The study is aimed to calculate an innovative numerical index for bit performance evaluation called
Bit Index (BI), applied on a new type of bit database named Formation Drillability Catalogue
(FDC). A dedicated research programme (developed by Eni E&P and the University of Bologna)
studied a drilling model for bit performance evaluation named BI, derived from data recorded while
drilling (bit records, master log, wireline log, etc.) and dull bit evaluation. This index is calculated
with data collected inside the FDC, a novel classification of Italian formations aimed to the
geotechnical and geomechanical characterization and subdivisions of the formations, called
Minimum Interval (MI). FDC was conceived and prepared at Eni E&P Div., and contains a large
number of significant drilling parameters. Five wells have been identified inside the FDC and have
been tested for bit performance evaluation. The values of BI are calculated for each bit run and are
compared with the values of the cost per metre. The case study analyzes bits of the same type,
diameters and run in the same formation. The BI methodology implemented on MI classification of
FDC can improve consistently the bit performances evaluation, and it helps to identify the best
performer bits. Moreover, FDC turned out to be functional to BI, since it discloses and organizes
formation details that are not easily detectable or usable from bit records or master logs, allowing
for targeted bit performance evaluations. At this stage of development, the BI methodology proved
to be economic and reliable. The quality of bit performance analysis obtained with BI seems also
more effective than the traditional “quick look” analysis, performed on bit records, or on the pure
cost per metre evaluation.
| Identifer | oai:union.ndltd.org:unibo.it/oai:amsdottorato.cib.unibo.it:858 |
| Date | 16 April 2008 |
| Creators | Magagni, Matteo <1975> |
| Contributors | Macini, Paolo |
| Publisher | Alma Mater Studiorum - Università di Bologna |
| Source Sets | Università di Bologna |
| Language | Italian |
| Detected Language | English |
| Type | Doctoral Thesis, PeerReviewed |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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