What PDG data provides
PDGs acquire pressure data at high frequency and
over a long duration. A typical data set will include two
types of information; each spike is an unscheduled
shut-in that may be treated as a ‘free’ well test for
PTA. In addition the long term global producing
pressure response, ignoring these spikes, can be
used in association with the well production to perform
production analysis and/or history matching.
The data is there and it is already paid for. It is ‘simply’
a matter of getting at and interpreting the data. Nice
idea, one not so little problem; the available data is
vast and growing. For one single gauge there are
typically 3 to 300 million data points. This will bring
even the fastest of today’s PCs to a grinding halt. But
we need both short-term high frequency data for PTA
and long-term low frequency data for PA.
To perform a transient or production analysis we
typically need 100,000 data points. The trouble is it
is a different 100,000 from the same dataset. To obtain
both, Diamant Master (DM) uses a wavelet algorithm.
The decomposition is presented in the diagram below.
Wavelets may be described as a ‘smart’ filter with a
threshold. For each point the local noise is estimated
for different frequencies. If the local noise is above
threshold, as occurs for pressure breaks when the well
is shut in, this is considered significant and it is kept.
The wavelets act as a high-pass filter. Conversely, if
the noise level is below threshold, this is just noise
and it is filtered out. The wavelets act as a low-pass
filter. As a result, producing pressures will be filtered
out and reduced to a few points per day, while all early
shut-in data will be preserved.
Diamant Master workflow
Diamant Master is a continuous process installed on
a dedicated machine running Windows Server™. It
is operated by engineers (subject to privilege) using
Ecrin or a WEB client. Users can navigate through
the historian databases and select the tags to be
imported. Diamant Master remains connected to the
historians, from which it sequentially mirrors the raw,
unfiltered data. For each mirrored data set, users with
the right privilege may define, for each tag, one or
several wavelet filters. The filters will be executed
on user request or automatically when sufficient new
data have been mirrored. Users may also order partial
reloads of legacy data with a different filter setting, or
no filter at all.
The filtered data is stored in the local DM database to
be subsequently sent to Ecrin analysis modules on a
single drag-and-drop. This data may also be exported
to a third party database.
Diamant Master stores KAPPA technical objects and
files in a hierarchic and intuitive structure to be shared
by Ecrin interpretation modules.
Connecting to data
The beauty of standards is that there are so many
to choose from. So it is in the Oil Industry; there is
no standard way to store PDG data. Almost every
provider so far has its own data model, and Operators
routinely have several providers as well as their
own data model. Most databases have low-level
access (ODBC, OLEDB, OPC, etc), but this is, at
best, cumbersome for end users. Each data model
requires a specific adaptor to navigate and access
data. A published API permits the development and
connection to customized adaptors, automatically
downloaded by Ecrin from Diamant Master.
When connecting to a new tag Diamant Master
proceeds with a quick data scan of one point in every
ten thousand to preview the data and help in spotting
anomalies and gross errors. A user defined data
window can immediately discard obvious outliers. A
first series of points, typically 100,000 or one week
of data, is then used in an interactive session for
the engineer to adjust the wavelet setting and data
post-filtering, based on a maximum Δt and Δp. Upon
user acceptance the filtering is performed using
overlapping increments the size of the initial sample.
These are user defined and permit mathematical
operations on data channels with a comprehensive
formulae package. The outcome may be another data
set or a Boolean function of time that may be used
to create an alarm. The outcome of the alarm is to
display, in the Diamant window, the execution of an
alarm E-mail, or the call of a user defined DLL.
Identifying shut-ins... automatically
Until recently all algorithms, including wavelets, failed
miserably to automatically identify shut-ins, especially
when data sets were showing both soft and hard shutins.
Diamant Master has an exclusive algorithm which
automatically identifies shut-ins. Years of PDG data
can be scanned in seconds. Shut-ins are identified
and made available to the user for analysis in Saphir
NL. This was the missing link to allow full automation
of the data processing. The times of shut-ins may also
be used to modify the production history in order to
honor both shut-in periods and cumulative production.
Transferring data to Ecrin analysis modules
Filtered data can be transferred to any Ecrin analysis
module by drag-drop. Shut-ins are analyzed and
compared using Saphir NL, producing rates and
pressures can be analysed and matched by Topaze
NL, and filtered data may also be used to constrain
With the transients identified and daily rates correctly
allocated and cleaned, shut-in data can be sent,
en masse or individually, to a Saphir NL document
automatically created by Ecrin. The result can be the
latest shut-ins or a cloud of transients from previous
years that may be analysed together, as a selected
group or discretely.
WEB access and administration
Diamant is the best way to handle data, technical
objects and files when using KAPPA applications.
However these can also be accessed from an Internet
browser by connecting to the DM server IP address
or its name in the domain. The engineer can view
the status of the different processes, access the
data tables and technical objects and recover the
filtered data in Excel™ format without using Ecrin.
An ActiveX control can also be loaded to navigate the
data structure in the same environment as Diamant.
What’s next ?
Diamant Master v4.12 is compatible with both Ecrin
v4.12 and v4.20. A major change of generation is
currently taking place. KAPPA Server v5.0 will replace
Diamant Master v4.12 in 2012.
KAPPA Server will be our first Generation 5 product,
developed under the DOT.NET environment. It will be
interfacing with Ecrin v4.20 and it will integrate our
second generation of wavelet filters, allowing raw data
to be filtered with no prior interpolation.
Typical PDG data response gathered over two weeks
Wavelets decomposition and denoising algorithm
Wavelets denoising: (1) raw data = 10,000 points; too low (2),
too high (3) and selected (4) thresholds; (5) post-filtration; (6)
filtered data = 70 points
Diamant Master processes
Automatic Shut-in identification in Diamant Master v4.12
Multiple build-up analysis in Saphir
History matching in Topaze
Build-ups indentified in Diamant and ready to send to Saphir
Generation 5 interface
Generation 5 interface
A second generation of wavelets