A Method To Estimate the Value of Well Log Information

Abstract

Abstract The cost of running logs to gather information about a well or reservoir can be a significant portion of an oil company's budget. Although the cost of well logs and surveys are often scrutinized, rarely do engineers or geologists analyze the value of this information. This paper describes how to compute the value of well logs before they are run by describing the uncertainty of what is already known, and predicting what will be lost as a result of a poor estimate. A probability distribution is drawn about the expected value ("best guess") of the parameter in question (e.g. OWC, porosity), and an opportunity loss is assigned to values that differ from this expected value. An "expected" loss is then computed based on the probability and conditional loss that may be incurred. This expected loss is equivalent to the value of perfect information. The author applies this technique to three examples to show how it is used, and draws general conclusions about the value of well log information. The paper shows that this relatively simple technique can be used to place a value on well logs to aid the decision making process. The examples show that in fields with little uncertainty, little heterogeneity, and/or low stakes, the value of information is often less than the cost of logs. On the other hand, in very productive fields, or areas where uncertainty is great, the value of information may be high.