Mature Oil Field Potential Study in Southern East Asian Countries
Bibliographic record
Abstract
Abstract With the difficulty to discover large new oil fields in Southern East Asia, it is very challenge for this area to maintain its oil production. Thus to increase the final recovery and increase oil production from mature oil fields gets more and more concern from government and oil companies operating in this region. These fields are classified as depleted solutions gas drive, weak natural water drive with partial water injection and strong natural water drive with no water injection. General characteristics of regional large mature field are analyzed on the basis of typical field data from Southern East Asian countries. Good reservoir property, low in situ viscosity, long production history makes these field often with high primary recovery as high as 40-60%. However, data shows that reserve potential does exist in the secondary reservoirs, in unrecognized oil interbedded zones and in untapped oil area by existing wells. Even for very homogenous reservoirs with perforation covering all oil-bearing intervals, oil has always mainly being produced from the good part of reservoirs. Recalculation of original oil in place and construction of fine reservoir model is critical to these fields for identification of infill well locations and reperforation strategies. Water injection potential for depleted fields are studied and the major challenge is that the depleted reservoir pressure and the existence of the secondary gas cap could make the oil gain from water injections arrives only after several years of injection process. Whole field scale water injection in mature oil fields is always risky and should be only performed by satisfactory simulation and pilot results. Polymer flooding to increase the final recovery is also discussed and its potential mainly fits for the mature fields with weak natural water drive in shallow burial depth. Big potential could be tapped in mature fields for recovering more reserves while high reservoir temperature, depleted reservoir pressure, and significant investment in facilities presents challenge for EOR solutions in this area. Work over and well stimulation potential are also discussed with strong recommendation to cut corresponding investment and relevant operation cost in order to make these measures are economic for mature fields.
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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".