Experimental Investigation of Surfactant Adsorption on Sand and Oil-Water Interface in Heavy Oil/Water/Sand Systems
Bibliographic record
Abstract
Abstract Surfactant adsorption on reservoir rocks or sands is one of the major factors that may significantly reduce the effectiveness of an alkaline/surfactant flooding for heavy oil recovery. It is difficult to determine the surfactant adsorption by measuring the difference in surfactant concentrations between before and after adsorption when water phase contains fine heavy oil drops that cannot be simply separated by using a centrifuge. In this work, an extraction method was used to determine the surfactant adsorption on sand surface. The adsorbed surfactant on sand was first "washed" by using an azeotropic mixture of isopropyl alcohol and deionized water in a Soxhlet apparatus. The amount of surfactant extracted from sands was then measured using two-phase titration after isopropyl alcohol in the mixture is evaporated. The purpose of this study is to quantitatively determine the adsorptions of surfactant on sand and at oil-water interfaces in an alkaline/surfactant flooding for heavy oil recovery. The addition of alkalis in water phase reduced surfactant adsorption on sand. Moreover, the reaction between alkalis and the acidic compounds of the heavy oil resulted in the formation of oil-in-water emulsions, which greatly increased the oil-water interface area in water phase. Experimental results showed that the formation of emulsions dramatically reduced surfactant loss to sand surface. The adsorptions of surfactant on sand and at oil-water interface were determined under various alkaline concentration and salinities. The results provide useful information for evaluating and predicting surfactant adsorption in alkaline/surfactant flooding for enhanced heavy oil recovery. Introduction Surfactants have been used for improving oil recovery for a long time. The loss of surfactants in the reservoir rock may limit the effectiveness and increase the cost of enhanced oil recovery (EOR) process. Several factors contribute to the loss of surfactants, such as adsorption at the solid/liquid interface, surfactant precipitation, and trapping in immobile phases, among others. In some cases, emulsions form in a porous medium as a result of oil-water interactions. Surfactant adsorption at the oil-water interface is also one of the factors that can make surfactant concentration even more dilute in the produced water during chemical EOR processes(1). Surfactant adsorption can be quantitatively determined by measuring surfactant concentration in aqueous solutions that are equilibrated with sands or cores. The two-phase titration test method is widely used for quantitatively measuring anionic surfactant concentrations (2–4). The conventional method of investigating surfactant adsorption on sand is to measure the difference in surfactant concentration before and after equilibrated with sands. However, when oil is introduced into the surfactant solution/sand system and emulsions are formed, the conventional method cannot give a correct estimation of surfactant adsorption on sand because surfactant will adsorb on both the oil-water interface and solid surface. Under this circumstance, the surfactant concentration determination by measuring surfactant concentration in aqueous phase cannot reflect the real surfactant adsorption on sand. Moreover, the dark color of emulsions interferes in the determination of the end point of the two-phase titration test because detection of the end point of the method depends on the visual observation of color change.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".