Low Tension Gas Process in High Salinity and Low Permeability Reservoirs
Bibliographic record
Abstract
Abstract Chemical enhanced oil recovery (EOR) in carbonate reservoirs has always been technically and economically challenging. Conventional Alkaline-Surfactant-Polymer (ASP) flooding has limited application in low permeability (2-20 mD) and high salinity formations (~200,000 ppm TDS) with a large concentration of divalent cations. Also injectivity into such low permeability reservoirs can be a significant problem with polymer solutions. The process of low tension gas (LTG) in tight carbonates has exhibited good microscopic displacement and mobility control. It combines interfacial tension (IFT) reduction with improved mobility control by in-situ generation of foam in low-permeable heterogeneous formations. This process has been tested in the lab for a Middle Eastern carbonate reservoir, which is the subject of this paper. This strategy has been tested through either co-injection or alternating injection of slug/drive surfactant solution and gas (CO2, N2, or hydrocarbon) at low foam quality (high water content). A successful surfactant screening was performed to select the optimum surfactant formula that exhibits ultra-low IFT, good aqueous stability, and low microemulsion viscosity. The formulation allows tailoring of optimal salinity for ultra-low oil-water IFT to the variation of formation and produced water salinity. Core flood experiments have been performed, which demonstrated favorable mobilization and displacement of residual oil. Tertiary recoveries of up to 85% on remaining oil were achieved for cores with permeability less than 10 mD. An innovative experimental method was also developed to achieve high initial oil saturation in tight rocks.
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".