Novel Carbonate Well Production Enhancement Application for Encapsulated Acid Technology: First-Use Case History
Bibliographic record
Abstract
Abstract Production from carbonate wells is often controlled by the degree of stratigraphic interconnectivity or lack thereof. Formation stratigraphy results in severely compartmentalized reservoirs. Effective methods for achieving hydraulic interconnectivity with such compartments are limited in horizontal openhole and long pay section in deviated wells. A new technology is emerging that incorporates solid acid capsules that function as both a fluid-diverting agent and a fracture conductivity enhancer. The degradable sized particulate system is incorporated into the acidizing fluid designed to enhance inflow from natural fracture swarms and to help enable propagation of hydraulic fractures that can breach or achieve wellbore communication with the stratigraphic compartments. This paper presents a case experimental project that involves a Canadian carbonate gas reservoir. Historically, horizontal wells drilled in low-permeability reservoirs with no natural fractures have shown poor production response. This successful production stimulation case demonstrates the potential to overcome the compartmentalization problem. In one of the first-use case wells reviewed in this paper, up to a 10-fold increase in reservoir pressure was observed in a shortterm buildup test, and the well was converted into an economic producer. Image logs were used to provide location and distribution of mineralized natural fracture swarms targeted for stimulation. Production data, laboratory data and post-treatment productivity index (PI) are presented. This paper adds to the industry's technical knowledge base by: (1) offering a practical, lower cost, high value solution to a significant emerging market; (2) documenting the first use of a new technology application; (3) presenting evidence of the technology's widespread global application to carbonate reservoirs and possibly sandstone reservoirs.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".