Production Technology Selection for Iranian Naturally Fractured Heavy Oil Reservoirs
Bibliographic record
Abstract
Abstract Global heavy oil (µ > 100 cP in situ) resources in carbonate rocks are estimated at 1.6?1012 bbl [250?109 m3]; one-third is in the Middle East. Iran has over 50?109 bbl [8? 109 m3], comprising > 40% of Iran's proven oil reserves, mostly in naturally fractured carbonate rocks (limestone and dolomite). Most reported Iranian heavy oil is mobile at reservoir conditions, implying ? < 2000 cP; several have coldflow tested oils of 6–18 °API. Current heavy oil contribution to national production is negligible, partly because appropriate technologies have yet to be implemented. New technologies developed in the last 20 years in Canada constitute a true revolution for heavy oil production, but are not yet applied widely to fractured carbonates. For Iran, assuming ultimate RF of 20% for heavy oil and 30% for conventional oil, heavy oil reserves comprise about 30% of the total recoverable oil. In this paper, occurrence, geological and reservoir engineering properties in selected heavy oil reserves in Iran are discussed. These selected reserves are technically evaluated for the implementation of several commercialized heavy oil production technologies. Results from this feasibility study show a promising future for some technologies in Iranian heavy oil reservoirs. However, final selection of the most appropriate production technologies requires more detailed reservoir evaluation and technical screening. A complementary research program is recommended for the next stage of technical production technology evaluation for Iranian heavy oil reservoirs in fractured carbonates. Introduction The Heavy and Extra Heavy Oil Resource Because of increasing demand on the fixed and relatively well-defined global light oil reserves, exploration and production of viscous oil have accelerated. Heavy oil may be defined as oil with an API gravity < 20 °API.[1] However, this does not describe the flow properties, which are better defined using oil viscosity.[2] Some oils may be heavy (low API) but with a relatively low viscosity because of reservoir temperature; for example, the deeper Faja del Orinoco oil in Venezuela is typically 8.5 -9 °API with a viscosity of 1,000 -4,000 cP at 40–45 °C. In Canadian reservoirs at 5 °C and 100 m deep, similar oil has a viscosity over 106 cP. Oil viscosity and its temperature sensitivity control flow rate in thermal production; thus, it is far more important in economic assessment than API gravity. Many suggest that heavy oils be defined as having viscosities >100 and <10,000 cP at reservoir conditions;[3, 4, 5] then, "bitumen" refers to oil having a reservoir viscosity >10,000 cP. We will use abbreviations: HO for heavy oil and XHO for extra-heavy oil with a viscosity <10,000 cP, but with a density <10 °API (as in the Orinoco deposit). HO used alone includes XHO and bitumen (i.e. all oil with µ > 100 cP), unless otherwise specified. Major occurrences of HO and XHO are reported in Canada, Venezuela, Russia, Kazakhstan, Iran, China, Iraq, Oman, Egypt, Kuwait and several other countries.[3]
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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 | 0.001 | 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".