Reasonable Productivity Calculation and Sensitivity Analysis of Horizontal Wells in Overseas Carbonate Reservoir
Why this work is in the frame
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Bibliographic record
Abstract
Unlike domestic carbonate reservoirs, overseas carbonate reservoirs typically exhibit significant lithological variations and stronger heterogeneity. There is a lack of effective methods for energy supply and techniques to enhance oil recovery. Additionally, acquiring data during offshore platform operations presents significant challenges. Evaluating field productivity solely based on existing data remains problematic. To address this, we integrate drill stem test (DST) data and reservoir numerical simulation to calculate productivity and conduct sensitivity analysis. Initially, the DST data are collected for pressure transient analysis to estimate reservoir permeability and skin factors, which enables reasonable single‐well productivity predictions. Subsequently, detailed reservoir numerical simulations are utilized to investigate the effects of liquid production rate, production pressure drop, horizontal section length, and perforation position on field productivity, thus guiding optimal production design. Results indicate that the combination of DST data and numerical simulations is essential for accurately assessing productivity in carbonate reservoirs and supporting efficient development. With an increasing liquid production rate, cumulative oil production gradually rises, plateauing when it exceeds 7%. As production pressure drop and horizontal section length increase, the recovery factor improves up to an optimal value. Improper perforation positions, either too low or high, reduce cumulative oil production and oil recovery.
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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 | 0.001 | 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 | 0.000 | 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