Chemical Sand Consolidation as a Failed Gravel Pack Sand-Control Remediation on Handil Field, Indonesia
Bibliographic record
Abstract
Abstract Handil field is a mature oilfield located in East Kalimantan Indonesia, operated by TOTAL E&P Indonesie (TEPI). By 2012, there were several wells completed with Gravel Pack completions that were producing sand during production phase. This condition created a hydrocarbon production limitation around 3700 bopd from three oil wells. TEPI were looking at technical solutions to improve well performance. Within the solution options that exist, chemical treatments - that consolidate the near wellbore area - can be a viable alternative for a number of completion types. Chemical sand consolidation can give a formation additional residual strength. This can enhance a maximum sand free rate (MSFR). One chemical treatment developed is environmentally acceptable by North Sea standards and simple to deploy by in a ‘one pass’ pumping operation. Looking at the completion type and complication during sand control remediation pumping, this chemical was finally chosen. The simpler deployment operation, since there is no overflush, induces less risk during pumping the treatment. The active chemical reacts with connate water in the near well bore area and forms a polymerized network around and between the sand grains. This network imparts additional residual strength allowing the near well bore formation to withstand greater drawdown and fluid flow. This paper discusses the experiences of TEPI with respect to using the organo-silane based chemical treatment in Handil field, Indonesia. A well intervention campaign treats a number of production zones which were treated separately by sliding sleeve door (SSD) selection. To ensure liquid cleanliness prior injection into formation, the use of coiled tubing was required and the treatment programs were adjusted from standard designs to accommodate this. Most of the operation performed resulted in an increase of the MSFR (leading to production increase). One job result however was not as per expectation. The lessons learnt from these treatments and improvements in candidate selection will be discussed here. This first coiled tubing application of the organo-silane based chemistry and the need to manage multiple small batches of the water sensitive treatment in a humid and wet environment were challenges to overcome.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".