Subsurface-to-Economics Closing the Loop on Uncertainty Analysis

We are all aware that our future is uncertain. Although some aspects can be predicted with more certainty and others with less, essentially everything is uncertain. Uncertainty exists because of lack of data, lack of resources, and lack of understanding. We cannot measure everything, so there are always unknowns. Even measurements include measurement errors. Also, we do not always have enough resources to analyze the data obtained. In addition, we do not have a full understanding of how the world, or the universe, works (Park 2011). Every day we find ourselves in situations where we must make many decisions, big or small. We tend to make the decisions based on a prediction, despite knowing that it is uncertain. For instance, imagine how many decisions are made by people every day based on the probability of it raining tomorrow (i.e., based on the weather forecast). To have a good basis for making a decision, it is of critical importance to correctly model the uncertainty in the forecast. In the oil and gas industry, uncertainties are large and complex. Oil and gas fields have been developed and operated despite tremendous uncertainty in a variety of areas, including undiscovered media and unpredictable fluid in the subsurface, wells, unexpected facility and equipment costs, and economic, political, international, environmental, and many other risks. Another important aspect of uncertainty modeling is the feasibility of verifying the uncertainty model with the actual results. For example, in the weather forecast it was announced that the probability of raining the next day was 20%. And the next day it rained. Do we say the forecast was wrong? Can we say the forecast was right? In order to make sure the uncertainty model is correct; we should strictly verify all the assumptions and follow the mathematically, statistically, proven-to-be-correct methodology to model the uncertainty (Caers et al. 2010; Caers 2011). In this paper, we show an effective, rigorous method of modeling uncertainty in the expected performance of potential field development scenarios in the oil and gas field development planning given uncertainties in various domains from subsurface to economics. The application of this method is enabled by using technology as described in a later section.