SLIM

A slim hole rig weighs about one fifth of a conventional rig and its small size can open new frontiers by making exploration economic in environmentally sensitive or inaccessible areas. 

The following table highlights the potential of slim hole wells ... 

The greatly reduced hole volume of slim hole wells can lead to problems if an influx is experienced (see section 3.7). The maximum depth drillable with slim hole configurations is another current limitation of this technology. 

However, coiled tubing drilling is limited to slim holes, and the reliability of some of the drill string components such as downhole motors needs further improvement. Presently, the cost of building a new customised CTD rig limits the wider application of this emerging technology. 

Morrison S R 1980 Electrochemistry at Semiconductor and Oxidized Metal Electrodes (New York Plenum) Dean M FI and Slimming U 1987 J. Electroanal. Chem. 228 135 Boehni FI 1987 Langmuir 3 924... 

Since we assume that all higher derivatives are essentially /.ero, dp/dq = con slim t. Therefore, it m ay be taken mi l of the in legral sign as follows ... 

Sta-Slim modified potato and tapioca starches Staley Mfg. 

In 1964, two competing series of slender volumes appeared one, the Macmillan Series in Materials Science , came from Northwestern Morris Fine wrote a fine account of Phase Transformations in Comlen.ted Systems, accompanied by Marvin Wayman s Introduction to the Crystallography of Martensite Transformations and by Elementary Dislocation Theory, written by Johannes and Julia Weertman. The second series, edited at MIT by John Wulff, was entitled The Structure and Properties of Materials , and included slim volumes on Structure, Thermodynamics of Structure, Mechanical Behaviour and Electronic Properties. 

SLIM Success Likelihood Index Methodology NUREG/CR-.35I8, 1984... 

Embry, D. E. et al., SLIM-MAUD an Approach to Assessing Human Error Probabihues Using Structured Expert Judgment, BNL, March 1984. 

The SLIM technique is described in detail in Embrey et al. (1984) and Kirwan (1990). The technique was originally developed with the support of the U.S. Nuclear Regulatory Commission but, as with TFIERP, it has subsequently been used in the chemical, transport, and other industries. The technique is intended to be applied to tasks at any level of detail. Thus, in terms of the HTA in Figure 5.6, errors could be quantified at the level of whole tasks, subtasks, task steps of even individual errors associated with task steps. This flexibility makes it particularly useful in the context of task analysis methods such as FITA. 

The basic premise of the SLIM technique is that the probability of error associated with a task, subtask, task step, or individual error is a function of the PIFs in the situation. As indicated in Chapter 3, an extremely large number of PIFs could potentially impact on the likelihood of error. Normally the PIFs that are considered in SLIM analyses are the direct influences on error such as levels of training, quality of procedures, distraction level, degree of feedback from the task, level of motivation, etc. However, in principle, there is no reason why higher level influences such as management policies should not also be incorporated in SLIM analyses. 

In the SLIM procedure, tasks are numerically rated on the PIFs which influence the probability of error, and these ratings are combined for each task to give an index called the success likelihood index (SLI). This index is then converted to a probability by means of a general relationship between the SLI... 

PROBLEM DEFINITION, QUALITATIVE ERROR PREDICTION AND REPRESENTATION. The recommended problem definition and qualitative error prediction approach for use with SLIM has been described in Section 5.3.1 and 5.3.2. The fact that PIFs are explicitly assessed as part of this approach to qualitative error prediction means that a large proportion of the data requirements for SLIM are already available prior to quantification. SLIM usually quantifies tasks at whatever level calibration data are available, that is, it does not need to perform quantification by combining together task element probabilities from a data base. SLIM can therefore be used for the global quantification of tasks. Task elements quantified by SLIM may also be combined together using event trees similar to those used in THERP. 

QUANTIFICATION PROCEDURE. In order to illustrate the SLIM quantification method, the case study developed in the earlier part of the chapter based on the chlorine tanker filling example will be used. The following operations from Figure 5.6 will be used to illustrate the method. 

Effects of Improvements in Procedures on Error Probabilities Calculated Using SLIM... 

The SLIM technique is a highly flexible method that allows considerable freedom in performing what-if analyses. In common with most human reliability quantification techniques, it requires defensible data, preferably from a plant environment, to be effective. In the absence of such data, the calibration values have to be generated by expert judgments made by experienced plant personnel. 

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