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Record W2040418288 · doi:10.2118/113686-ms

Predesigned Bottomhole Pressure (BHP) in Aerated Drilling Matches in the Field and Improves Drilling Performance in Carbonate Reservoir

2008· article· en· W2040418288 on OpenAlexaff
Farid Shirkavand, G. Hareland, Mohammad Behbahani, Vahidreza Mostafavi

Bibliographic record

VenueAll Days · 2008
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsLost circulationDrillingRate of penetrationUnderbalanced drillingDrilling fluidPetroleum engineeringVolumetric flow rateAerationWell controlAnnulus (botany)Environmental scienceGeologyEngineeringMechanical engineeringMaterials scienceWaste managementMechanics

Abstract

fetched live from OpenAlex

Abstract A field case analysis of under balanced drilling (UBD) in the "A" structure located in Southern Iran has been carried out in the present paper. It was initially reported that 51% of an average well's cost was Non-Productive Time (NPT). Typical recordable NPT categories and key performance indicators used include tight hole, tool failure, hole cleaning issues, well control and lost circulation. It was decided that aerated drilling could be applied with advantages such as higher penetration rates, less lost circulation and overall lower drilling cost. As part of designing these wells the bottom hole pressure (BHP) was minimized. This paper shows that in the planned UBD, pre-simulated BHP is in good agreement with the operational BHP. The well drilling design of mud and air rates and the corresponding pressures are in this paper have been plotted against the field recorded pressures for different mud and air rates. The result of the pre-simulations also revealed that there is an unfavorable range of mud flow rate that provides a low BHP of the aerated mud for different mud rate and air injection rates. By illustrating the BHP (dynamic and static), annulus back pressure and different mud rates, it has been shown that an optimum combination, of mud and air rates must be determined in order to maximize the penetration rate. The design process of BHP includes checking for required cuttings carrying capacity, which is determined by ensuring that kinematics energy per unit volume is enough for all planned rates. The design method presented herein also suggests injecting air into mud during drilling of the lost circulation intervals as the best mud loss controlling method. The methodology and the calculation procedures used to pre-design the operation are presented herein with the field data against the pre-estimated. The results of this approach in the field have given reduction in NPT with some results presented herein. Introduction A well was drilled with an aerated drilling program to reach the "A" structure located immediately to the east of the central Iranian fault along with Dashtak and Kutah structures, in Fars North area. Close by, on the western side of the fault, other fractured gas and oil fields are located. During drilling of well "A-1", the larger challenge was controlling mud weight to avoiding lost circulation, tight hole and wellbore collapse (Figure 1). At the depth of 3850m, loss of circulation with rate of 90–170 bbl/hr was observed, which was controlled with LCM (Lost Circulation Material) after about 3.72 days. Drilling operation continued with 18–42 bbl/hr losses down to the depth of 3890 m and to 3928 m with 67.5 pcf mud and 8–21 bbl/hr losses. At 4242 m the mud weight was decreased to 65.5 pcf and well started to flow at 20 bbl/hr. At this point the mud weight was gradually increased to 67.5 pcf while continuous loss and salt water flow was occurring. It is believed that the well could only have been drilled with aerated drilling practices because of the specific challenges encountered.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.689

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.195
Teacher spread0.184 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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".

Quick stats

Citations0
Published2008
Admission routes1
Has abstractyes

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