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A Study to Investigate the Value of Information (VOI) Relating to Gas Well Testing and Data Acquisition

Fenwick, Melissa

Engineering Honours Degree, 2012

University of Adelaide


Petroleum operating companies spend large amounts of money on well testing and data acquisition every year. The purpose of spending this money is to reduce uncertainty when making future decisions leading to better project decisions and increased revenue. Well testing can be very expensive, it is possible that companies are overpaying for information that reduces their uncertainty. This paper discusses the cost of well testing and data acquisition compared to its value. It is important for companies to determine what the information would be worth to them prior to acquisition, to ensure that they are not overpaying for it.

Value of information can be divided into two sub-categories; quantitative (‘VOI’) and qualitative (‘voi’). Quantitative VOI usually refers to the direct monetary value of various alternatives. Qualitative voi is subjective and need not to be monetary; it is defined in terms of the value which is placed upon it by the decision maker, such as reserves estimations, safety ratings, reliability etc. Many of these scales may eventually evolve into or be indirectly related to monetary value, however, the scale that is used to measure them need not be.

In order to perform a quantitative value of information (VOI) analysis, specific details are required for the decision alternatives and all of the possible uncertain outcomes. It is not possible to perform a generic analysis and adapt it to various applications, rather, it is up to the decision maker to analyse the decision and perform an analysis using various inputs such as probabilities of outcomes and values of each alternative. This paper demonstrated how the decision tree methodology could be utilized to determine the best decision based on expected net present value and will also provide the decision maker with what the true value of information acquisition is. Once a decision tree has been solved and the decision maker has determined the value of acquiring new information (such as well testing), an informed and calculated decision can be made as to the best alternative to proceed. This paper presents the method of decision tree analysis, how a tree is constructed, solved and interpreted, then applies this method to a relevant example.

Conversely, qualitative value of information (voi) analyses, as presented in this study, only require the use of test data and subsequent beneficial remedial action to assess the value. This allows the value of multiple previous well tests to be assessed quickly and in a generic fashion as is the case for the analysis of the value of Santos’ recent well tests. One of the purposes of this paper is to display to Santos how decision-making strategies can be beneficial when faced with an investment decision, and to demonstrate how they can be used and implemented with respect to well testing and data acquisition.

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Australian School of Petroleum



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