Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractThis paper analyzes forward-looking rules for Swiss monetary policy in a small structural VAR model consisting of four variables taking into account data revisions for GDP. First, the paper develops an analytical method to analyze the effect of data revision errors in GDP on the ex ante or conditional inflation-output-growth volatility trade-off and applies it to Swiss data. Second, the effects of different targets in a forward-looking monetary policy on ex post or unconditional volatility of inflation and output growth is explored by a simulation exercise. In general, the results obtained suggest that focusing monetary policy on GDP growth instead on inflation may lead to an inefficient policy with both increased medium term inflation and GDP growth volatility in the presence of GDP data revisions.
The anticipation and remediation of operational problems while drilling an oilwell is the main goal of real time measurements of drilling parameters, such as bottomhole pressure, flow rate, pump pressure, torque, drag, among others. The petroleum industry has spent a great amount of financial resources to ensure the quality and availability of these data, but the knowledge for a correct analysis and interpretation of them is still far from being spread among the rigsite teams and drilling engineers. Nowadays, the interpretation of real time drilling data to identify possible operational problems is done by a drilling analysis specialist. However, this can be a very subjective job since it depends on the specialist experience. These analists also take their decisions based on intuition and qualitative rather than quantitative criteria. Petrobras has developed a computational tool (called PWDa) to interpret real time drilling data, predicting and analyzing drilling operational parameters (such as pump pressure, bottomhole pressure, torque and drag). The software detects abnormal behaviors (such as an unexpected increasing trend on bottomhole pressure) and establishes quantitative criteria in order to identify a possible cause, suggesting corrective and/or preventive actions. The main goal of the software is the establishment of an automated methodology to interpret operational parameters in real time helping the drilling engineers to take right and fast decisions. The software is being currently implemented at Petrobras Real Time Operations (RTO) rooms and is providing good results. Over 70 wells have already been monitored with PWDa and several operational problems (such as washout, mud losses, bit wear, downhole motor fail, deficient hole cleaning, pore pressure increments, etc) were successfully identified, allowing the operators to take fast decisions and avoiding riskier situations. The wells monitored include deep water exploratory wells (mostly), directional development wells and extended reach wells. This work aims to highlight the benefits generated by the implementation of the technology. The interaction with the drilling team, including operator and service company members will be discussed. Introduction The analyzis of PWD (Pressure While Drilling) data and other operational parameters (such as rate of penetration, standpipe pressure, flow rate, torque, drag, etc) is an important tool to identify and prevent several operational problems (Aragao et al). The real time interpretation of these data may be very useful to reduce non productive time, risks and operational costs. According to Teixeira et al, most of events and problems have direct or indirect impact on bottomhole pressure and standpipe pressure. Some of them may also affect torque and drag. Problems like poor hole cleaning, annular obstructions, wellbore collapse, kicks, washouts and mud losses will affect the amount of solids in the annular space and/or friction losses and, therefor, will directly affect standpipe and bottomhole pressure (Aragao, et al, 2005). Thus, the analysis of pressure data is a key element to identify and prevent operational problems. Additionaly, when other parameters are simultaneously analyzed (modlogging measurements, for instance), the interpretation becomes much richer.
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