Fracture Detection On Surface Seismic Using Dip Steering Cube
Tyiasning, Stephanie Wikan
Geoscience Honours Degree, 2011
University of Adelaide
At Scotia Field of the Bowen Basin on eastern Queensland (Australia), natural fracture system has been identified as one of the important parameters in the success of gas production in Coal Seam Methane (CSM) reservoir, along with cleat system in coal and in situ stress condition. Fractured coal seams were analysed with dip-steering method to investigate its ability in detecting small-scale faulting and natural fractures in surface seismic data. This method was suggested to be powerful in enhancing multi-trace attributes, which would result in recognising subtle structural features on seismic data. Seismic attributes such as Curvature and Similarity have been widely used in enhancing complex three-dimensional structural and stratigraphic interpretation, particularly in identifying and analysing complex deformations that are unresolved in conventional amplitude volume. These attributes were calculated from dip-steered volumes, and the dip-steered Similarity results were compared with standard Coherency Cubes in terms of fault and fracture detection capabilities. The results revealed that cross-hatched features that may indicate fracture systems were clearly revealed on most positive curvature attribute. There are weak correlations between fabric and major conjugate shear fracture systems in the area. Fabric orientations were also inconsistent with the fracture orientations in the image log data and believed to be the result of curvature attribute calculation itself. On the other hand, Coherence Cube turned out to be more effective compared with the dip-steered similarity volume not only in fault interpretation but also in recognising depositional features on low relief horizon slices. On the contrary, dip-steered similarity seemed to allow better fault interpretation on high relief horizons. The crosshatched fabrics identified on the most positive curvature attribute were not observed on either the similarity volume or the coherence cube, which supports the earlier suggestion that these fabrics are an artifact of the curvature attribute calculation process. On the whole, the most positive curvature attribute can be used in identifying faults and fractured areas. However, prediction of fracture orientation was proven to be less reliable.