Horizontal Water Disposal Well Performance in a High Porosity andPermeability Reservoir
Bibliographic record
Abstract
Nexen Petroleum International Ltd. (Nexen) has a 52 percent interest and is operator of the Masila Block in the Republic of Yemen. Oil and water are produced mainly from the under pressured Qishn Formation, a non-marine to marine clastic sequence of Lower Cretaceous Age, which is roughly 200 feet thick and lies at a depth of 5500 feet from surface. Currently oil production is 230,000 BOPD at a water cut of about 80 percent. The one million barrels of water produced each day are currently reinjected under matrix injection pressures into 24 vertical and 4 horizontal wells. These are completed in the best quality sands (the S2/S3 members of the Upper Qishn Formation) that have average porosity and permeability of 20% and 3700 md, respectively.Despite the exceptional disposal reservoir quality, injection problems continue to exist that have caused Nexen to study and evaluate numerous methods of improving injectivity. After extensive laboratory core and field testing, hypotheses have been developed to explain the behaviour of the water disposal wells including the so-called ‘check-valve effect’. Horizontal wells and proppant fractured wells were employed to test the hypotheses and to improve injectivity.This paper reviews the laboratory results and discusses the placement of horizontal injectors along with the drilling and completion details of the wells. The performance of the horizontal disposal wells under matrix injection is compared to conventional vertical disposal wells and proppant fractured vertical wells. Produced water is expected to reach 1.5 MMBWPD and improvements in disposal well performance will reduce the number of wells that will need to be drilled to handle this volume, thereby improving overall project value.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".