Ungani Oil Field, Canning Basin - Evaluation of a Dolomite Reservoir
Bibliographic record
Abstract
Core supported study of the heterogeneous Ungani dolomite reservoir architecture is driving development drilling and upgrades to field resource estimates. Vuggy connected and macro non-connected pore space was directly measured over a 70m continuous core using 3D structural analysis of CT-scans. Plug density measurements indicate non-connected or sub-140 micron resolution contribution of around 1% to 2.5% (pu) for the tight matrix, but all remaining porosity potentially contributes to oil production. The high resolution core porosity data is vertically repositioned and upscaled to calibrate neutron-density and sonic petrophysically derived porosities which are inadequate to resolve productive zones using conventional reservoir cut-offs. Conditioned resistivity image data correlated exceptionally with directly measured connected porosities. Reservoir properties were extrapolated to all wells across the Ungani field giving field net/gross estimates of up to 63% and porosities over 30% pu in some vuggy and brecciaed zones. The heterogeneity and prolific nature of the uppermost 17m of reservoir had not been previously recognised due to poor log data coverage and access at the casing points. Recent re-analysis of this section at Ungani-3 with Chemostrat ICP-OES-MS analysis of ditch cuttings was instrumental in proposing additional drilling to re-target this zone. Mineralogy analysis is used to calculate rock grain densities and help calibrate neutron-density derived porosity logs over the Ungani field. Up-scaled core porosity correlates well with density and sonic porosity logs. Resistivity logs adjusted for minerology can also be used to predict porosity and support the use of resistivity image logs to identify vuggy zones and estimate porosity at a higher resolution than conventional logging tools. A field static model was populated with three facies distributed over vertical zones according to the distribution encountered in the core porosity analysis and well logs, and iteratively matched to the dynamic pressure data and field production history which exhibits field scale multi-Darcy horizontal permeability and protection from vertical water cut. Further drilling and downhole artificial lift is planned to extend field production rates to 3000 bbls/day. Increased confidence in this regionally developed reservoir is supporting further exploration of undrilled prospects in this immature and under-explored trend
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".