Net Values of Our Information (includes associated papers 18563 and 18580 )
Authors: Lohrenz John 
Published: December 2007

Summary.
Petroleum engineers' basic product is information. We arecontinuously deciding what information to produce. This paper discusseshow to determine net values of information, recognizing that uncertaintiesare always present. Bias toward information that is "good news" ariseswhen uncertainties are not considered. Surprisingly, some information canhave higher net value when oil prices are lower.

Introduction
Petroleum engineers are producers primarily of information, andthey flourish according to the value of the information they produce. In a very real sense, the most important decisions petroleumengineers make are choices of which information to produce. Thesedecisions are unavoidable. The thought and consideration given inmaking these decisions ranges from none to turmoiled anguish. The number of decisions is unarguably huge.
A method to guide these decisions on the basis of net value ofinformation produced or purchased is presented here. A simpledecision tree rationalizes each decision. The information obtained canturn out to be either favorable(good news) or unfavorable (badnews). In either case, the information may turn out to be wrong. Recognition of this makes the method consistent with the real world.
Only information gathered to guide subsequent decisions is considered here. Information may often be produced or purchased forother purposes. For example, information may be gathered tocreate an image rather than to improve the chance of a bettersubsequent decision. A specific example is implicit in a complaintarticulated by a professional colleague that managers werespending money on "high tech," but were paying no attention to theresults and making the decisions on intuition. These intuitive decisions, when shown to be flawed, can always be rationalized bynoting that high tech supported them. The colleague noted that therewas nothing wrong, per se, with using intuition to make adecision: what is suspect is paying for high tech that will not be usedto make a decision. One cannot change the extant syntax: however, it would be preferable if the use of the term "information" implied only work undertaken to make a better decision. This is theonly use of the term implied here.
Here, a simple decision tree is used to quantify net information values with four petroleum engineering examples. For eachexample, the method guides the decision to obtain (or not to obtain)information. The maximum that can be paid for information is shown. When the possibility of wrong information is neglected, there willbe a bias toward purchasing favorable rather than unfavorable in-formation. This bias may correlate with actual performances thattend to be lower than projections.
Finally, the effect of oil price on net values of information is treated. A lower oil price can actually increase the value of information.

Information Value Decision Tree
The decision tree in Fig. 1 puts the decision to gather information pertinent to a subsequent decision into a rational framework. Information can be purchased (or gathered at cost) that, when known, can be characterized as good or bad news. Good news is synonymous with amore favorable view of doing what is proposed; bad news with a lessfavorable view. Any information, however, whether good or bad news, mayturn out to be wrong. The decision tree defines the requisite frequenciesand expected value outcomes used in Eq. 1 to define Cmax, the maximumamount that the information might be worth:
(1)
It would be reasonable to spend up to Cmax for information, butno more: if Cmax were negative, the information considered wouldhave no positive value.
The simple decision tree of Fig. 1 embodied in Eq. 1 capturesthe essence of the decision to obtain or not to obtain someinformation to make a better decision in petroleum engineering and otherdisciplines involved in oil/gas extraction. The decision tree can, in fact, be applied universally;however, the vagaries of oil/gasextraction projects make one more cognizant of the frequency of badnews, incorrect information, and their consequences. Understandably, venders of information do not emphasize the possibility that their product may be incorrect. It is not surprising that thepossibility and frequency of incorrect information have received scantattention in our literature. Ricks is an exception, and Ref. 2specifically treats seismic studies that may point to the wrong decision. Quite recently, Campbell et al. presented an example that considers errorsin seismic information. No doubt other treatments that consider thepossibility of wrong information exist but remain hidden.
The more common approach to the value of information is toassume that, given sufficient expenditure for information, "truth"is unimodally asymptotic. This is the usual approach in managementscience. Ref. 4 is an excellent example. That paradigm may befruitful sometimes, but not in petroleum engineering and other oil/gasextraction information decisions that characteristically differ. Characteristically, our information does not come close to truth, even with unlimited budgets. For example, no engineer can have informationabout a reservoir's rock and fluid properties that approaches truth. Thatis why the common approach to the value of information does not suffice inour work.
The decision tree used here can be applied in our businessprecisely because it recognizes good and bad news and informationthat may be correct or incorrect. To be sure, there may be gradationsbetween good and bad news, as well as information that is betweencompletely right and completely wrong, but the bifurcations of informationwith these qualities on an either/or basis robustly modelthe real world of our information.

Information Value: Four Examples
Suppose you have completed an economic evaluation that concludesthat a certain development well has a value to you of 20. You mayhave measured value as an appropriately discounted present valuein dollars, but that is just one definition. Here it suffices to imputearbitrary units to an economic value.
Suppose further that you have two subordinates who are equallyrespected. Both propose that more geophysical and geologicalstudies be completed before drilling. Their judgments regardingthe outcome of the studies differ, however.
JPT
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