Monitoring and Control of Smart Wells
Abstract/Contents
- Abstract
- Smart wells, wells equipped with smart completion, provide great potential to improve the recovery from hydrocarbon resources. Smart wells provide the ability to control uncertainties associated with reservoir heterogeneity. One example is to mitigate unexpected water production due to fractures and hence increase the ultimate recovery. This is achieved by selectively controlling production from multiple laterals. Due to subsurface communication between laterals that have different productivity indices, it is difficult in practice to optimize production from smart wells. The optimization of smart wells involves more than one parameter. These parameters include the settings of the downhole inflow control valves (ICV) that act as a subsurface chokes. This research focused on the reservoir engineering aspects of finding the optimum ICV configuration that optimizes reservoir performance parameters such as recovery factor and net present value. Also, the work studied the effect of heterogeneity, mainly fractures, on the optimization process. This research also proposed a technique to quantify the effect of fractures on the optimization process to provide recommendations of further analysis. Genetic algorithm (GA) was used as the main optimization engine to find the optimum ICV configuration. The GA was accompanied by a data library (proxy) to reduce the number of required simulation runs. The commercial reservoir simulator Eclipse was used as the objective function evaluator that assesses how good an ICV configuration is. Several examples are presented to show the improvement in reservoir parameters made using the optimization process. These examples include a synthetic model, and real onshore and offshore models. Various objective functions were optimized such as water cut minimization, and net present value maximization.
Description
| Type of resource | text |
|---|---|
| Date created | June 2009 |
Creators/Contributors
| Author | Al-Ghareeb, Zeid M. |
|---|---|
| Primary advisor | Horne, Roland N. |
| Degree granting institution | Stanford University, Department of Energy Resources Engineering |
Subjects
| Subject | School of Earth Energy & Environmental Sciences |
|---|---|
| Genre | Thesis |
Bibliographic information
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Preferred citation
- Preferred Citation
- Al-Ghareeb, Zeid M. (2009). Monitoring and Control of Smart Wells. Stanford Digital Repository. Available at: https://purl.stanford.edu/xc677zk9683
Collection
Master's Theses, Doerr School of Sustainability
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- brannerlibrary@stanford.edu
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