A Probabilistic Approach to Quantify the Value of Information of 4D Seismic Projects

Abstract

AbstractA challenge that all managers face is to make decisions to maximize the project's return in the face of uncertainty. Acquisition of new information can assist decision makers in the reservoir management process. However, the acquisition of new information is not cost free and a routine business decision to be faced is whether acquiring new information is worthwhile. Consequently, the valuation of information becomes a significant part of a reservoir management process. The value of information (VOI) concept is commonly used to quantify the economic benefit resulted from the new information. The quantification of the VOI after the acquisition of information is simpler. In contrast, the VOI estimation before the acquisition of information is more complex because of the number of uncertainties and difficulties to model the problem; the term Expected Value of Information (EVOI) should be used in such context. The EVOI is based on average expectations; it is a weighted measure and does not show the variation of the expected benefits owing to reservoir uncertainties and consequently does not provide a complete picture of the problem. Thus, it is proposed a methodology that provides information about the possible range of outcomes increase and their probability. The methodology employs the chance of success (COS) concept, which provides more complete results. It applies the uncertainty analysis technique to generate multiple reservoir models, from which the fluid behavior establishes the period to acquire 4D seismic data. The representative models technique selects the models that represent the reservoir geological and economic variability. Finally, the impact of 4D seismic data on each representative model is quantified. The present study describes the methodology to estimate the COS, applies it to a synthetic model to validate the results and shows its benefits, as well as compares the EVOI and COS results obtained. The COS better supports the decision-making process due to its probabilistic approach. The decision maker can more meaningfully frame the range of potential increased returns and validate this against the organization's tolerance level. Such procedure makes the methodology an important tool for reservoir management.