Without a good understanding of the faults and fractures present in a net pay zone, the possibility of wasting valuable resources is high. We characterize here fractures and faults within the Utica Shale by integrating routinely used methods such as geometric attributes (e.g. Dip, Similarity and Curvature) and comparing them with a new fault attribute that extracts faults and fractures, and improves their visibility. The new method also helps minimize random noise in the seismic data. In order to fully optimize faults and structures, we first filtered the seismic data with a structurally oriented filter to reduce the noise and improve the imaging quality. Using a single attribute to derive information from faults and fractures is not optimum, therefore we employed a second step, applying several conventional attributes such as similarity, curvature, and fault enhance filters. These successfully identified the fault and fracture geometries. A comparatively new fault attribute, known as Fault Likelihood and defined as a power of semblance, was then used to capture and delineate faults and fractures in the same Utica Shale area. This attribute is created by scanning a range of fault dips to identify maximum likelihood. The value range of the fault likelihood attribute is between 0 and 1. In order to obtain even sharper fault plane, a filtering step is also performed. When compared to traditional attributes, the faults and fractures are better defined by the new method. In addition, the new fault likelihood attribute is extremely versatile and can be used to characterize fault and fracture proximity and density.


In unconventional reservoirs, seismic characterization of naturally occurring faults and fractures is one of the main goals. This is critical in understanding the geological history as well as to identify sweet-spots for drilling. Manual fault picking is a typical exercise for most geoscientists, though it is a time consuming task and needs a well-trained interpreter. Therefore, a seismic fault enhancement or detection procedure is essential for improving and accelerating the overall fault and fracture interpretation process. Faults are typically classified as seismically resolvable features. However, some subtle faults and fractures, which often are of exploration significance, are not directly visible in seismic sections and time slices. Therefore, a combination of geometrical attributes (i.e. a multi-attribute set) is needed to achieve a satisfactory result (Brouwer and Huck, 2011). These attributes are good indicators of seismic discontinuity (Taner, 2001). Since early to mid 1990s, similarity/coherency and dip/azimuth attributes, have been used to detect faults and fractures. However, most of these typical attributes still lack capabilities to capture subtle faults and fractures, especially in complex geological scenarios. In this paper, we provide a comparison between a few conventional geometrical attributes and three new unconventional attributes. The new attributes are aimed to both enhance the seismic data for structural interpretation and to visualize and capture very subtle faults and fractures. Thus, these new unconventional attributes are of special significance for unconventional reservoirs. Utica Shale - a Late Ordovician Calcareous shale - is an ideal play demonstrating the importance of fault and fractures identification. A complete characterization of faults and fractures is crucial to optimally produce gas from the Utica Shale reservoir, which is one of the main unconventional shale plays in the US.

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