Indigo PNN —
Memory Pulsed
Neutron-Neutron
Logging

Pulsed neutron-neutron (Sigma) logging is based on bursting neutrons into the near-wellbore zone and consequent monitoring of neutron count decay due to scattering and capturing.

Concept SPE


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about Indigo PNN

Capture neutron count decay depends on reservoir lithology and hydrogen and chloride contents. There are a number of mathematical procedures over raw decay data yielding various reservoir parameters, such as hydrogen index and chloride concentration. One of the most important decay parameters is the capture cross-section, also known as Sigma which gives a name for a wide range of neutron decay based techniques. The main problem in the Sigma technique is that the calculation of reservoir water invasion is based on the difference between water and oil Sigma values. If they are close, Sigma calculations may fail. The Sigma technology also fails when reservoir porosity is low. The decay response is very complex and depends on many factors including tool design and generator quality. However, once the survey is completed, one can check the data quality by visual and mathematical analyses and evaluate calculation quality using the mean square error log.

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The conventional Sigma tools record the secondary gamma ray emission produced by neutron capture. They are usually referred to as pulsed neutron gamma (PNG) tools. Unlike PNG tools, the PNN tool directly detects neutron response. Modern neutron detectors are very efficient and capture more than 90% of neutrons passing through detector’s chamber. Generally, the PNN tool can be used to determine invasion in reservoirs with lower water salinities and porosities than for conventional PNG tools.

A key advantage of the PNN technology is that its neutron decay rate always goes down to zero, whereas PNG decay is always floored at the natural GR background. In many practical cases the GR background may be disturbed by scale deposits, caused by acidisation or high cumulative water flux, which increases the GR background and makes PNG data noisy and properly declining in time. In such cases, the PNN tool may have an advantage over conventional PNG tools.


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Hardware tools


Indigo PNN


Example 1


The example below shows PNN SIGMA survey conducted through tubing.

The COUNT_NEAR and COUNT_FAR panels show the actual time decay of neutron density at near and far detectors. The COUNT_RATIO panel shows the distribution of ratio of cumulative counts during the survey. This panel is very sensitive to reservoir lithology and porosity. The further processing of this panel yields the synthetic TPHI log which usually has a very good correlation with reservoir porosity NPHI from open-hole data.


PNN SIGMA Flyer Pic1_sm


The SIGMA panel is derived from COUNT panels through the stabilised multi-exponential decomposition and correction for porosity impact on near and far responses. The panel is easily split into a borehole and reservoir responses with latter to be sensitive to reservoir lithology and water invasion. The consequent processing of this panel yields the reservoir capture cross-section (SIGMA_FRM) log which is further interpreted in terms of sweep (blue color on VOL MODEL panel). In this case the main water breakthrough ensues across the bottom perforations.

Example 2


The next example shows SIGMA survey in interchange of dolomite and anhydrite rocks. One can note a persistent quality of PNN SIGMA data both in casing and tubing.

The porosity developments in limestone streaks are clearly picked up by COUNT_RATIO panel. The TPHI log shows a very good correlation with open-hole porosity NPHI.


PNN SIGMA Flyer Pic2_sm


The SIGMA panel is very sensitive to anhydrite streaks which have high capture cross-section and extend the high values through all the channels.

Volumetric interpretation suggests that water invasion across perforations is not high and most of the produced water comes from the overlying non-perforated reservoir unit by downward channelling behind the casing, as confirmed by spectral noise logging and temperature simulations.