Shale composition estimation based on well log analysis

The first step involves the following procedures: to create an inventory of available well logs, and consider which logs are more useful in identifying particular shale components; to delimitate the interval to study, as, due to changes in deposition energy, shale composition can vary vertically; to establish shale baselines for each well and log measured in the field, and to compare them; and finally to identify trends (in compaction or eventually in composition). Below is a detailed analysis of the available logs, their features and uses for shale composition estimation

Gamma Ray (GR): this log is a direct measurement of rock radioactivity (presence of radioactive components). It is used to establish how “pure” the shale is, based on the analysis of shale electrofacies homogeneity, and also to define the clay-silt relation or relative percentages (as quartz and feldspar are not radioactive and clays are); and coarsening up or fining up trends (silt and sand content vertical variation in an interval). Radioactivity can vary in clays (see Table 2-3), according to their content of uranium, thorium and potassium. Special attention needs to be paid to the GR log interpretation when the borehole was drilled using bentonite (a type of smectite) based mud fluid, as this material is radioactive and GR measures can be affected, especially under bad hole conditions (washouts), where more drilling fluid is accumulated in the borehole cavity.

Clay Mineral °API

Illite 182

Kaolinite 155

Smectite 90

Chlorite 50

Table 2-3 Typical GR values in shales were a specific type of clay is dominant (not 100% monomineralic

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Spectral Gamma Ray: is a radioactivity measure that differentiates uranium, potassium and thorium signals, and hence proportions. Potassium and thorium content are used to identify clays (see Table 2-4), while uranium abundance is indicative of organic matter content.

Potassium content Thorium content Mineral % by weight Average % Average (ppm)

Illite 3.51 – 8.31 5.20 6 - 22

Glauconite 3.20 – 5.80 4.50 2 - 8

Kaolinite 0.00 – 1.49 0.63 18 - 26

Smectite 0.00 – 0.60 0.22 10 - 24

Chlorite 0 0 0 - 7

Table 2-4 Potassium and Thorium content by clay, taken from published literature [Rider and Kennedy,

2013]

Density: this log measures formation bulk density (recording gamma ray scattering), which is the overall density record including solid matrix and fluid enclosed in the pore space. Shales in conventional reservoirs are water saturated, so by knowing water properties it is easy to determine the occurrence and proportion of mineral components of the rock solid matrix and their bulk density (see Table 2-5). Density log measures are apparent (low readings) in washout sections (borehole enlargement) because the tool is recording mud properties instead of true formation, and needs to be corrected through accurate analysis. As can be observed in Table 2-5, the bulk densities of clays have a wide range of values, depending on consolidation and bound water content, so compaction needs to be assessed prior to using a clay distinctive bulk density for shale composition differentiation, as some clay densities’ values overlap each other.

Mineral _{Bulk Density (g/cm}3

)

Silt Quartz 2.65

Fraction Feldspar (average) 2.62

Illite 2.5 – 3.0

Glauconite 2.67

Clay Kaolinite 2.2 – 2.6

Fraction Smectite (Montmorillonite) 2.0 – 3.0

Chlorite 2.6 – 3.3

Calcite 2.71

Organic matter (kerogen) 1.3

Table 2-5 Main shale components’ bulk density, values taken from published literature [Mavko et al., 2009;

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Caliper: This is a contact tool that measures inner borehole diameter variations, which is used in quality control of other logs, to ensure that the tool is recording formation properties instead of mud filtrate. Sloughing (borehole diameter reduction or ‘tight spots’) is usually related to the presence of swelling clays, such as smectite (montmorillonite and bentonite). Washouts or increases in the borehole diameter in shales are generally related to poorly consolidated shaly intervals, but are more common in illite and kaolinite clay dominated intervals.

Sonic: this log measures P-wave and S-wave (dipole tools) propagation in the formation (in fact, the tool measures acoustic slowness or interval transit time). Each mineral has different P-wave and S-wave velocities, which can be used to corroborate shale mineral composition (Table 2-6). These reference values can increase or decrease according to compaction and bound water content, but the values do not overlap each other. The sonic log is an excellent indicator of compaction and porosity reduction in shales; it is also used to detect overpressured or underpressured intervals, expressed by an anomalous decrease or increase in the shale compaction trend (naturally velocity gradually increase with depth).

Mineral P-wave Velocity (m/s) S-wave Velocity (m/s)

Silt Quartz 5760 3660

Fraction Feldspar (average) 4680 2390

Illite 4320 2540 Clay Glauconite 5640 3830 Fraction Kaolinite 1440 930 Smectite (Montmorillonite) 3600 1850 Chlorite 5490 3730 Calcite 6640 3440

Organic matter (kerogen) 2250 1450

Table 2-6 Main shale components’ P-wave and S-wave velocities, values taken from published literature

[Mavko et al., 2009; Rider and Kennedy, 2013]

Resistivity: this log measures the formation’s ability to conduct electricity. Most rock frames do not play an active part in determining the formation resistivity. The conductivity is basically related to the fluid contained in the pore space, (water, oil or gas) and their amount of associated ions (salinity); however, in the case of shales, the clay fraction introduces an excess of conductivity, due the presence of brine in their pore space and negatively charged molecules of water in the clay crystalline structure. The

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phyllosilicate structure determines the clay’s cation exchange capacity, CEC (Table 2-7), and hence its conductivity. As can be observed, kaolinite and chlorite are more resistive than illite, smectite clays, due their lower water content. As micro resistivity logs have one of the highest vertical resolutions, the microspherical resistivity log (MSFL) can be used to determine a shale’s heterogeneity, allowing silt and fine sand interbedded laminations and layers to be detected and differentiated from most clays (quartz and feldspar do not conduct electricity).

Mineral Average CEC (meq/g)

Illite 0.25

Kaolinite 0.04

Smectite 1

Chlorite 0.04

Table 2-7 Clay cation exchange capacity, taken from published literature [Dewan, 1983]

Photoelectric Factor (PEF): this is a continuous record of the effective photoelectric absorption per electron index of a formation. As this measurement is dependent on the atomic number of the formation, PEF readings are not influenced by fluids and are very responsive to heavy elements such as iron (high atomic numbers), and can be used as shale and clay composition discriminators, due to the variable heavy element composition inside their crystalline structure. As can be seen in Table 2-8, the PEF log can be very useful to differentiate most clays (only kaolinite and smectite values overlap). Some corrections in PEF readings may be necessary if the borehole was drilled with a barite based mud.

Mineral PEF (barn/gr)

Silt Quartz 1.806 Fraction Feldspar 2.86 Illite 2.837 Clay Glauconite 5.32 Fraction Kaolinite 1.635 Smectite 1.636 Chlorite 9.973 Calcite 5.084

Table 2-8 Photo Electric Factor (PEF) for main shale components, taken from published literature [Rider

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Neutron: this measures the Hydrogen Index, which is related to the formation’s hydrogen content. The log is given in neutron porosity units. While, in sands, the hydrogen is strictly related to water and fluids contained in the pore space, in shales there is also hydrogen associated with the bound water in the clay crystalline structure, so the neutron porosity measured is overestimated. A typical neutron log will indicate Neutron Porosity values for shales between 25 and 75% (average is between 40-50%), while the range for sands is 0-30% and for limestone is from 0-35% [Rider and Kennedy,2013]. The interstitial water in clays also can be used to differentiate them (Table 2-9). When Neutron-Porosity and Density logs are plotted in the same track at specific scales (Density from 1.95 to 2.95 g/cm3 and Neutron-Porosity from 0.45 to -0.15 fraction in reverse scale), the separation between both curves can be used as indicative of shale silt and clay content. If the separation decreases, that implies that the silt content is higher, while if the separation increases, the clay fraction content dominates the shale composition.

Mineral % water

(average) Hydrogen index Neutron Porosity

Illite 8 0.09 30

Kaolinite 13 0.37 37

Smectite 18 - 22 0.64 52

Chlorite 14 0.32 44

Table 2-9 Clay water content and Neutron Porosity measures, taken from published literature [Rider and

Kennedy, 2013]

Nuclear Magnetic Resonance: this log records the behaviour of protons (hydrogen nuclei) under an induced magnetic field, as a measure of their relaxation time (the protons’ rotation and alignment time after the induced magnetic field is removed and hydrogen nuclei return to their original position, which is aligned with the Earth’s natural magnetic field). As the hydrogen protons contained in the clay bound water are quite tight, the relaxation time is very fast and the T2 distribution (one of the relaxation time parameters measured by the tool) is unimodal for most of the clays. Only very high smectite concentrations could give some differentiation in the T2, due to higher water content [Rider and Kennedy, 2013].

Dipmeter: this log provides a continuous record of formation dip and azimuth. The tool acquires four microresistivity curves in orthogonal position in the borehole; a correlation

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between them is then used to calculate the dip and the azimuth. Depending on the vertical resolution of the processing (which is usually very high), the dipmeter can be used in sedimentological and stratigraphic studies to analyse paleocurrents and sedimentary structures such as lamination and bedding (which in the specific case of shales can be used to infer shale heterogeneity, i.e. sand and silt content).

Image logs: images can be produced from electrical, acoustic, density, photoelectric, gamma ray and calliper measurements, but the higher resolution comes from electrical (multi pad) and acoustic logs. Based on 0.5-centimetre vertical resolution, bedding, and even textural analysis can be performed, thin-bedded sequences that can look like shaly intervals can be better characterized and shale, silt and fine sand lithofacies can be separated.

It is clear that qualitative analysis of shale composition can be performed using a single or more integrated logs to discriminate between clay and silt mineral properties. On the other hand, quantitative shale composition analysis based on logs requires the integration of a minimum number of logs and a weighted relationship between the different parameters, which is usually calibrated from previous knowledge about the basin stratigraphy and even core laboratory tests performed to representative lithologies of the area: this is basically what most wireline log service companies offer as part of their portfolio under the “Lithologic log”. Given that, for this research, there were no calibration algorithms available, the quantitative analysis of shale composition was based on assumptions for the clay type proportions, based on the study of clay provenance, which is explained next.