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Controllable drilling parameter optimization for roller cone and polycrystalline diamond bits
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Geosciences and Environmental Engineering.ORCID iD: 0000-0001-8577-1776
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Geosciences and Environmental Engineering.ORCID iD: 0000-0002-1629-2920
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.ORCID iD: 0000-0002-6790-2653
2019 (Swedish)In: Journal of Petroleum Exploration and Production Technology, ISSN 2190-0558, E-ISSN 2190-0566Article in journal (Refereed) Epub ahead of print
Abstract [en]

Oil well drilling data from 23 oil wells in northern Iraq are analyzed and optimized controllable drilling parameters are found. The most widely used Bourgoyne and Young (BY) penetration rate model have been chosen for roller cone bits, and parameters were extracted to adjust for other bit types. In this regard, the collected data from real drilling operation have initially been averaged in short clusters based on changes in both lithology and bottom hole assemblies. The averaging was performed to overcome the issues related to noisy data negative effect and the lithological homogeneity assumption. Second, the Dmitriy Belozerov modifications for polycrystalline diamond bits compacts have been utilized to correct the model to the bit weight. The drilling formulas were used to calculate other required parameters for the BYM. Third, threshold weight for each cluster was determined through the relationship between bit weight and depth instead of the usual Drill of Test. Fourth, coefficients of the BYM were calculated for each cluster using multilinear regression. Fifth, a new model was developed to find the optimum drill string rotation based on changes in torque and bit diameter with depth. The above-developed approach has been implemented successfully on 23 oil wells field data to find optimum penetration rate, weight on bit and string rotation.

Place, publisher, year, edition, pages
Germany: Springer, 2019.
Keywords [en]
Bourgoyne and Young model, Clustering, Drilling, Multiple linear regression, Optimization
National Category
Geotechnical Engineering Geophysics
Research subject
Exploration Geophysics; Soil Mechanics
Identifiers
URN: urn:nbn:se:ltu:diva-77274DOI: 10.1007/s13202-019-00823-1OAI: oai:DiVA.org:ltu-77274DiVA, id: diva2:1382047
Available from: 2020-01-01 Created: 2020-01-01 Last updated: 2020-01-07

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Darwesh, AliRasmussen, Thorkild MaackAl-Ansari, Nadhir
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