Field Foam Applications in Enhanced Oil Recovery Projects: Screening and Design Aspects
Bibliographic record
Abstract
Abstract An in-depth analysis covering over forty foam applications in Enhanced Oil Recovery (EOR) projects and numerous production well treatment operations was conducted, to obtain insights on screening and design of such applications. Foam can be used to solve conformance problems caused by either a thief zone or gravity override; proper identification of the cause, as well as of the affected production well(s) is basic to definition of the problem. Either blocking/diverting foams or in-depth mobility control foams can be placed through the injection wells. On the other hand, foam is placed in production wells mainly to mitigate an override problem. The most important factors in foam assisted EOR projects are:manner of foam placement in the reservoir (injection of pre-formed foam, co-injection foam and SAG or surfactant alternating gas foam),reservoir pressure andpermeability. While pre-formed foams are effective in the treatment of production wells, co-injection foam and SAG foam can be employed for solving specific sweep problems. For designing a steam-foam project (which is a low pressure foam application), foam quality in the range 45% to 80% should be considered. In this application, a co-injection foam is employed and the additives (surfactant and non-condensable gas) are injected intermittently (on and off), superimposed on a continuous steam injection. Injection cycles as short as 7 days are common. Under suitable conditions, an oil rate increase of 1.5 to 5 times, a decrease in water cut by 20 %, and an incremental oil recovery of 6%-12% OOIP can be achieved with this implementation. At high pressure, such as in gas miscible flooding, foam application can result in excessive mobility reduction factors, and injectivity reduction. Due to this reason, in these projects, alternate injection of surfactant solution and gas (SAG foam) is favoured over a coinjection mode of placement. Introduction The first review of field applications of EOR foams was published in 19891, and it was not until 1994–1995 that more advanced EOR foam Reviews(2, 3, 4)appeared in the public domain. Building on the previous reviews, more than 40 foam field tests are analyzed here. Unlike the previous reviews, our focus was on the reservoir engineering aspects of foam application, mainly on the mode of foam placement with respect to the problem to be solved. Other differences from the previous reviews include:For the various field tests presented, all available details are tabulated to enable an easy analysis of the data.A reservoir engineering analysis is conducted for the basic recovery process during which foam injection was implemented, in order to establish "a-posteriori", the nature of problem solved.Interpretation of results of field foam applications is based on the results of recent laboratory foam tests on long distance foam propagation In this paper only the key conclusions of our analysis are presented; 19 tables containing the supporting details accompany this paper, and they can be made available by the Journal of Canadian Petroleum Technology, upon request.
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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 | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".