Field Treatment To Stimulate a Deep, Sour, Tight-Gas Well Using a New, Low-Corrosion and Environmentally Friendly Fluid
Bibliographic record
Abstract
Summary Matrix acidizing of high-temperature gas wells is a difficult task, especially if these wells are sour or if they are completed with high-chrome-content tubulars. These harsh conditions require high loadings of corrosion inhibitors and intensifiers in addition to hydrogen sulfide scavengers and iron control agents. Selection of these chemicals to meet the strict environmental regulations adds to the difficulty in dealing with such wells. Recently, a new environmentally friendly chelating agent, glutamic acid-diacetic acid (GLDA), has been developed and extensively tested for carbonate and sandstone formations. Significant permeability improvements have been shown in previous papers over a wide range of conditions. In this paper, we evaluate the results of the first field application of this chelating agent to acidize a sour, high-temperature, tight gas well completed with high-chrome-content tubulars. Extensive laboratory studies were conducted before the treatment, including corrosion tests, coreflood experiments, compatibility tests with reservoir fluids, and reaction-rate measurements using a rotating disk apparatus. The treatment started by pumping a preflush of mutual solvent and water-wetting surfactant, followed by the main stage consisting of 20 wt% GLDA with a low concentration of a proper corrosion inhibitor. Following the treatment, the well was put on production, and samples of flowback fluids were collected. The concentrations of various ions were determined using ICP. Various analytical techniques were used to determine the concentration of GLDA and other organic compounds in the flowback samples. The treatment was applied in the field without encountering any operational problems. A significant increase in gas production that exceeded operator expectations was achieved. Unlike previous treatments where hydrochloric acid (HCl) or other chelates were used, the concentrations of iron, chrome, nickel, and molybdenum in the flowback samples were negligible, confirming low corrosion of well tubulars. Improved productivity and longer-term performance results confirm the effectiveness of the new chelate as a versatile stimulation fluid.
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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".