Study of the Parameters of Steam Assisted Gravity Drainage (SAGD) Method for Enhanced Oil Recovery in a Heavy Oil Fractured Carbonate Reservoir
نویسندگان
چکیده
منابع مشابه
Neural Network Meta-Modeling of Steam Assisted Gravity Drainage Oil Recovery Processes
Production of highly viscous tar sand bitumen using Steam Assisted Gravity Drainage (SAGD) with a pair of horizontal wells has advantages over conventional steam flooding. This paper explores the use of Artificial Neural Networks (ANNs) as an alternative to the traditional SAGD simulation approach. Feed forward, multi-layered neural network meta-models are trained through the Back-...
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We present a lab-on-a-chip approach to informing thermal oil recovery processes. Bitumen - a major global resource - is an extremely viscous oil which is extracted by injecting steam underground in a process known as Steam Assisted Gravity Drainage (SAGD). Here, a microfluidic network saturated with bitumen provides a physical model of the SAGD reservoir; steam is injected into the chip, and th...
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Steam-assisted gravity drainage (SAGD) is a technique that has been developed to efficiently extract bitumen from deep reservoirs. We propose using electrical impedance tomography (EIT) for real-time monitoring of SAGD wells to maintain optimal operating conditions. Several electrode configurations along the pipelines and measurement strategies are presented and compared.
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The Biqian-10 block, located in Henan Oilfield of Sinopic, contains many thin and interbedded reservoirs, which have been operated by cyclic steam stimulation for 20 years or more. Therefore, it is a challenge to implement the conventional steam flooding. In order to improve the recovery of steam flooding, urea was used to assist steam flooding. Urea can decompose into CO2 and NH3, which are be...
متن کاملNeural Network Meta-Modeling of Steam Assisted Gravity Drainage Oil Recovery Processes
Production of highly viscous tar sand bitumen using Steam Assisted Gravity Drainage (SAGD) with a pair of horizontal wells has advantages over conventional steam flooding. This paper explores the use of Artificial Neural Networks (ANNs) as an alternative to the traditional SAGD simulation approach. Feed forward, multi-layered neural network meta-models are trained through the Back-Error-Propaga...
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ژورنال
عنوان ژورنال: American Journal of Engineering and Applied Sciences
سال: 2016
ISSN: 1941-7020
DOI: 10.3844/ajeassp.2016.647.658