Case Study in Venezuela: Performance of Multiphase Meter in Extra Heavy Oil
Bibliographic record
Abstract
Abstract The objective is to present accurately the performance of the combination of a venturi and multi energy gamma ray in a case study in Venezuela. The focus will be on practical information, knowledge sharing to overcome all classical problems due to fluid behavior met by multiphase metering device in extra heavy oil including classical separator. Heavy and Extra-Heavy Oil represents more than 50% of the worldwide oil reserves, and large efforts have been spent to overcome difficulties related to this kind of oil production. Venezuela has pone of the largest reserve of HO and EHO with more than currently 1.5 trillion of oil in place. Different set of technologies and methodologies have been used to overcome the technical production and monitoring challenges in these lifted or pumped wells. Petroleos de Venezuela (PDVSA) at the opposite of Canada companies is currently producing most of the Heavy Oil from cold and therefore non thermal production methods due to historical reasons. Recently, Orocual field in Monagas Northern (Venezuela) was put in production a cluster with extra heavy oil reaching gravity from 8.6 to 11 API and with a viscosity range from 6 Pa.s to more than 20 Pa.s at line conditions. As per fact, this new production cluster did not have any data, and PDVSA could only use conventional storage tanks to try to estimate the liquid flow rate with no possibility to be able to get the gas production because no separator were able to work in these conditions. However, it was essential to PDVSA in this early phase of the development to review the performance of the field and get access to the oil, water and gas flow rates. In these challenging conditions, and after trying other multiphase meters said to work in Extra Heavy Oil, PDVSA found that the only solution was Venturi - multi energy gamma ray combination. This multiphase technology broke the extra heavy oil paradigm related to multiphase technology to measure flow rates accurately and a comparative test were capable to demonstrate when it was possible from a reference point of view that the overall uncertainty of the entire system (Venturi-Tank) was better than 2%. This extended the new multiphase technology operating envelope for PDVSA from Gas to Extra Heavy Oil and provided a unique solution and the capability to monitor and optimize in real-time the production in this field.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".