Permeability Determination of the PL19-3 Field for Geologic Model Input
Bibliographic record
Abstract
Abstract The overall structure of the PL19-3 field, which is located in Bohai Bay, is an asymmetrical wrench anticline that formed by a combination of differential subsidence, strike-slip faulting, and normal faulting. Faults form the main trapping components for the individual hydrocarbon-bearing fault blocks. The reservoir sands of the deeper Guantao formation are dominantly braided fluvial sandstones, while the shallower Minghuazhen formations are dominantly meandering fluvial sands. Fault blocks penetrated by appraisal or development wells tested oil with viscosities ranging from 10 to 380 cp. Multiple vertically separate pressure systems exist in each fault block. The purpose of this paper is to present a case history that demonstrates multiple methods used to calculate permeability for input into a fine grid geologic model and ultimately a flow simulation model. Special core analysis and facies description was used to generate facies-based permeability versus porosity relationships that can be used with log-calculated variables. Permeability log curves were calculated for each well in the field, and then input them into a geologic flow model. Pressure transient analysis was used to condition the facies based porosity versus permeability relationships to ensure that they matched actual well performance. The permeability logs for all of the producing and injection wells were input into a flow simulation model. Comparisons of model predicted versus actual performance show close agreement. A good permeability estimate ultimately results in reasonable values of transmissibility, original oil in place, and sand connectivity. Advanced decline curve analysis was used as an additional method for calculation of kh, skin, and original oil in place (OOIP) and to validate model predicted performance matched actual transient, depletion, and waterflood performance behavior. In addition because this field contains reservoirs with unconsolidated sands the effect of stress dependent permeability was studied.
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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".