Page 150 - Fundamentals of Gas Shale Reservoirs

130 PETROPHYSICAL EVALUATION OF GAS SHALE RESERVOIRS

exponent to a value smaller than 2 (Zhao et al., 2007, R
Ramirez et al., 2011). logR log 10 R . 002 t t baseline (6.19)
In cases where within a shale formation, there are both baseline
lean shale intervals and organic‐rich shales, the simplified
1/n
Archie equation, S = (R /R )^ , can be used to quantify gas Baseline is determined when sonic and resistivity directly
t
w
o
saturation. Within lean shale intervals where water saturation overlaid each other or they just tracked each other. According
is basically high, rock resistivity (R ) is low (similar to the to the assumptions of this technique, this condition will exist
o
wet zone in a conventional reservoir rock), whereas within at the organic‐lean interval. The amount of TOC can then be
TOC‐rich, gas‐mature shale intervals water saturation is low determined from the following relationship by knowing the
and thus rock resistivity (R ) is high in comparison with the level of maturity (LOM):
t
lean shale. ( 2 297 0 1688 LOM)
.
.
The use of this approach for the log data shown in TOC logR 10 (6.20)
Figure 6.9 has resulted in a very low gas saturation of about
10% for the upper lean part of the shale interval at a depth of Although this methodology is used extensively for TOC
about 2310 m and a gas saturation of more than 50% at a determination in the shale layers, there are many uncer­
depth of about 2450 m for high TOC shale interval. The sat­ tainties in its evaluation. This method requires similar clay
uration exponent (n) was considered to be 1.7 based on minerals or similar conductive minerals (e.g., pyrite) in both
Luffel and Guidry (1992), who report that a saturation expo­ organic‐lean shale (baseline) and the organic‐rich interval.
nent of 1.7 for shales provides a good match to core‐derived Extensive vertical heterogeneity of the shale layers may
water saturation. result in very high uncertainty for the calculated TOC.
Moreover, this method requires knowledge of the LOM for
6.4.2.3 Determination of TOC There are two main converting the apparent ∆logR to a quantitative TOC. In
methodologies for in situ TOC determination in the gas shale exploration wells the LOM may not be known or may also
layers: the pulsed neutron mineralogy tool and the Passey change with depth (Pemper et al., 2009).
(∆logR) methodology. Furthermore, according to the ΔlogR technique, an
increase in the resistivity and sonic transit time is also a
Pulsed Neutron Mineralogy Tool The pulsed neutron function of hydrocarbon saturation. Passey et al. (1990) con­
mineralogy tool can determine the amount of carbon in the cluded that an increase in the amount of hydrocarbon at the
formation. The most important matrix minerals containing higher thermal maturity level could be correlated to the pre­
carbon are calcite, dolomite, and siderite. Therefore, excess sent TOC content of the rock. However, this assumption
carbon can then be interpreted as organic carbon, seems not to be correct all of the time. Theoretically, the
hydrocarbon, coal, or organic matter (Jacobi et al., 2009) amount of hydrocarbon in the pores relies on both the matu­
using the following relationship: rity level and initially deposited TOC (iTOC), and not on the
amount of TOC present in the rock. Analysis of the data
C TOC C Measured C Calcite C Dolomite C Siderite (6.18) reported by Modica and Lapierre (2012) confirms this idea.
The elemental ratio of silicon to carbon determines whether As can be seen in Figure 6.11, for the data points reported for
this excess carbon is coal or not. To determine whether the the Mowery Shale in the Powder River Basin of Wyoming,
carbon is oil or organic matter, a cut‐off value for uranium is thermal maturity and initial TOC have the higher effect on the
used. If the uranium is above the minimum value, the excess generated hydrocarbons than the present TOC. Therefore,
carbon is assumed to be organic matter; otherwise, it should generated hydrocarbons and, as a result, separation between
be hydrocarbon. The minimum uranium cut‐off is from 4 to 7 sonic and resistivity logs, could be correlated to iTOC and
ppm for most gas shale layers (Pemper et al., 2009). Measuring not present TOC. Although there is a relationship between
in situ carbon for TOC estimation using the pulsed neutron iTOC and TOC, this relationship is not a global relationship
mineralogy tool is preferable compared to other techniques and depends on the thermal maturity of the data points
where TOC is determined from well log data. (Fig. 6.12), and therefore should be (separately) determined
for different case studies.
Passey (∆logR) Methodology This is a practical
methodology first developed by Passey et al. (1990) for 6.4.2.4 Determination of Kerogen Density Kerogen
identifying and calculating TOC in organic‐rich rocks density can be determined from geochemical data but if
using well logs. This method employs overlaying of a geochemical data is not available it can be determined
properly scaled porosity log (generally the sonic transit using the following log‐based procedure which uses
time curve) on a resistivity curve (preferably from a deep NMR and density logs accompanied by the pulsed
reading tool) and then calculating the separation between neutron mineralogy data (Jacobi et al., 2008; Vernik and
these two curves by defining a baseline: Milovac, 2011):