Produced Fluids Separation Using A Coalescer Column
Bibliographic record
Abstract
Abstract A coalescer column - a simple, inexpensive, and environmentally friendly technology - successfully removed water from produced heavy oil emulsions. The laboratory study tested the use of the column, and the effects of column length, column packing size, temperature, flow rate, demulsifier concentration, and water addition. The use of the column improved basic sediment and water (BS&W) values after 4 hours of settling time by an average of 38%. Flowing the emulsions through the column at lower temperatures and much lower demulsifier concentrations matched the results of conventional treating. The results indicated that incorporating a coalescer column into a treatment facility allowed the reduction of demulsifier concentration from 250 ppm to 70 ppm, translating to an annual cost savings of $320,000 to $1,100,000 per battery. The column also promoted faster treating. Water droplets grew by as much as 34%, suggesting that treating time could be sped up by an average of 21% and as high as 80%. Introduction Heavy oil producers have reported that chemical costs represent the highest fraction of their operating expenses. A small survey of battery operators showed that demulsifier concentrations at heavy oil batteries ranged from 200 to 333 ppm (1 L/5 m3 to 1 L/3 m3) in 2001. 1 These operators also reported that demulsifier doses were rising: within the last five years, the concentration of demulsifier used to treat a typical heavy oil has risen by 25 to 50% for many reasons. A battery in the heavy oil region can easily spend over $100,000 annually on demulsifying chemicals. The two treating batteries which supplied emulsion samples for this set of experiments were estimated to spend between $400,000 and $1,100,000 every year on such costs. Heating costs are also considerable: some heavy oil batteries heat their pressurized treating vessels to 130 °C. In addition to the cost of heating, producers are becoming increasingly aware of the importance of reducing greenhouse gas production. An alternate, inexpensive, and environmentally friendly technology to help separate oil and water would be highly desirable. One promising separation method is of the passive mechanical type: a coalescer column. Over the past 18 years, the Saskatchewan Research Council (SRC) and the University of Regina have applied this technique to break water-in-oil emulsions. 2–8 Whereas our previous work focused on resolving slop oils, this study applied the coalescer column to the treatment of wellhead emulsions. A literature survey on the subject of coalescers and resolving crude oil emulsions is deceptive. A number of researchers use the word coalescer, but apply it to plate separators or pipes with no packing. Our use of the term restricts it to a pipe filled with some sort of porous packing material which aids in the coalescence of dispersed droplets of an emulsion. In their review of the literature on coalescing media, Stocker et al. listed the many types of packing materials that have been tested. 9 These fall into the categories of fixed media, granular packing, and fiber packing.
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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) | 0.001 | 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".