A Framework for Mechanistic Modeling of Alkali-Surfactant-Polymer Process in an Equation-of-State Compositional Simulator
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Alkaline/Surfactant/Polymer (ASP) is an important chemical EOR process that involves the generation of in-situ soap through the reaction of the acid component in the oil with the alkali, in conjunction with intra-aqueous reactions, mineral dissolution and precipitation, micro-emulsion behavior and salinity gradient. The mechanistic simulation of ASP is very complex and has been carried out with specialized chemical flood simulators. Current trends in EOR processes show an interest in hybrid methods where chemical flooding is combined with other EOR methods such as low salinity waterflood, foam and gas/CO2 injection. Thus, it is beneficial to develop such capabilities in an Equation-of-State (EOS) compositional simulator for screening and combining different EOR processes. This paper presents a framework for mechanistic modeling of the ASP process within an EOS compositional simulator. A new approach for modeling the Winsor Type I, II and III micro-emulsion phase behavior is introduced based on laboratory solubility data. In the Type III system, the emulsion is distributed judiciously between the oil and water phase without the introduction of a third liquid phase. The optimal salinity variation with the soap/(soap + synthetic surfactant) mole fraction is modeled. This feature allows the design of salinity gradient, an essential requirement for a successful ASP flood. The above physics are coupled with comprehensive geochemistry calculations (intra-aqueous reactions and mineral precipitation/dissolution reactions) and three-phase oil/gas/water flash calculations with an equation of state and Henry's law. The whole system of associated equations is solved simultaneously with the flow and energy equations using Newton's method, making the simulator one of the most robust and comprehensive simulators for EOR methods. The simulator is validated with ASP core flood experiments. The optimization of the ASP process for a typical field is illustrated and discussed with regard to alkali, synthetic surfactant and polymer injection with decreasing salinity.
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.
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 | 0.001 |
| 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 it