A robust kriking model for predicting accumulative outflow from a mature reservoir considering a new horizontal well
Publication details: 2012Description: 6 p. ; 113-119 In: Journal of Petroleum Science & Engineering 82-8360Summary: Transcripción del resumen del autor: The objective of this research is to build a response surface based on Kriging method to predict accumulativeoutflow from amaturereservoir as a function of location, direction and length of anewhorizontalwell over a planning horizon. Investigating the impacts of horizontalwell parameters on the outflow using repetitive runs of reservoir flow simulation would involve enormous computation time for evaluating possible well placement scenarios. Instead, we construct a Kriging model to build a good approximation of accumulated outflow from areservoir when anewhorizontalwell is to be drilled. Kriging method is a geostatistical approach in which the spatial correlation of samples can be estimated via a variogram or a covariance matrix. The objective of this research is to find a more accurate estimate of the covariance matrix used in the construction of Kriging model. The method includes an optimization model to smoothen the noisy experimental covariance matrix which in turn leads to enhancing the fitting process. We have observed a very good fit of the resulting Kriging model in a case study on amature oil reservoir in Iran for which a dynamic simulation model was set up previously. However, it is necessary to add the nugget effect to the model in order to yield better predictions.| Current library | Status | Barcode | |
|---|---|---|---|
| Biblioteca Alejandro Angel Bulgheroni | Not for loan | 200059198 |
Transcripción del resumen del autor: The objective of this research is to build a response surface based on Kriging method to predict accumulativeoutflow from amaturereservoir as a function of location, direction and length of anewhorizontalwell over a planning horizon. Investigating the impacts of horizontalwell parameters on the outflow using repetitive runs of reservoir flow simulation would involve enormous computation time for evaluating possible well placement scenarios. Instead, we construct a Kriging model to build a good approximation of accumulated outflow from areservoir when anewhorizontalwell is to be drilled. Kriging method is a geostatistical approach in which the spatial correlation of samples can be estimated via a variogram or a covariance matrix. The objective of this research is to find a more accurate estimate of the covariance matrix used in the construction of Kriging model. The method includes an optimization model to smoothen the noisy experimental covariance matrix which in turn leads to enhancing the fitting process. We have observed a very good fit of the resulting Kriging model in a case study on amature oil reservoir in Iran for which a dynamic simulation model was set up previously. However, it is necessary to add the nugget effect to the model in order to yield better predictions.



