Auditable volumetrics for fast and effective evaluation of hydrocarbon resources Within the newest release 2018.2, GeoTeric is enhancing the exploration workflow by introducing a ‘Volumetrics’ tool which allows calculation of oil and gas resource estimates at any point during horizon interpretation ...
One way to incorporate information from FMI logs into GeoTeric is to classify fault by their trend (orientation along strike). This will allow the user to quickly correlate the orientation of open fractures/faults from FMI logs to the seismic volume, gaining a better understanding of the direction of these fractures/faults.
One of the most popular applications of GeoTeric’s Reveal module is the Fault Expression. Its example driven framework enables rapid optimisation and co-visualisation (CMY blending) of three independent edge attributes ensuring that faults of different sizes and seismic expressions are identified and detected with confidence.
A great value of the Fault Expression tool is that the effects of the different parameters can be immediately assessed: there is no need for extensive testing and comparisons, because after adjusting the filter footprints, the resulting changes are seen in the preview window. However, there is a set of parameters, which are hard wired and cannot be changed. These are the fault enhancement filters, mentioned in fine print in the Detect tab of Fault Expression. Switching between the different preview swatches, we see that the detected faults are different, even without changing the detection filter parameters. So, what do these numbers in the brackets mean?
In the previous post we covered the basics of using GeoTeric’s Fault Expression tool. The aim of that post was to take the user through all of the steps required to produce a reasonable first pass product. However there are also many variations and optimisation methods that can be used to give you different options based on the data you are working with.
GeoTeric’s Fault Expression is an intuitive and flexible tool that allows the user to produce fault attributes, blends and detect volumes in one simple workflow. By providing a range of different parameters, the results can be optimized for any size or style of fault. In this blog post, we will go through the process for successfully producing all of the products available in Fault Expression. Later posts will focus on optimizing for different types of faults.
By Randy Hee and Rachael Moore
Coherence cubes calculated from 3D seismic provide a representation of the similarity (or dissimilarity) of the seismic waveforms and are therefore indicators of discontinuities in the seismic volume. One of the most common coherency algorithm employed is the well-known semblance, multi-trace correlation calculation (Marfurt et al., 1998) which identifies discontinuities and reflector distortions within the data.
Colour blending is one of the most powerful visualisation tools currently available to geoscientists. Through this one simple process, the user is able to concurrently view the information from three different volumes, allowing them to interpret their data with more confidence. While there are other methods of interrogating multiple volumes, none offer the same level of data density at one time and although interpretation can be done by moving between multiple volumes, it is far more difficult to notice subtle variations.