Estimation of Multiple Petrophysical Parameters for Hydrocarbon Reservoirs with the Ensemble-Based Technique
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Bibliographic record
Abstract
The ensemble-based history matching technique has been successfully applied to simultaneously estimate multiple petrophysical parameters for hydrocarbon reservoirs. The tuning petrophysical properties include horizontal and vertical permeability, porosity and three-phase relative permeability curves. Four scenarios with different combination of the tuning parameters have been evaluated. The ensemble-based history matching technique is found to be capable of estimating multiple petrophysical parameters by conditioning the reservoir geological models to production history. The uncertainty range of production data generated from the updated models is reduced compared to that of initial models. However, the history-matched models may not always provide good production prediction results, especially when absolute permeability and relative permeability are tuned simultaneously. This further illustrates the non-uniqueness of the history matching solutions. In addition, three-phase relative permeability curves are found to be estimated with good accuracy when absolute permeability fields are known. Key words : Petrophysical parameters; Assisted history matching; Ensemble kalman filter (EnKF); PUNQ-S3 model
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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 | 0.000 |
| 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 it