Field Treatment To Stimulate an Oil Well in an Offshore Sandstone Reservoir Using a Novel, Low-Corrosive, Environmentally Friendly Fluid
Bibliographic record
Abstract
Summary Acidizing sandstone formations is a real challenge for the oil and gas industry. Fines migration, sand production, and additional damages caused by precipitation are some of the common concerns related to sandstone treatments. Furthermore, the complexities of sandstone formations require a mixture of acids and loadings of several additives. The environmentally friendly chelating agent glutamic acid N,N-diacetic acid (GLDA) was used successfully to stimulate deep gas wells in carbonate reservoirs. It was tested extensively in the laboratory to stimulate sandstone cores with various mineralogies. Significant permeability improvements were reported in previous papers over a wide range of conditions. In this paper, the result of the first field application is evaluated 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 region, 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. The treatment fluids were allowed to soak for 6 hours, then the well was put into production, and samples of flowback fluids were collected. The concentrations of key cations were determined using inductively coupled plasma, and the chelant concentration was measured using a titration method with ferric chloride solutions. Corrosion tests conducted on low-carbon-steel tubulars indicated that this chelant has low corrosion rates under bottomhole conditions. No corrosion-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 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 sulphides, while keeping the dissolved species in solution without causing unwanted precipitation. Unlike previous treatments conducted on this well, where 15 wt% hydrochloric acid (HCl) or 13.5 wt%/1.5 wt% HCl/hydrofluoric acid (HF) acids were used, the concentrations of iron and manganese in the flowback samples were negligible, confirming the low corrosion rates of well tubulars when using GLDA solutions.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".