Micromodel method for enhanced oil recovery; fabrication and image processing

Mahmoodi, Maziyar (2017) Micromodel method for enhanced oil recovery; fabrication and image processing. Masters thesis, Memorial University of Newfoundland.

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Abstract

The number of research projects that employ microtechnology and microfluidic devices has expanded the application of this technique to more innovative fields of study over recent decades. Oil and gas production, a multidisciplinary industrial field, has benefited from the opportunities that microfluidic devices provide to study microscale processes, such as adhesion, interfacial tension (IFT) alteration and multiphase pore scale transportation. Obtaining a deeper understanding through the micromodel visualization experiments, the governing factors in large scale extraction from hydrocarbon reservoirs will be controlled efficiently. The diversity of proposed micromodel research and the associated requirements have led researchers to develop new methodologies, materials and techniques to overcome challenges attributed to micromodel visualization experiments. This project aims to suggest alternative solutions for two main problems, model fabrication and visual data interoperation, related to the process of exploiting the micromodels in Enhanced Oil Recovery (EOR) screening studies. First, this research tries to modify and combine the recent advances in wet etching micromodel fabrication method to offer a low-cost and efficient alternative procedure. This modified procedure offers increased flexibility in size and network pattern as well as a significant reduction in the material, time and operation costs. Next, the fabricated prototype is applied in a two-phase flow visualization study to verify the proposed features under the specified experimental conditions. Following the fabrication of a suitable glass micromodel, this thesis will explore processing/analysis of the visual data in a micromodel experiment. In this section, an image-based computational algorithm is developed and programmed in LabVIEW. This platform offers a graphical programming language and a vision toolbox that can be used for image processing purposes. The availability of advanced image-transform functions and the simplicity of working with LabVIEW, provide the unique opportunity to implement a sophisticated graphical-based algorithm that quantifies the visual observations during a glass micromodel test for enhanced oil recovery screening purposes. The performance of this custom algorithm is then verified by comparison of calculated data from carbonated water injection (CWI) images with absolute values derived from volumetric material balance. Through this procedure, the controlling parameters for utilized LabVIEW functions are optimized to obtain an acceptable agreement between estimated results and true values. At the final stage, the implementation of the presented algorithm in the LabVIEW and a popular commercial software are compared to highlight the advantages and disadvantages.

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