Valutazione delle performance degli scalpelli da perforazione: studi teorici, analisi dati e valutazioni tecnico-economiche

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.

Cyclic alternating pattern in sleep and its relationship to creativity

Background/Objectives: Sleep has been shown to enhance creativity, but the reason for this enhancement is not entirely known. There are several different physiological states associated with sleep. In addition to rapid (REM) and non-rapid eye movement (NREM) sleep, NREM sleep can be broken down into Stages (1-4) that are characterized by the degree of EEG slow wave activity. In addition, during NREM sleep there are transient but cyclic alternating patterns (CAP) of EEG activity and these CAPs can also be divided into three subtypes (A1-A3) according to speed of the EEG waves. Differences in CAP ratios have been previously linked to cognitive performances. The purpose of this study was to learn the relationship CAP activity during sleep and creativity. Methods: The participants were 8 healthy young adults (4 women), who underwent 3 consecutive nights of polysomnographic recording and took the Abbreviated Torrance Test for Adults (ATTA) on the 2 and 3rd mornings after the recordings. Results: There were positive correlations between Stage 1 of NREM sleep and some measures of creativity such as fluency (R= .797; p=.029) and flexibility ( R=.43; p=.002), between Stage 4 of Non-REM sleep and originality (R= .779; p=.034) and a global measure of figural creativity (R= .758; p=.040). There was also a negative correlation between REM sleep and originality (R= -.827; p= .042) . During NREM sleep the CAP rate, which in young people is primarily the A1 subtype, also correlated with originality (R= .765; p =.038). Conclusions: NREM sleep is associated with low levels of cortical arousal and low cortical arousal may enhance the ability of people to access to the remote associations that are critical for creative innovations. In addition, A1 CAP activity reflects frontal activity and the frontal lobes are important for divergent thinking, also a critical aspect of creativity.