Modeling Dependence Among Geologic Risks in Sequential Exploration Decisions
- J. Eric Bickel (Texas A&M University) | James E. Smith (Duke University) | Jennifer L. Meyer (CERA-SDG Oil and Gas)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- April 2008
- Document Type
- Journal Paper
- 352 - 361
- 2008. Society of Petroleum Engineers
- 4.1.5 Processing Equipment, 5.1.5 Geologic Modeling, 7.2.3 Decision-making Processes, 7.2.1 Risk, Uncertainty and Risk Assessment, 5.1.1 Exploration, Development, Structural Geology, 4.3.4 Scale, 4.1.2 Separation and Treating, 1.6.1 Drilling Operation Management, 1.6 Drilling Operations
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- 701 since 2007
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Prospects in a common basin are likely to share geologic features. For example, if hydrocarbons are found at one location, they may be more likely to be found at other nearby locations. When making drilling decisions, we should be able to exploit this dependence and use drilling results from one location to make more informed decisions about other nearby prospects. Moreover, we should consider these informational synergies when evaluating multiprospect exploration opportunities. In this paper, we describe an approach for modeling the dependence among prospects and determining an optimal drilling strategy that takes this information into account. We demonstrate this approach using an example involving five prospects. This example demonstrates the value of modeling dependence and the value of learning about individual geologic risk factors (e.g., from doing a postmortem at a failed well) when choosing a drilling strategy.
When considering a new prospect, it is important to consider its probability of success. In practice, this assessment is often decomposed into success probabilities for a number of underlying geologic factors. For example, one might consider the probabilities that the hydrocarbons were generated, whether the reservoir rocks have the appropriate porosity and permeability, and whether the identified structural trap has an appropriate seal [see, e.g., Magoon and Dow (1994)]. The overall probability of success is the product of these individual probabilities. Although these assessments may be difficult, for a single prospect, this risk analysis process is straightforward.
When considering multiple prospects in a common basin or multiple target zones in a single well, in addition to considering the probability of success for each prospect, we need to consider the dependence among prospects. For example, if hydrocarbons are found at one location, they may be much more likely to be found at another nearby location. Conversely, if hydrocarbons are not found at the first location, they may be less likely to be found at the other. When evaluating opportunities with multiple prospects, we should consider decision processes and workflows that exploit this dependence and use results from early wells to make more informed decisions about other locations. For example, if a postmortem analysis of core samples from a failed well reveals that there were no hydrocarbons present, then we may not want to continue drilling at nearby sites. On the other hand, if the postmortem analysis reveals that hydrocarbons were present, but the reservoir lacked a seal, then we may want to continue to explore other nearby sites. In this paper, we describe an approach for modeling dependence among prospects and developing a drilling strategy that exploits the information provided by early drilling results.
|File Size||1 MB||Number of Pages||10|
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