Combination of Dual String Single Trip Multi-Zone Completion Systems and High Rate Formation Pack as a Proven Completion Methodology for an Unconsolidated Reservoir: Case Study Tunu Field
Bibliographic record
Abstract
Abstract Failures due to sand production can manifest themselves in many ways; from surface equipment damage to downhole equipment failures which can ultimately result in loss of well integrity and worst case catastrophic failure. Several methods are available in the industry to control sand production problems, gravel packing being a widely used method. Gravel packing entails placing a sand or proppant filter in the annular space between an unconsolidated formation and a centralized slotted liner or wire-wrapped screen. Increased mechanical skin and achieving time and cost efficiencies are amongst the many challenges faced when implementing gravel packs as part of a completion operation. The Tunu field is a large gas field located in the Mahakam delta, East Kalimantan, Indonesia. Gas production started in 1990 and to date hundreds of wells have been drilled in the field. Until recently, the primary target was the Tunu Main formation which is a deep, well consolidated reservoir. To maintain production goals the operator has started to produce from the shallower unconsolidated zones. The first well targeting the Tunu Shallow reservoir was drilled in 2008. The Tunu Shallow formation has average porosity of 28% and permeability of approximately 1 Darcy. Shale content can be as high as 25%. Coal seams are also frequently found interbedded amongst the shales and reservoir sands. Within the interval of 500 to 2,000 m TVD the reservoir is generally found to be completely unconsolidated. In the Tunu Shallow development, more than 100 zones in 30 wells have been completed using a dual string single trip multi zone gravel pack completion system (STMZ) in combination with high rate formation packing (HRFP) as the sand control method. Using these combined techniques has given excellent results in terms of well productivity, rig non-productive time (NPT) and costs. Analysis performed on data garnered from pressure build-up tests (PBU’s) show mechanical skins ranging from 10 to 21 with an average of 14 obtained. The wells produce up to 24 MMscf/D sand free. This paper explains the implementation and optimization of the STMZ completion system with HRFP treatments as a completion technique in the shallow sands of the Tunu field.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".