Simultaneous Well Stimulation and Scale Squeeze Treatments in Carbonate Reservoirs
Bibliographic record
Abstract
Abstract In many oilfields the relatively small number of high-cost, highly productive wells, coupled with a carbonate and or sulfate scaling tendency (upon waterflood breakthrough of injected seawater) requires effective scale management along with removal of near-wellbore damage in order to achieve high hydrocarbon recovery. The nature of the well completion strategy in new fields such as frac packs for sand control and acid stimulation for carbonate reservoirs has resulted in some wells with higher than expected skin values due to drilling fluid losses, residual frac gel, fluid loss agents, and fines mobilization within the frac packs where applied. This paper presents how the challenges of managing impaired completions and inorganic scale forced innovation in terms of when to apply both stimulation and scale inhibitor packages to carbonate reservoirs. The combined treatment has the potential to provide cost savings with a single mobilization for the combined treatment. The paper will describe the laboratory testing that was performed to qualify the treatments for two carbonate reservoirs (black oil and HT gas/condensate). In the test program assessment was made of oil, brine and gas permeability prior to and following application of the stimulation packages. The chemical packages assessed included classic HCl formulation and chelant stimulation chemicals on their own and with inclusion of scale inhibitor chemicals to provide simultaneous stimulation/squeeze treatments. These formation damage results and chemical return profiles were then compared to coreflood test results with scale inhibitor applied as a typical squeeze treatment. Results for these studies show that under matrix flow conditions inclusion of even highly compatible scale inhibitor resulted in formation damage due to chemical/rock/brine incompatibility during the stimulation process. Details of the solution to this problem are outlined within this document.
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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".