Field Treatment to Stimulate an Oil Well in an Offshore Sandstone Reservoir Using a Novel, Low Corrosive, Environmentally Friendly Fluid
Bibliographic record
Abstract
Abstract Acidizing in sandstone formations is a real challenge for the industry. Fines migration, sand production, and additional damages due to precipitation are some of the common concerns with sandstone treatments. Furthermore, the complexities of sandstone formations require a mixture of acids and loadings of many additives. The environmentally friendly chelating agent, glutamic acid N,N-diacetic acid, GLDA, was successfully used to stimulate deep gas wells in carbonate reservoirs. It was extensively tested in the lab to stimulate sandstone cores with various mineralogies. Significant permeability improvements were reported in our previous papers over a wide range of conditions. In this paper, we evaluate the results of the first field application with a fluid based on this chelating agent to acidize an offshore, sour oil well in a sandstone reservoir. The field treatment included pumping a preflush of xylene to remove oil residues and any possible asphaltene deposited in the wellbore area, followed by the main stage that contained 25 wt% GLDA, a corrosion inhibitor, and a water wetting surfactant. The treatment fluids were displaced into the formation by pumping diesel. Following the treatment, the treatment fluids were allowed to soak for 6 hours, then the well was put on production, and samples of flowback fluids were collected. The concentrations of key cations were determined using ICP, and the chelate concentration was measured utilizing a titration method using ferric chloride solutions. Corrosion tests conducted on low carbon steel tubulars indicated that this chelate has low corrosion rates under bottomhole conditions. No inhibitor intensifier was needed. The treatment was applied in the field without encountering any operational problems. A significant gain in oil production was achieved without adversely impacting the water cut, causing sand production, or fines migration. Analysis of flowback samples confirmed the ability of the chelating agent solution to dissolve various types of carbonates, oxides, and sulfides, while keeping the dissolved species in solution without causing unwanted precipitation. Unlike previous treatments conducted on this well, where 15 wt% HCl or 13.5/1.5 HCL/HF acids were used, the concentrations of iron and manganese in the flowback samples were negligible, confirming the very low corrosion rates of well tubulars when using GLDA solutions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".