Steam-Injection Experiments for Recovery of Heavy Crude Oil of an Iranian Field
Bibliographic record
Abstract
Steam Injection experiments for Recovery of Heavy Crude oil of some Iranian Field Alireza Tabatabaei; Alireza Tabatabaei Search for other works by this author on: This Site Google Scholar Sirus Shafiei; Sirus Shafiei Search for other works by this author on: This Site Google Scholar Saeid Rajabzadeh; Saeid Rajabzadeh Search for other works by this author on: This Site Google Scholar Amir Naser Haghlesan Amir Naser Haghlesan Tabriz Pertochemical Company Search for other works by this author on: This Site Google Scholar Paper presented at the SPE International Thermal Operations and Heavy Oil Symposium, Calgary, Alberta, Canada, November 2005. Paper Number: SPE-96959-MS https://doi.org/10.2118/96959-MS Published: November 01 2005 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Tabatabaei, Alireza, Shafiei, Sirus, Rajabzadeh, Saeid, and Amir Naser Haghlesan. "Steam Injection experiments for Recovery of Heavy Crude oil of some Iranian Field." Paper presented at the SPE International Thermal Operations and Heavy Oil Symposium, Calgary, Alberta, Canada, November 2005. doi: https://doi.org/10.2118/96959-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE International Thermal Operations and Heavy Oil Symposium Search Advanced Search AbstractThermal methods for enhanced oil recovery account for the large share of the world's production. Steam flooding is one of the oldest commercial methods to enhance the heavy oil recovery. In due respects, experiments of steam injection into a sand pack were performed to study the recovery of heavy oil (API<20) and a lighter oil (API>20) of Iranian field.Two different porosity of sand pack were used and the experiments were conducted with four different types of heavy oil, with different API, to study their effect on recovery.An experimental setup was designed and used to inject the steam into the sand pack.Using different pressures at each experimental run, results show that there is an optimum pressure, which is the characteristic of each reservoir and must be determined by field experiments.The rate of injected steam has an important effect on recovery and an optimum rate exists for ultimate recovery.Steam injection is more effective for heavy oil reservoirs, as for light oil reservoirs; there is the risk of fingering which results in production of steam without sufficient oil production.Even though, in literature, some authors have indicated that the steam injection could be used for the lighter oil reservoirs (API~ 24 or more) but based on the conducted experiments it is proposed to take more care.IntroductionIran is one of the oldest countries in the world of producing oil.The exploration of oil in Iran dated back to the Ghajar era, which the first producing oil well was drilled in 1908 and its producing rate was 500 bbl/day. Then after many other fields were developed (i.e. Haftgel 1927, Aghajari 1936, Gachsaran & Pazanan 1937, etc.). Since then the oil has played a major role in Iran's economic. Figure 1 presents the production and consumption of the Iran's oil.Conventional methods of oil production can produce only about (average) 20 percent of oil in place. After that the natural pressure of the field decreases and different methods can be used to raise the pressure and keep the oil production in economic range. These methods are called secondary recovery methods. In this stage of production normally water or produced gases are injected to keep or increase the pressure. After secondary recovery period more sophisticated methods should be used to produce the remaining oil [1–7]. Different methods in this stage can be used. One of oldest methods which is specially suitable for heavy oil fields is steam injection which is one of the thermal methods for enhancing oil recovery (EOR) of heavy oil.Many advancements have been made both in experimental and field studies to improve the heavy oil recovery.These include many experimental, fields and numerical methods as well as combination of them [8–28]Clossman et al. and other authors [29–31] conducted experiments of injecting steam in sand pack saturated with oil. They concluded that the oil production rate after injecting several PV of steam is dependent on the water/oil viscosity ratio and that at high ratios the oil production continues after steam production. In another study Demiral et al. and many others [32–36] conducted experiments with steam and foam and used two types of surfactant and found that steam injection with foam increases the oil production about %45. Bagci et al. & Sukkar [37,38] studied light oil production using steam in lime reservoirs and used oil with various API. They concluded that in higher API the production increases and also it increases with lowering steam flow rate. The mechanism of oil production by steam injection involves diffusion of condensed water, evaporation of light components, and diffusion of steam [39–48]. Here we have conducted several tests to evaluate the recovery by steam injection using heavy oil. Keywords: heavy oil, sand pack, thermal method, flow rate, doe report, recovery, haghlesan, porosity, steam flooding, injection Subjects: Improved and Enhanced Recovery, Thermal methods This content is only available via PDF. 2005. SPE/PS-CIM/CHOA International Thermal Operations and Heavy Oil Symposium You can access this article if you purchase or spend a download.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".