Case Study: Kazakhstan's First Application of Inflow Control Devices ICDs for Horizontal Wells
Bibliographic record
Abstract
Abstract This Paper describes the challenges and successful application of Inflow Control Devices ("ICDs") combined with sand control screens for horizontal wells. The ICDs were installed to reduce water and gas coning at the Shoba field. Shoba was the first field in Kazakhstan to use ICD technology and the first field in the Pre-Caspian basin where shallow horizontal wells were drilled. The Shoba field is located within the Zharkamys West 1 block in western Kazakhstan. The Triassic-age sandstone reservoir consists of sweet 34° API oil. The field was initially developed with seven (7) vertical wells. However, high vertical permeability, in combination with high gas and water mobility, resulted in excessive gas and water breakthrough that marginalized the field's economics. An alternate development plan utilizing ICDs and horizontal well technologies was necessary to enhance field commerciality. This project presented numerous challenges. Since the field is relatively small and wells of this type had not been drilled in the region, there was little opportunity for a "learning curve", no margin for excessive cost over-runs, or well failures. Some of the issues overcome that will be presented: ICD design and selection considerationsWellbore instability for shallow horizontal wellsIsolation of a sizable gas cap above the productive oil zonePlugging of the sand control screens during their placementPremature gas or water coning Shoba's first two horizontal wells were drilled and completed on time and under budget, with early results confirming a reduction of water and gas coning. A significant increase in production rates has also been realized. Given the project's initial success, additional horizontal well development drilling continues.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 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".