Thesis Abstract

Abstract
The accurate characterization of subsurface fractures is crucial for various geophysical applications, including hydrocarbon exploration, geothermal energy development, and underground storage operations. This thesis focuses on the seismic characterization of subsurface fractures using advanced imaging techniques. The study aims to enhance the understanding of fracture networks within the subsurface through the integration of seismic data acquisition, processing, and interpretation methodologies. The research begins with an introduction that provides an overview of the motivation for the study, highlighting the importance of fracture characterization in geophysics. The background of the study delves into the existing literature on subsurface fractures and the challenges associated with their characterization using traditional seismic methods. The problem statement identifies the gaps in current approaches and emphasizes the need for advanced imaging techniques to improve fracture characterization accuracy. The objectives of the study are outlined to guide the research process towards achieving specific goals, such as developing innovative seismic imaging algorithms for fracture detection and characterization. The limitations of the study are also acknowledged to provide a clear understanding of the potential constraints that may impact the research outcomes. The scope of the study defines the boundaries within which the research will be conducted, focusing on specific geological settings and seismic survey parameters. The significance of the study is highlighted, emphasizing the potential impact of improved fracture characterization on various geophysical applications. The structure of the thesis is outlined to provide a roadmap for the reader, detailing the organization of chapters and the flow of information throughout the document. Definitions of key terms are provided to ensure clarity and understanding of the terminology used in the study. The literature review chapter critically examines existing research on subsurface fractures and advanced seismic imaging techniques. Ten key themes are identified, ranging from fracture detection methods to seismic attribute analysis approaches. The chapter synthesizes the findings from previous studies and highlights gaps in current knowledge that the present research aims to address. The research methodology chapter details the approach taken to collect, process, and analyze seismic data for fracture characterization. Eight key components are described, including seismic data acquisition, pre-processing steps, attribute analysis techniques, and fracture identification algorithms. The chapter outlines the workflow followed to achieve the research objectives and provides rationale for methodological choices. The discussion of findings chapter presents the results of the seismic characterization process, focusing on the detection and interpretation of subsurface fractures using advanced imaging techniques. The chapter explores the implications of the findings for geophysical applications and discusses the challenges and limitations encountered during the research process. In conclusion, this thesis provides a comprehensive investigation into the seismic characterization of subsurface fractures using advanced imaging techniques. The research contributes to the advancement of geophysical methods for fracture detection and interpretation, with implications for improved reservoir characterization, geothermal resource assessment, and underground storage operations. The summary highlights the key findings and implications of the study, emphasizing the significance of accurate fracture characterization in enhancing geological understanding and resource exploration efforts.

Thesis Overview

The project titled "Seismic characterization of subsurface fractures using advanced imaging techniques" aims to investigate and analyze the subsurface fractures through the utilization of advanced imaging technologies in the field of geophysics. Fractures in the subsurface play a crucial role in various geophysical processes, such as fluid flow, seismicity, and geomechanical behavior. Understanding the characteristics and distribution of these fractures is essential for various applications, including hydrocarbon exploration, geothermal energy production, and underground waste storage. The research will focus on utilizing advanced imaging techniques, such as seismic tomography, borehole imaging, and microseismic monitoring, to capture detailed images of subsurface fractures. These imaging technologies provide high-resolution data that can help in identifying the orientation, density, connectivity, and spatial distribution of fractures within the subsurface. By integrating data from multiple imaging techniques, the project aims to develop a comprehensive characterization of subsurface fractures in the study area. The research methodology will involve collecting seismic data through controlled source seismic surveys and passive seismic monitoring. Borehole imaging tools will be used to capture detailed images of fractures within boreholes, providing valuable insights into the subsurface structure. Additionally, microseismic monitoring will be employed to detect and locate small-scale seismic events associated with fracture activities. The findings of this research are expected to provide valuable insights into the subsurface fracture network and its implications for geophysical processes. By characterizing the fractures using advanced imaging techniques, the project aims to improve the understanding of subsurface dynamics and enhance the predictive capabilities for various geophysical applications. Overall, the project on "Seismic characterization of subsurface fractures using advanced imaging techniques" will contribute to the advancement of geophysical research by providing a detailed analysis of subsurface fractures and their impact on geophysical processes. The research outcomes will have implications for various industries, including oil and gas exploration, geothermal energy production, and environmental monitoring.