A Review of Fractured Carbonate Reservoir Identification Techniques Based on Seismic Attributes

Abstract

Fractured carbonate reservoir is an important area of hydrocarbon exploration and development. Their reservoir spaces, formed through multiple phases of karst processes, having complex morphology and are highly interconnected. These make accurate identification and prediction particularly challenging. Seismic attribute analysis is a key method linking seismic reflection characteristics with subsurface geological features, and it can quantitatively extract response characteristics such as amplitude, frequency, and phase from large amounts of seismic data, and provides effective support for the identification of such reservoirs. This study systematically reviews the classification system of seismic attributes, proposes a three-class attribute classification based on geological target identification, and constructs a hierarchical progressive reservoir prediction technology chain. We also analyzes the limitations of applying single attributes using seismic attribute case studies. Furthermore, we summarizes the core concepts and practical achievements of multi-attribute fusion and anticipates the future directions of application trends and intelligent technologies in this field, which help to provide the systematic theoretical references and practical insights for the efficient identification and prediction of fractured carbonate reservoirs.