Abstract
The research presents a case study of fracture characterization through the integration of well production data and a suite of interpreted seismic attributes from an offshore super-giant carbonate field in Kazakhstan. The goal of the study is to map the distribution and connectivity of the fracture network and subtle faults within the carbonate field's platform interior and rim areas to aid field development planning and to understand the existing well behavior and production performance.
The well data analyzed includes core descriptions (orientation and fracture types), image logs, and dynamic data (PTA, interference, and mud loss). Multiple 3D seismic attributes were calculated using two different seismic volumes, such as diffraction and least-squares – reverse time migration (LSRTM or LSR). Volume-based attributes (dip and azimuth, curvature, coherency, chaos, variance, structural smoothing, and ant-tracking) were calibrated against production data to create an optimal structural framework that describes the range of connectivity controls within the carbonate reservoir. Throughout the study, well recognized features, such as seismic scale natural fracture swarms were observed in both seismic volumes, and clearly identified using complex attributes. A qualitative correlation with the well data was also noted, where mud loss intervals are aligned with the position of the identified fracture networks.
This research has enhanced the understanding of how multiple seismic attributes can be used to characterize the fracture networks within the carbonate reservoir. Additionally, it could assist future well placement strategies, potentially reducing the number of connected development wells and resulting in significant cost savings for the project.
