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Record W2766458041 · doi:10.2118/186954-ms

Drilling Optimization to Overcome High Torque Problem: Lesson Learned on Kujung First Offshore-Near HPHT-Horizontal-Critical Sour-Slim Hole Development

2017· article· en· W2766458041 on OpenAlexaff
D.. Rizkiani, Kiki Yustendi, B.. Rusli, A. N. Mbouw, D. R. Mcken, Hero Santoso Effendi, S. Zulkarnain, Alfon Soufanny, Zhao Yang, Yuan Tian, Jie Lian, Anton Maladi, A. P. Diemert, M. Fadil, P. P. Utomo, S. D. Yudento, Arvandi Mahry

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsHusky Energy (Canada)
FundersChina National Offshore Oil Corporation
KeywordsTorquePetroleum engineeringDrillingDrilling fluidWorkoverDrillHigh pressureDrill pipeSour gasWell controlDragCompletion (oil and gas wells)GeologyMechanical engineeringEngineeringMechanicsNatural gasPhysicsWaste management

Abstract

fetched live from OpenAlex

Abstract BD Field is the first development project of Husky-CNOOC Madura Limited (HCML) in Madura Strait, Indonesia which has a pressure of 8,100 psi and a temperature of 300°F. This Kujung gas reservoir contains of 5.5% CO2 and 5,000 ppm H2S, indicating that the reservoir is near High Pressure High Temperature (HPHT) and critical sour environment. This paper describes the best practices, lessons learned and strategy to control drilling issues such as slim hole, horizontal, near High Pressure-High Temperature, high density, and sour/acid gas environment to achieve the well TD with torque and ECD limitation, without compromising production target. Kujung reservoir section was drilled with an overbalance mud system as per CNOOC HPHT and sour well requirement. Drill-In fluid (DIF) system treated with potassium formate and manganese tetraoxide as weighting agents was chosen for drilling the 5-7/8-in. reservoir section. Throughout the drilling operation, higher torque and ECD value was identified compared with Torque and Drag (T&D) Calculation and Hydraulics simulation. This can lead to shallower TD decision, which has consequence of possibility not achieving initial target depth/production. Calibrating T&D model using the pickup/rotate/slack-off value from actual measurements on both cased and open holes was done in order to match the model with actual condition. Several analysis and review of all possible causes was performed, including performance of solids control equipment, inadequate hole cleaning, dog leg severity, wellbore direction and/or formation lithology changes. T&D and hydraulics simulation was also performed to foresee the possible operation limitation with several lateral lengths to ensure having successful drilling operation without compromising both operational safety and future well production. Based on the original model, with friction factor values of 0.25 (cased hole) and 0.35 (open hole), 1000-1500 ft lateral length of 5-7/8-in. slim hole section can be achieved. However, with calibrated T&D model, friction factor values were almost double the original model. Comprehensive planning was done to accomplish the drilling objectives, such as re-plan well trajectory to reduce dog leg severity, selection of drill fluid lubricant additives to ensure its stability at pH > 11 environment as planned to control sour gas and compatibility with other products, maximize centrifuge usage to minimize excessive LGS build-up caused by successive and repetitive mud system re-use for batch drilling operations, and diluted system using rehabilitation mud. Reduced friction factors and decreased torque values were the key parameters to successful drilling through the updated planned horizontal length. In terms of gas well production, the objective of well productivity was achieved during unloading operation when gas production result from the wells yielded higher Absolute Open Flow (AOF) as compared to the planned target. Hence a successful BD wells had been delivered to production.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.017
GPT teacher head0.238
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

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".

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Citations2
Published2017
Admission routes1
Has abstractyes

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