Handling PDG data
PDGs acquire pressure data at high frequency
and over a long duration capturing build-ups
as ‘free’ well test candidates for PTA. The long
term response can be used in association with
the well production to perform production analysis
and/or history matching.
The data is vast with a single gauge typically
generating 3 to 300 million data points. It is often
difficult to locate and when used requires a different
emphasis; short-term high frequency data for PTA
and long-term low frequency data for PA.
Wavelet filtering
To perform a PTA or PA analysis typically requires
100,000
data points, but it is a different 100,000 from
the same dataset. To obtain both, KAPPA Server (Ks)
uses a wavelet algorithm. This 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 retained. The wavelets
act as a high-pass filter. Conversely, if the noise level
is below threshold, this is 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.
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-filtra-
tion; (6) filtered data = 70 points
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