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A comprehensive suite of
conventional statistical tools to help you make sense of large amounts
of data very quickly
A fundamental requirement for detailed statistical
interpretation of log and core data is to be able to perform
comprehensive Exploratory Data Analysis. Techstat provides a wide
range of visual and calculation tools to understand user's data.
Factorial Analysis
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Principal Component Analysis (PCA) is a useful tool to
summarise data, since it separates the dominating features in the
data set |
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Linear Discriminant Analysis (LDA) is used to determine
the best projection space to discriminate between two or more
naturally occurring groups.
It clarifies subsequent Cluster Analyses on your data. |
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Multiple Correspondence Analysis compares qualitative
variables that may either be of similar type (observed vs
predicted curves) or be of dissimilar type (geology vs
petrophysics). |
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Regressions
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Regression Plots using interactivity with an
associated layout
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Linear, non-linear, polynomial and multiple lines
algorithms are available. |
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Regression and other fit lines and functions may be
created and conditioned on filters, zonation, well-by-well or
multi-well. |
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Fit lines may be calculated for user-defined subsets of
data using the data selection tools and interactivity between
viewers. |
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Classification and normalization
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Hierarchical Clustering: Dendrogram. Find similarities
between wells; group wells together; if necessary, align data
responses using sophisticated Gaussian analysis, group-by-group
amongst wells. |
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Decision tree
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powerful classifiers where inputs are mixed and
incomplete variables (qualitative and quantitative ). |
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rank inputs by their information gain. |
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deduced rules can help to understand the input data
regarding the output. |
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Classic and optimized normalization
algorithms.Classification and normalization |
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Box-Plot + Multi-well Matrix
Histo/Cross-Plot
+ Dendrogram Plot
Signal Processing
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Comprehensive suite of tools available for
single and multi-well applications.
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Interpolation: linear, Fast Fourier Transform,
Gaussian,... |
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Undersampled transformation of ordinal data. |
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Spline functions & smoothing functions. |
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Despiking. |
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Outliers detection. |
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Instant graphical confirmation of results. |
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