Successful Diversion of Acid Stimulation in Water Producing Oil Wells: Case Histories, Nisku Formation, Central Alberta
Bibliographic record
Abstract
Abstract Stimulation of carbonate oil and water producers with acid can result in an uneconomical increase in water production. This is the result of poor placement of the treatment stimulating the water-bearing rock preferentially to the oil. Typical treatments in the Nisku use selective tool isolation of zones to achieve the required placement control. The operational costs associated with this type of treatment make it difficult to perform economical stimulation treatments on marginal wells. Acid treatment of such a well, using only a diverting agent for control of placement, risks increased operational costs associated with possible increased water production and, therefore, the reduction of a marginal well to an uneconomical one. A unique diverting material formed by the reaction of an aqueous solution of dibasic acids and rosin esters, with divalent cations, present in formation water or spent acid allows the selective stimulation of only the oil-producing zones. The reaction product is an oil-soluble precipitant. The oil-soluble nature of the diverter base materials and the resultant precipitants makes the likelihood of the precipitant forming in the oil zones remote; however, in the event of such a result, the produced oil will remove the precipitant. Presented are laboratory tests describing the effectiveness of the oil-soluble material to divert acidic fluids away from water flows. Also, demonstrated is the subsequent cleanup of this oil-soluble diverting material using produced oil. In addition, several case histories from the Wayne area of Alberta, Canada are included. The results of these treatments demonstrate that control of acid placement in water-cut producers results in a considerable increase in oil production while minimizing the effect on water cuts. A significant reduction in the operational costs associated with switching from the selective tool isolation technique to the one described above is also demonstrated.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".