Electricity: measuring and testing – Particle precession resonance – Using well logging device
Reexamination Certificate
1999-08-10
2002-04-23
Oda, Christine (Department: 2862)
Electricity: measuring and testing
Particle precession resonance
Using well logging device
Reexamination Certificate
active
06377042
ABSTRACT:
FIELD OF THE INVENTION
The present invention relates to nuclear magnetic resonance (NMR) logging, and more particularly to a method and system for processing different signals in the time domain to obtain a composite signal that is optimized in terms of its transform domain resolution.
BACKGROUND OF THE INVENTION
Nuclear magnetic resonance (NMR) logging has become an important input to formation evaluation in hydrocarbon exploration and is one of the preferred methods for determining formation parameters. Improvements in hardware as well as advances in data analysis and interpretation allow log analysts to generate detailed reservoir description reports, including clay-bound and capillary-bound related porosity, estimates of the amounts of bound and free fluids, fluid types (i.e., oil, gas and water), as well as permeability, based on NMR logs.
The basic input for analysis of NMR data are spectra of the transversal NMR relaxation time T
2
calculated from pulse-echo trains. Several issues arise in this context, and are considered in some detail next.
T
2
resolution
T
2
resolution is affected by several parameters of the echo train, including the inter-echo spacing, echo train length and the noise.
Generally, the temporal length of the echo trains determines the maximum T
2
that can be resolved.
FIG. 1
shows the normalized error between an input model and a T
2
inversion result as a function of echo train length, and in particular indicates the longest resolvable T
2
component as a function of the echo train length. The solid line shows the exact modeling results, while the dashed line represents the trend. The results were modeled using a Monte Carlo method, the noise standard deviation was &sgr;=1 p.u.
FIG. 1
suggests that the longest resolvable T
2
component is on the order of 2-3 times the length of the echo train. This is indicated in the figure by a sharp increase of the normalized error for T
2
/echo-train-length ratio>2. Theoretically, Whittall et al. (see the reference below) have found that the “resolving power” of the echo train is proportional to
SNR•{square root over (Ne)}
(1)
where SNR is the signal-to-noise ratio of the signal and Ne is the number of echoes.
FIG. 1
in combination with Eq. (1) indicates that the echo train length (T
e
•Ne) has a stronger influence on the longest T
2
that can be resolved than the noise.
Further modeling results support the assumption that noise is critical for the resolution of fast T
2
components.
FIG. 2
shows the normalized error between fast T
2
components (0.5 to 3 ms) and the input model as a function of noise. The inter-echo spacing T
e
is 0.6 ms, &sgr; ranges from 0.1 to 10 p.u. As expected, the uncertainty in determining fast T
2
components increases with the amount of noise.
Another aspect to consider is the ability to resolve fast T
2
components with respect to inter-echo spacing T
e
. The modeling results are presented in FIG.
3
. The noise standard deviation is &sgr;=1 p.u. The normalized error is shown as a function of the fastest T
2
component normalized by T
e
. The fastest T
2
component, which can be resolved, is on the order of the inter-echo-spacing T
e
. Note that this holds true only if the first echo (recorded after one T
e
-time) is included in the inversion. The results presented above allow the following conclusions:
(1) The resolution of fast T
2
components depends both on T
e
and noise. Low noise on the early echoes is as important as a small T
e
to obtain accurate short T
2
's; and
(2) The temporal echo train length is the limiting factor for the resolution of long T
2
relaxation times. Noise does not play such an important role.
Note that all results were calculated using the fast T
2
inversion technique introduced by Prammer (MAP ALGORITHM (see reference to paper SPE 28368 below). It is expected that other inversion techniques will produce similar results.
Noise Optimization
Edwards and Chen suggested to improve the accuracy of results from NMR well logs by time-dependent filtering of echo train data. (see reference to paper RR below). They recommend applying a relatively weak filter on early echoes and gradually increasing the filter strength for later echoes. The results outlined above indicate that no significant improvement in T
2
resolution will be achieved by filtering.
Other methods, such as “windowing techniques” suffer from similar limitations. In order to preserve the information contents of the early echoes (yielding fast T
2
components), the window length for the early echoes has to be very short. Since a window length of 2 would effectively double the minimal T
2
component, a common practice is to set the window length to 1 for the first echoes, i.e., use the early echoes instead of windows. This highlights the importance of recording good, low noise, early echoes in the first place. With a multi-volume tool this can be done efficiently by stacking, while single volume tools need to sacrifice logging speed.
Prammer et al. introduced a technique, originally designed for a dual-volume NMR logging tool, to record low noise pulse-echo data. (See reference to Prammer et al., paper SPE 36522 below). The method allows to acquire pulse-echo NMR data covering the entire geologically meaningful T
2
range (approximately between 0.5 ms and 2 sec.) with adequate resolution and precision at acceptable logging speeds.
Essentially, two sets of data are recorded (quasi) simultaneously. One data stream consists of short stacked, low noise, echo trains with T
e
=0.6 ms. The second data set includes long echo trains. It is recognized in the art that the early echoes of a CPMG pulse-echo data are significant for the determination of fast T
2
components. Slow T
2
components on the other hand can only be resolved with long echo trains.
The method involves recording blocks of short, under-polarized echo trains resolving the fast relaxation components T
2
, interleaved with long, fully polarized echo trains that allow the determination of slow components. The two echo trains are analyzed separately and the partial spectra are combined to obtain a complete spectrum. This technique, developed for NUMAR Corporation's (a Halliburton Company) dual-volume tool (MRIL® C/TP*), allows acceptable logging speeds, while acquiring NMR logs of good quality. For a more detailed discussion of the method, the reader is directed to application Ser. No. 08/816,395 filed Mar. 13, 1997 to one of the co-inventors of this application, which is hereby incorporated by reference for all purposes. Extending the effective range of T
2
measurements using multiple quasi-simultaneous measurements represents an important advancement of the art.
It should be noted that while the wait time Tw between two long data sets is sufficiently long to fully polarize the hydrogen atoms, the 0.6 ms data used in the Prammer et al. method is recorded with a wait time of about Tw=20 ms. Thus the long components in the 0.6 ms data are not fully polarized. Hence the two data sets are inverted into T
2
domain separately. (See reference to paper SPE 36522 below).
In a separate step the two partial spectra are combined into one spectrum covering the full T
2
range. Although this method provides good results in most cases, the choice of the “combining point” of the two input spectra introduces some uncertainty. (See the references to Chen et al., paper SCA 9702; and Dunn et al., paper JJ cited below).
Another set of issues is presented by the latest generation of NMR logging tools (MRIL® Series D to NUMAR Corporation, a Halliburton company) that extend the concept of combining different echo trains and provide further analysis flexibility. These multi-volume instruments allow to simultaneously record NMR data with different inter-echo spacing T
e
, wait time T
w
, and signal-to-noise ratio (SNR). Each part of the data set can emphasize different NMR properties. That way, almost universal data can be acquired in single-pass operation. The problem then remains how to co
Menger Stefan K.
Prammer Manfred G.
Fetzner Tiffany A.
NUMAR Corporation
Oda Christine
Pennie & Edmonds LLP
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