A Comprehensive Model of High-Rate Matrix Acid Stimulation for Long Horizontal Wells in Carbonate Reservoirs
Bibliographic record
Abstract
Abstract Matrix acidizing models have traditionally under-predicted acid stimulation benefits due to under-prediction of wormhole penetration and corresponding completion skin factors in vertical wells. For long horizontal wells drilled in carbonate reservoirs, productivity enhancement is a function of acid placement and effective wormhole penetration. However, prediction of wormhole penetration requires more effective analysis than provided by current industry models. This paper presents results of matrix acid modeling work for horizontal wells and describes a practical engineering tool for analyzing the progress of matrix acid stimulation for cemented and un-cemented horizontal well completions typically employed in carbonate reservoirs. An integrated flow model has been developed to predict the wellbore pressure profile and wormhole distribution by tracking the movement of the acid in the wellbore and the formation. Analysis of injection rates and pressures during acid treatment provides engineers with a way to determine the varying injectivity and tubing friction as stimulation proceeds. The model presented here can be used as a forward model for analyzing real-time treatment rate and pressure histories and can also be used to review past treatments to improve future treatment designs. The wormhole growth model is based on Buijse and Glasbergen’s empirical correlation augmented by the effect of formation heterogeneity and scale-up procedures that extend the wormhole geometry and penetration from laboratory flow tests on small cores to field-size treatments. Application of this modeling shows acid wormholing through carbonate formations can provide significant stimulation resulting in post-stimulation skins as low as −3.5 to −4.0 vs. previously predicted values in the −1.0 to −2.0 range. Using actual field stimulation data, we also discuss key elements to successful stimulation planning and the diagnosis of matrix acid treatments to achieve effective wormhole coverage for horizontal completions in carbonate formations.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".