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RokDoc Cross-Plotter
Using powerful RokDoc technology, the plugin enables cross-plotting of all well and seismic data types. Inclusive/exclusive polygons, rock physics models, best fit lines and a linked well viewer provide flexible tools to interpret the data. These include a histogram plotter with statistics and standard deviations/percentiles,and a matrix cross-plotter to analyse multiple data types simultaneously
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Cross-Plotting options
Users have complete flexibility to cross-plot data in MD, TVDss or TWT domains, while points may be coloured by type, working interval, value or density count. A variety of rock physics models may be overlain, and well data and seismic data can be displayed together.
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Polygons and Well Viewer Display
Users can draw inclusive and exclusive polygons on the cross-plot. The points defined by the polygon are highlighted in the well viewer which is dynamically linked to the cross-plot so particular points can be identifited on the input logs.
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Trend Lines
Users have option to apply a variety of best fit lines, including linear, polynomial, exponential and power law fits. Histograms may be displayed as stacked or unstacked blocks, and/or as lines, cumulative lines and Gaussian distribution curves.
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Matrix Cross-Plotter
The Matrix Cross-Plotter can generate multiple cross-plots in a single view, enabling users to rapidly target the attributes that define their target best. Rock physics models and templates can be applied across the full range of cross plots and interactively modified to fit the data.
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Histogram
Shown here is a histogram plot of three wells, displaying the Mean, +/- one standard deviation, min and max percentiles, with the frequency shown for the individual wells as stacked blocks. Lines, cumulative lines and Gaussian distribution curves are overlain. Users have total flexibility on data display, which can include both seismic and well data.
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Add a new dimension to your cross-plot analysis.
Using a third parameter in the cross-plot space can help separate previously unseen clusters or petro-elastic facies. Clustering in 3D space is easily recognisable, improving reliability and usefulness of interpretations.
Plug-in Attributes
Lifecycle
Appraisal | Concept
Challenges:
Unconventional Shale
ECCN:
UK origin, EAR99 de-minimis
Supporting Documents
Installation Guide
Release Notes
User Manual
Others