An Ontology Based for Drilling Report Classification

Guilherme, Ivan Rizzo; Serapião, Adriane Beatriz de Souza; Rabelo, Clarice; Mendes, José Ricardo Pelaquim

doi:10.1007/11925231_99

Cited by 4 publications

(2 citation statements)

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“…The system interprets the results from daily drilling reports, by successively evaluating by experts, shown in Figure 5. The process of extracting may be done either automatically or manually [7]. The bold arrows represent the way that has been used in this study.…”

Section: Revisementioning

confidence: 99%

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A Semi-Automatic Method for Case Acquisition in CBR - A Study in Oil Well Drilling

Shokouhi¹,

Aamodt²,

Skalle³

2010

Artificial Intelligence and Applications

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Oil well drilling operation is a complex process, in which there are always new lessons learned during drilling operation. Casebased reasoning (CBR) is an approach to problem solving that recalls previous experiences. Whenever the process is running smoothly, or is failing, the experiences gained during such episodes are valuable and should be stored for later re-use. This paper presents a methodology for automatic case building and case discrimination to obtain a robust case-based reasoning and learning system. To achieve this, a platform that integrates cases with general domain knowledge was used and employed in the oil well drilling domain. The implemented system showed the efficiency of the methodology for capturing and reusing previous experiences. KEY WORDSCase-based reasoning, oil well drilling, knowledge discovery

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Section: Revisementioning

confidence: 99%

“…The second motivation is to extract information from daily drilling reports. Guilherme et al [7] presented a methodology to organize and extract information from DDRs. It is required to know where and when the extraction is needed.…”

Section: Introductionmentioning

confidence: 99%