Uncertainty planning

However, there are hurdles to be overcome, and companies pursuing such growth will have to manage risks and uncertainties, plan their growth routes carefully, and build critical organizational skills. 

The range of uncertainty in the UR may be too large to commit to a particular development plan, and field appraisal may be required to reduce the uncertainty and allow a more suitable development plan to be formed. Unless the range of uncertainty is quantified using statistical techniques and representations, the need for appraisal cannot be determined. Statistical methods are used to express ranges of values of STOMP, GIIP, UR, and reserves. 

In determining an estimate of reserves for an accumulation, all of the above parameters will be used. When constructing an expectation curve for STOIIP, GIIP, or ultimate recovery, a range of values for each input parameter should be used, as discussed in Section 6.2. In determining an appraisal plan, it is necessary to determine which of the parameters contributes most to the uncertainty in STOIIP, GIIP, or UR. 

The prediction of the size and permeability of the aquifer is usually difficult, since there is typically little data collected in the water column exploration and appraisal wells are usually targeted at locating oil. Hence the prediction of aquifer response often remains a major uncertainty during reservoir development planning. In order to see the reaction of an aquifer, it is necessary to produce from the oil column, and measure the response in terms of reservoir pressure and fluid contact movement use is made of the material balance technique to determine the contribution to pressure support made by the aquifer. Typically 5% of the STOMP must be produced to measure the response this may take a number of years. 

The number of injectors required may be estimated in a similar manner, but it is unlikely that the exploration and appraisal activities will have included injectivity tests, of say water injection into the water column of the reservoir. In this case, an estimate must be made of the injection potential, based on an assessment of reservoir quality in the water column, which may be reduced by the effects of compaction and diagenesis. Development plans based on water injection or natural aquifer drive often suffer from lack of data from the water bearing part of the reservoir, since appraisal activity to establish the reservoir properties in the water column is frequently overlooked. In the absence of any data, a range of assumptions of injectivity should be generated, to yield a range of number of wells required. If this range introduces large uncertainties into the development plan, then appraisal effort to reduce this uncertainty may be justified. 

In dealing with future uncertainties. Royal Dutch/SheU pioneered Scenario planning (54,55). Alternative assumptions for future developments can be combined under this approach in various ways to give a number of consistent possible outcomes (56) and provide a basis for both actions and reactions. The approach has rewarded Shell handsomely. 

Table 5-1 gives values of electrical resistance for different coating materials. It is advisable to increase these by 100% at the planning stage because of the uncertainty in estimating the protection current density. 

Part of the planning should include the evaluation of test uncertainty. This evaluation can be limited to a common sense approach based on available instrumentation and the locations relative to the ideal. A more sophisticated study can be made in which instrumentation accuracy and the impact of any inaccuracy on the measured parameters is evaluated. This is a complex task with the need being based on the motivation for the test. If the test is being performed to settle a dispute, a formal understanding of the uncertainty should be developed. Methods for evaluation of test uncertainty are found in ANSI/ASME PTC 19.1 [11]. 

Assists in planning disposal systems for community waste. The model accepts appropriate inputs describing the community s situation and constraints, performs cost analyses for various scenarios to account for uncertainties in the input, and provides the system with heuristic indicators which describe the results. Interprets the results and provides advice on planning scenarios to be used as guidelines for making a study of appropriate alternative scenarios. 

Risk-based information provides a foundation for regulation of severe accidents. Early PRAs, with large uncertainties, indicated risk that was above or below the Safety Goals depending on containment performance. Consequently the NRC developed an Integration Plan for Closure of Severe Accident Issues (SECY-88-47) with six main elements to this plan 1) individual plant examinations (IPE), 2) containment performance improvements, 3) improved plant oper itions, 4) severe accident research, 5) external event considerations, and 6) accident management. 

The severe accident research program improved public risk assessment, reduced uncertainties, and the reliance on subjective expert opinion. To close two severe accident issues in NRC s Severe Accident Research Plan (NUREG-1365) Mark I Liner Attack and Direct Containment Heating (DCH) were addressed with a new approach using the Risk Oriented Accident Analysis Method (ROAAM) (Theofanous, 1994, 1989). The resolution of the Mark-I Liner Attack issue constitutes the first full demonstration of ROAAM. It emphasizes the determinism and provides a basis for synergistic collaboration among experts through a common communication frame. 

When setting the goals of a measurement project, it has to be asked, What exactly has to be determined. What are the final quantities required and what is the inaccuracy that can be tolerated in these quantities Only when these factors are known can an analysis be made, where the quantities to be measured and the measurement accuracy of each quantity are defined. This analysis is based on the mea surement method selected, and on the computation of measurement uncertainties. Usually the analysis of measurement uncertainties is made after monitoring however, making it beforehand is part of good planning practice. This approach ensures that the correct information with the desired accuracy is achieved. 

Even the best-laid plans are subject to last minute changes and unexpected variables, and there is an element of uncertainty in every estimate. Some of the more common sources of variance include factors beyond your control, such as ... 

There is little or no capability to evaluate risk. The robustness of the plan to key uncertainties is rarely assessed. Important risks in R D develop-... 

Managing risk—project managers planning research tasks need to identify the most important outstanding sources of uncertainty and work out which most need resolution at any given point in the R D process. 

This paper discusses the role that statistics can play In environmental sampling. The primary difference between an Investigation based on statistical considerations and one that Is not Is the degree of objectivity that can be Incorporated Into the evaluation of the quality and uncertainty of the study results. Statistical methods In the planning stage can also aid In optimizing allocation of resources. 

Moore (1998) suggested that the data available could be interpreted in terms of an ice crust 10-15 km thick. Christopher Chyba from the SETI Institute (Mountain View, California) has published articles in Nature (2000), the Proceedings of the National Academy of Sciences (2001a) and in Science (2001b) in which he suggests that a detailed study of this Jovian moon is necessary he discusses the possibility of a complex ecosystem, nourished by the radiation coming from outer space, on or in the ice layers of the moon. The planned Europa orbiter mission may provide certainty on this, but at least another five years of uncertainty lie ahead. The use of a submersible robot to study the (possible) ocean layer and its floor has been discussed. 

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