State-of-the-Art Solution of Capacitance Resistance Model by Considering Dynamic Time Constants as a Realistic Assumption
Why this work is in the frame
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Bibliographic record
Abstract
To have an acceptable accuracy for water flooding projects, proper history matching is an important tool. Capacitance resistance model (CRM) simulates water flooding performance based on two tuning parameters of time constant and connectivity. Main advantages of CRM are its simplicity and fastness; furthermore, it needs only some field-available inputs like injection and production flow rates. CRM is reliable if producers receive the injection rate signal; in other words, duration of history matching must be enough so that the rate signal of injection is sensed in producers. It is a shortcoming of CRM that the results might not be accurate as a result of short history. In the common CRM, time constant is considered to be a static parameter (constant number) during the history of simulation. However, time constant is a time-dependent function that depends on the reservoir nature. In this paper, a new model has been developed as it decreases model dependency on the history matching length by shifting time axis. This new definition adds a rate shift constant to the model mathematics. Moreover, a new model is considering dynamic time constants. This new model is called dynamic capacitance resistance model (DCRM). Two reservoir models have been simulated to analyze the performance of DCRM, and, as a result, it is found that the static time constant is an erroneous assumption. Finally, the accuracy of the results has been improved since the degree-of-freedom of the CRM increased in the new version.
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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