Graph-based structural controllability and observability of steam assisted gravity drainage pressure chamber: A data driven approach

Abstract

Abstract Distributed parameter processes are challenging when it comes to modeling and control. Steam assisted gravity drainage (SAGD), used for in-situ extraction and recovery of oil sands bitumen, is a large scale distributed parameter process. The analysis of control relevant properties like controllability and observability enables to address the problem of control of steam chamber growth and sensor placement. We present a data driven and computationally affordable technique to assess the controllability and observability of the SAGD steam chamber dynamics in a structural perspective by exploiting the underlying interaction amongst different regions of the reservoir. A reservoir simulator is used to gather the data, and density-based clustering combined with Granger causality is used to develop a directed graph through which the structural controllability and observability of the SAGD process is characterized. This paper presents a detailed procedure and results for the sensor and actuator locations for partial and full controllability and observability to validate the discussed approach using the data acquired from the CMG-STARS simulator.