An Analytical Model To Predict Cumulative Steam/Oil Ratio (CSOR) in Thermal-Recovery SAGD Process
Language: Inglés Publication details: jul. 2012Description: 6 p. ; 269-275 In: Journal of Canadian Petroleum Technology 51Summary: Transcripción del resumen del autor. This paper presents a simple yet sophisticated analytical model to predict cumulative steam/oil ratio (CSOR) using material/energy balance and gravity-drainage theory in which CSOR is a function of average reservoir properties (porosity, permeability, heat capacity, and thermal conductivity) and time-dependent variables (injection temperature, rising chamber height, chamber oil saturation, and produced-fluid temperature) to mimic practical steam-assisted gravity-drainage (SAGD) processes. This model has been applied to predict CSORs of typical wells in the JACOS Hangingstone SAGD project. History-match results show the reliability and accuracy of the model at different geological conditions. The analytical model has proved to be satisfactory in predicting CSOR by reasonably adjusting a limited number of reservoir parameters, such as formation permeability, effective net pay, and operational parameters.| Current library | Status | Barcode | |
|---|---|---|---|
| Biblioteca Alejandro Angel Bulgheroni | Not for loan | 200059554 |
Transcripción del resumen del autor. This paper presents a simple yet sophisticated analytical model to predict cumulative steam/oil ratio (CSOR) using material/energy balance and gravity-drainage theory in which CSOR is a function of average reservoir properties (porosity, permeability, heat capacity, and thermal conductivity) and time-dependent variables (injection temperature, rising chamber height, chamber oil saturation, and produced-fluid temperature) to mimic practical steam-assisted gravity-drainage (SAGD) processes. This model has been applied to predict CSORs of typical wells in the JACOS Hangingstone SAGD project. History-match results show the reliability and accuracy of the model at different geological conditions. The analytical model has proved to be satisfactory in predicting CSOR by reasonably adjusting a limited number of reservoir parameters, such as formation permeability, effective net pay, and operational parameters.
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