An Overview of Heavy and Extra Heavy Oil Carbonate Reservoirs in the Middle East
Bibliographic record
Abstract
Abstract Global heavy oil resources in carbonate rocks have been estimated to be on the order of 1.6 trillion barrels1, of which about one-third may occur in the Middle East. Published resources for specific fields and proprietary databases, however, suggest a more modest STOOIP resource base of approximately 120 BBO. Owing to its vast light oil reserves, documentation in the public domain on Middle Eastern heavy oil accumulations is not complete but enough information is available to assemble a reasonable picture of the geological setting, reservoir and oil quality issues and the status of cold and EOR production in the region. Productive heavy oil carbonate fields can be grouped into two categories:low matrix permeability, fracture dependent andmatrix permeability dependent production. Fracture enhanced, low matrix permeability production is dominant and occurs in Oman, Iran, Iraq, Syria, Turkey and Egypt and includes producing fields such as Qarn Alam in Oman and Issaran and Bakr-Amer in Egypt. In Iran, several fractured carbonate fields have successfully cold tested oil qualities on the order of 10o API. Wafra, located in the Partitioned Neutral Zone (PNZ) of Kuwait and Saudi Arabia, is the most notable example of an accumulation that has ample matrix permeability to allow economic cold production without significant fracture enhancement. Ultimate recovery from these fields is heavily dependent on oil viscosity and the ability to lower it. EOR implemented in the region include a CO2 flood at Bati-Raman in Turkey, a completed pilot crestal steam injection at Qarn Alam and an ongoing pilot steamflood at Wafra that commenced in February 2006. These three fields, along with Issaran, where a CSS project began in 2006, constitute the bulk of carbonate heavy oil activity in the Middle East. Current carbonate heavy oil production is in the range of 125–150 TBD (0.5% of Middle East production). Introduction Current worldwide supply and demand dynamics, coupled with the dramatic escalation of crude prices beginning in 2003, has brought a renewed interest in heavy oil (HO) and bitumen deposits. The allure of the bitumen and heavy oil resource base is compelling, as it is estimated to contain on the order of 70% of the earth's oil endowment relative to a 30% share for conventional oil2. In the forefront of global heavy oil efforts is decades old cold wellbore-based production in Venezuela and bitumen mining in Alberta, Canada. Other notable developments are ongoing in California and Indonesia. The Middle East, with its vast light oil reserves found predominately in carbonate rocks, is not presently a significant producer of heavy oil and nor should it be expected to be by virtue of its dominant position in light oil reserves. However, in view of tightening worldwide light oil supplies a survey of heavy oil potential in Middle East carbonate reservoirs is needed to assess future prospects for replacing or increasing oil production in the area. This paper is an initial effort to catalog Middle East heavy oil carbonate fields that have been documented in the literature and summarize some of their basic reservoir and fluid properties while providing some insights into their productive potential today and going forward. Most of the material in this paper is based on information from published technical papers, primarily from the SPE, with supplements from the databases of IHS Energy3 and Wood Mackenzie4 for completeness.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".