Field Treatment of an Injector Well in a Sandstone Formation Using a Low Corrosive Environmentally Friendly Fluid that Does Not Require Flow-Back
Bibliographic record
Abstract
Abstract Throughout a waterflood project, injector wells can experience scale build up mostly related to formation-water incompatibilities; as a consequence, injectivity index (II) decreases and vertical conformance can suffer leading to poor sweep efficiency. Stimulation treatments are required to reestablish well injectivity; usually Hydrochloric acid and Regular Mud Acid are used in sandstone reservoirs. Such treatments involve a number of difficulties such as handling highly corrosive fluids, risk of clay instability, secondary reactions and time-consuming flowback of spent treatment in low pressure reservoirs. Recently, a novel chemical was identified to effectively dissolve scale obstructions in injector wells while avoiding the operational constrains found in traditional acidizing jobs, including the need of flowback. Fluids containing the environmentally friendly chelating agent Glutamic acid N, N diacetic acid (GLDA), were tested in the laboratory under downhole conditions to evaluate the dissolution of a scale sample from the field composed by Fe2O3 and CaSO4. Additionally, core-flood, compatibility and corrosion tests were carried out to evaluate the interaction with clays, formation and well's metallurgy. Results showed effective dissolution of the scale sample, while being fully compatible with formation clays and fluids which indicated that the treatment could be left downhole and pushed into the formation without causing further formation damage. Furthermore, corrosion tests showed no need of corrosion inhibitor for a low carbon tubular under tested conditions. Field implementation took place in an on-shore injector well completed selectively with injection valves between packers. A two stage treatment was designed; the target of the first phase was cleaning out the injection valve itself and the tubing-casing annular space of this interval, and the second stage aimed the dissolution of scale located in the perforations and deeper into the formation. Step rate tests were performed before and after the treatment to evaluate well injectivity. Low injection treatment rates and soaking allowed enough time for the GLDA to effectively dissolve the scale obstruction along the treated interval; spent treatment was pushed further into formation once regular water injection was reestablished with a 51% increase in its injectivity index. The use of GLDA in the field was considered cost-effective due to the lack of additives, no need for of N2 to kick-off flow-back, nor flow-back fluids neutralization and disposal.
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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 | 0.001 |
| 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".