PMDI
Base Module
PMDI
Information Advancement Tool
PMDI
Seismic Inversion Tool
PMDI
Section Classification Tool
PMDI
Quantitative Prognosis Tool |
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PMDI Base Module
This module provides
various processing manipulations over seismic and non-seismic
profile data, combined with log data, if available.
It enables numerous kinds of data visualization,
including making hard copies, export and import,
including exchange with
Areal
Data Integrator modules, horizon correlation,
fault tracing, geological interpretation, profile
data cross-correlation, time and spectral analysis
and a number of auxiliary operations. Base module
also works as a server for other
modules.
Visualization
PMDI
Base Module provides color and black-and-white
profile seismic and non- seismic data
visualization combined with log data, picked
events, faults, and geological objects
or features. There are
special options for tuning color palette to data
values, visual tracing and editing of events and
faults, visual correlation of seismic traces and
log data. Options for combined visualization of
different data are available as well. Various log
data are presented both in depth and time scales,
with reflectivity or contrast coefficient
calculated and visualized for each type of log
data. These data can be visually edited and
re-scaled to match seismic data.
PMDI Base
Module enables making a hard copy of a data
picture for various kinds of plotters and
printers. It supports HP/GL, HP-GL/2, PCL 5, HP RTL, PostScript, Windows bitmap (DIB), CGM, XWD,
ESC/P-2 graphical languages and formats. The
module also provides combination of different
pictures, making standard stamps and color
editing.
Data Export and
Import
PMDI Base Module provides
import of seismic data in SEGY format and log
data in LAS format. Data obtained can also be
exported in SEGY format. Data exchange with
Areal
Data Integrator modules is supported along
with data exchange with GIS systems. Non-seismic
(not SEGY) data can also be imported in the data
base through special converters registered by the
user.
Horizon Correlation and Fault
Tracing
PMDI Вase Module supports
a wide range of possibilities to pick up and
correlate horizons and events both by seismic data
and as a result of
the integrated interpretations. Events
can be picked manually, semi-automatically with
phase correction, and automatically. Six kinds of
correction for different phases are available.
Three kinds of automatic event correlation are
available, with one of them applied for
correlation based on the integrated interpretation
results. Picked events can be edited locally or
globally and can be used for cross-correlation and isochrones and depth maps making.
Faults can be
traced on seismic data and on the integrated
interpreted results, with the last method being
more powerful. Faults can also be edited with new
result emerging.
Geological
Interpretation
Geological bodies
or features can be constructed base on picked events
and traced faults. These bodies can be visualized
together with all types of data, with the bodies
being dynamically reconstructed while editing events
and faults. A tool for paleo-reconstruction of previously picked events is available. All the
objects concerned, such as profile data, log data,
events, faults, geological bodies and features, etc. are
reconstructed
simultaneously.
Profile Data
Cross-Correlation
Events and
faults made on different profiles can be cross-correlated with a
special tool. Correlation can be made manually by moving data at
the cross-points or automatically by interpolating the data,
involving well data as well. Applying these tools can be made
isochrones and depth maps along with maps of seismic and
non-seismic attributes at the event sites or in layers. These maps can be
used in the
Areal
Data Integrator modules.
Time
and Spectral Analysis
PMDI Base
Module possesses a wide range of tools to analyze seismic trace spectra. Different kinds of spectra both for trace
and section can be calculated and visualized. Also module supports
original technology for seismic sequence stratigraphy and cycles revealing
through visual analysis of time and spectral
columns.
Auxiliary
Programs
Auxiliary programs of PMDI
Base Module provides data partitioning and combining of different
types of data and also interpolation of data for a more precise
griding.
Also the programs enable to calculate a number of
math operations with profile
data.
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This tool allows calculating a variety of
profile data transformations over seismic and non-seismic data to
improve their quality or to extract new attributes from these data. Also this tool provides
a conversion of gravity and magnetic profile
curves into seismic profile sections for further
integrated and combined analysis.
Seismic Data
Improvement
This program set
comprises widespread seismic post-stack
processing programs. A number of filtering
programs are among
them: |
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Program for
zero-phase band-pass or rejecter time
filtering; |
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Program for time
filtering with arbitrary
wavelet; |
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Program for trace
mixing (lateral
filtering); |
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Program for coherent
filtering (both time and lateral) to correlate
broken
events; |
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Program for
correction of higher frequency time attenuation
and frequency equalizing; |
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Deconvolution
programs such as minimum-phase and zero-phase deconvolution with 2 types of homomorphic
deconvolution (filtering and lateral averaging
methods) are also included. |
Gain
Analysis and
Control |
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There are 4
possibilities to realize gain control: hard,
soft, time dynamic, and both
time and lateral dynamic
gain
control. |
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There are also
programs to analyze and eliminate amplitude linear
trend and mean value linear trend that is
especially important for further seismic
inversion. |
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Also a special
service programs for data centering, normalizing
and outstanding values elimination is available, as
well. |
Seismic Attributes
Extract |
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Special program
allows computing instant amplitudes, phases, and
frequencies of the seismic data by Hilbert
transform. |
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Another program can
calculate a variety of seismic integral dynamic
parameters for previously correlated events and
layers. These are 32 parameters and are divided into 3 groups: amplitude parameters,
frequency parameters and attenuation parameters.
Maps of these parameters can be effectively used
in Areal
Data Integrator
modules. |
Gravity and Magnetic
Transformations |
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These programs
convert surface gravity and magnetic profile
curves into profile sections of the fields
using
the method of harmonic continuation. Not only
fields themselves but their integrals and
derivatives up to 3rd order can be calculated with
respect to arbitrary
directions. |
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A program to
calculate gravity and magnetic normalized gradient
from surface curves, is also available. These
gradients demonstrate special points of the
fields that are the approximate distribution of
the density and
magnetization. |
Auxiliary
Programs |
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Tool possesses a service program to re-scale profile
data to fit different events on different data
or to reconstruct the data considering
some events to be paleo-surfaces. This program is
useful for fitting seismic and non-seismic data
and for paleo-reconstructions. |
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Another auxiliary
service program can convert data from time to
depth scale or vice versa, using velocity data or
certain correlated events both from time and depth
sections. |
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Some extra math
operations are also realized in a special
program. |
This tool
realizes a variety of seismic inversion
algorithms, with inversion being possible not only
for conventional reflectivity calculated on
impedance but for contrast coefficients calculated
on all the types of log data. Tool comprises
simple seismic inversion algorithms, so called
pseudo-acoustic analysis, subtle algorithms using stratigraphic deconvolution and post-processing
correction
programs.
Pseudo-Acoustic
Analysis
Functions and programs of
pseudo-acoustic analysis materialize simple, crude and
robust method of seismic inversion, when wavelets
are considered to be one of fixed set of shapes,
namely, harmonic pulse, Rikker pulse and Puzyrev
pulse. Wavelet amplitude and frequency parameters
are estimated based on seismic trace
spectrum. The correlation coefficients between
synthetic and observed seismic traces are
calculated and visualized to tie seismic and log
data. Sections of log parameters based on these
results for one or more wells can be evaluated in a
cross-well space. Various kinds of correction and
tuning are available, so that pseudo-log
parameters sections can be evaluated even in the
case, when only minimum, maximum and mean values
of parameters in the wells are
known.
Stratigraphic
Deconvolution
Stratigraphic
deconvolution functions and programs represent a
subtle method of seismic inversion, when both
wavelet shape and amplitude are evaluated comparing
log reflectivity (or contrast) trace with the
observed seismic trace. The correlation
coefficients between synthetic and observed
seismic traces are also visualized along with the
wavelet obtained and the results of inverse
transform both for reflectivity and log parameter.
One can tie log data and seismic with the aid of
these results.
Wavelet calculated can be
stored in a database, edited, and used for other
programs. Based on one or several wavelets
stored in the database, can be made stratigraphic deconvolution
of the seismic section combined with a estimated
section of log data in the cross-well space. Another more robust program offers an
algorithm to create a layer model of the well log data
based on the wavelets stored, events correlated
after deconvolution and a priori information of
the reflectivity.
Post-Processing
Correction Programs
Since seismic
section includes only middle-frequency
constituents the results of seismic inversion usually
have no low and high frequencies. Low frequency
part of the spectrum can be recovered after making
inversion through special
programs: |
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One of the programs makes
low frequency recovery automatically based on the
results of Hilbert
transform; |
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Another program, used
in a more complex case, performs a recovery after
a proper events correlation. |
Section Classification Tool allows using a
variety of seismic and non-seismic profile data to discriminate
different geological objects or features, select prospective zones
and determine the importance of different data, from the
geological and geophysical point of view. User can split the
section into uniform strata, improve the contrast of seismic
horizons and detect lateral heterogeneity when log data are absent
or poor. User can determine the sequential data significance for
the prognosis and obtain informative combinations of the data eliminating non-
informative data and data, which contains almost the same
information. Seismic Classification tool includes main component
and factor analysis, taxonomy, classification and clustering programs.
Taxonomy
These are programs for section classification
without reference point, e.g., wells.
Taxonomy programs makes a whole
section classification in a multidimensional indicator space, based
on a strictly non-linear classification algorithm, which seeks for
continuous domains in the indicator space or continuous relations
between indicators, corresponding to uniform
objects from
geological or geophysical point of view. Fractal geometry analysis
lies behind the algorithms. Program can evaluate
the discrimination
degree for subsections which are taxons, and the sequential
significance of the data from the viewpoint of made
classification. This algorithm is robust to residual data and very powerful for delineating
seismic section features.
Layer
Taxonomy is a program, which applies the
same algorithm as the previous one, but very good for analyzing
the shape of seismic or other data, along some
events in specified windows. This program also provides
discrimination degree and data significance. It is powerful for
correlating horizons broken by faults or small and
periodically repeated objects, such as clinoforms.
Classification
Faster
variant of a classification without references, based on the classic algorithm of cluster analysis in
a multidimensional indicator space. Clusters
characterized by centers and radius of a sphere.
All points in this sphere belong to some cluster.
The positions of centers change until they are
stabilized.
Clustering
These programs perform the classification with reference
points. The points can be specified by well log data or
by seismic features, etc.
Clustering program discovers
zones resembling the references specified, based
on the principles of fuzzy set theory. For each
class of references, that is a cluster, a probable
section is evaluated to belong to this cluster.
These sections enable to test the quality of
clustering. This algorithm is a powerful tool for
delineating seismic section features, as well as
geological objects.
Topology
Another
program which solves similar problem is based upon
applying self-coordinated rule for relationships
between indicators at references and at the points
to classify. This rule resulting from entropy
theory of topological chains of Markov , possesses
strong robustness. Program produces not only
a clustering section in a whole with probability
sections but also estimates the weights of the
information for each one of the
indicators. |
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PMDI Quantitative Prognosis Tool enables to
discover
relationships between well log data and a variety
of data sets and their attributes. Once the relationship being
established is applied to the whole section and to well log data
section, a prediction is produced. Also the tool
allows choosing the combination of data sets,
which possess the most quantity of information, to discover and
delineate prospective objectives and to evaluate
reservoir parameters. The program represents an extremely powerful
and necessary tool to perform a
final prognosis. Informative combination of data
can be stored and used for further
parameter
monitoring.
All computed results are
accompanied by statistical estimates of possible
predictive errors and uncertainties. The following
items are calculated: test of the applied model consistency,
multiple correlations of the profile data sets used and log data,
variation of the observed log data from their locally averaged
values, confidence interval of the prediction, optimistic and
pessimistic predictions. These results allow considering the quality of
obtained prognosis.
Usually seismic (and
other profile data) and log data have different sampling rates. For
log data it is much less than for profile data. There are special
modes to predict averaged log data parameters, this procedure improves
the quality of the
prediction, making the same scale for profile and
log data. Averaging can be made automatically or
in specially delineated
layers. |
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