Optimum Injection Rate of A New Chelate That Can Be Used To Stimulate Carbonate Reservoirs
Bibliographic record
Abstract
Abstract Different chelating agents were used as alternatives for HCl in matrix acidizing to remove near wellbore damage and create wormholes in carbonate formations. Previous studies have demonstrated the use of ethylenediaminetetraacetic acid (EDTA), hydroxy ethylenediaminetetraacetic (HEDTA) and glutamic acid-N,N-diacetic acid (GLDA) as an alternative for HCl to stimulate carbonate reservoirs. The main problem with EDTA and HEDTA is the low biodegradability. GLDA was introduced as alternative for HCl for stimulating deep carbonate reservoirs at which HCl will cause corrosion and face dissolution problems. In this study calcite cores, 1.5 in. diameter with 6 and 20 in. length were used to determine the optimum conditions where the GLDA can breakthrough the core and form wormholes. GLDA solutions with pH values of 1.7, 3, and 3.8 were used. The optimum conditions of flow rate and pH were determined using the coreflood experiments. CT scan was used to determine the wormholes length and diameter to determine of optimum Damkӧhler number. GLDA was compared with chelates that are used in the oil industry such as EDTA and HEDTA. GLDA also was used to stimulate parallel cores with different permeability ratios (up to 6.25) to assess its ability on diversion. GLDA was found to be very effective in creating wormholes at pH = 1.7, 3, and 3.8 at different injection rates at temperatures of 180, 250, and 300°F. Increasing the temperature increased the reaction rate and less amount of GLDA was required to breakthrough the core and form wormholes. Unlike HCl and EDTA, there was no face dissolution or washout in the cores even at very low rates. Also, an optimum flow rate and Damkӧhler number were found at which the pore volume required to create wormholes was the minimal. GLDA at pH 1.7 and 3 created wormholes with a small number of pore volumes. Compared with acetic acid the volume of GLDA at pH 3 required to create wormholes was less than that required with acetic acid at the same conditions. GLDA was found to be effective in stimulating parallel cores with different permeabilities.
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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) | 0.000 | 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".