the remaining reservoirs contain oil and water. The reservoir units as encountered in well AK-04 show slightly different fluid saturation pattern as reservoir A1 contains only oil, A4 is gas saturated while the remaining two reservoir units (A3 and A4) plot in the field of both water and oil.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".