Log analysis for unconventionals

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Shale volume estimation

The estimation of the shale volume in the zone of interest can be performed in the available wells using the normalized version of the Gamma-Ray log (GRn), and using both neutron and density porosity logs.

Using the Gamma-Ray log

GR vs. Corrected Spectral GR for Well B, color-coded by formation. The correlation between both GR responses allows an adequate linear fit of 0.981. The linear empirical relationship is used to calculate the corrected GR for uranium in the Well A.

Following the concept that the increase in radioactivity of the organic-rich shales is related to their organic matter content, the GR and spectral GR responses need to be corrected for uranium before estimating clay content. This element forms compounds that sorbs to clays and organic material in both cases where their depositional environment is anoxic marine or oxidizing lacustrine (Ahmed and Meehan, 2016). In case spectral GR data are not available for a particular well (Well A), its correction for uranium should be conducted by means of a linear empirical relationship constructed using both, the corrected spectral GR of another well in the area of interest (Well B) plotted against its original log (Figure XX). The following equation is used for the GR correction for uranium:

Where, GRc = corrected GR, GR = total GR, and U = uranium in ppm.

After correcting the GR for uranium to remove the effect of the organic matter, the normalization of the GR log is conducted as a method of reducing mud weight and hole size effects (Crain et al., 2014). The normalization process follows the assumption that all pure shales in an area have the same GR values, and that all clean sands have the same GR log reading using the following equation:

Where, GRn = normalized corrected GR in API units, GRmin = GR clean sand value to normalize to, GRmax = GR shale value to normalize to, GR = total GR, GRlow = GR clean sand value in the well/zone, GRhigh = GR shale value in the well/zone.

To calculate Vshale from GRn, the following methodology should be applied:

Where, VshGRn = shale volume from normalized GR log, GRn = normalized GR, GR0 = GR log reading in 100% clean zone, GR100 = GR log reading in 100% shale.

Using porosity logs

Well A logs. From left to right, total GR, the corrected GR for uranium and its normalized readings (thick black curve), neutron porosity and density, density porosity and the comparison between the estimated shale volumes (VshGrn, VshNPHI, VshPHI). Shale volumes calculated with the three methods follow the separation trend between NPHI and RHOZ except in the dolomitic formation (in grey). Since the high-density porosity reading in the shales is due primarily to organic matter rather than porosity, values of shale volume in these two members are considered underestimated. VshGRn and VshNPHI are taken as better representations of the relative volume fraction of shales in the formations of interest (red, yellow and green).

Given the neutron porosity log and the densities of clay (2.68 g/cc) and shale (2.35 g/cc), the volume fraction of shale (VshNPHI) can be calculated via determination of the clay-bound water by setting values representative of clean sand and pure shale that correspond to the maximum and minimum value of the neutron porosity log, respectively.

Another method for estimating the shale volume uses both the density and neutron porosity logs. The linear interpolation of the separation between these two logs corresponds to the following algebraic formula to solve for shale volume:

Where, VshPHI = Vshale from porosity logs, NPHI = neutron log reading in zone of interest, PHID = density log porosity reading in zone of interest, NPHIsh = Neutron log reading in 100% shale, PHIDsh = apparent density porosity in shale. The density porosity and neutron porosity of pure shale are 0 and 0.4, respectively. The neutron porosity at pure shale is taken from the density neutron cross-plot at the depths of the shales of interest.

In general, the shale volumes calculated should follow the separation trend between NPHI and density (RHOZ) curves: the higher the separation, the higher the shale volume (Fig XXX). In cases where the lithology is characterized by dolomites, the separation between the two curves is not a function of shale (Crain, 2000).

TOC estimation

Total organic carbon (TOC) is an important parameter in the evaluation of kerogen-rich unconventional reservoirs (Charsky and Herron, 2013).

Heslop (2010) method

Well A logs. From left to right, total GR and the normalized corrected GR (GRn), neutron porosity and density, P-wave sonic, and the superposition of the deep resistivity and the GRn curves. The cross-over between resistivity and gamma-ray readings (in yellow) is indicative of high TOC content.

An initial identification of zones with high TOC content can be performed using the Heslop (2010) method. The increase in GR readings and deep resistivity (RT) can be related to TOC within shales and there is a relationship between the curves associated with these two petrophysical properties. In a clean matrix, the GR typically decreases whereas the resistivity increases. On the other hand, in non-source shales (i.e. low TOC content), the GR increases while the Rt decreases. Since these two curves tend to “hour-glass” when plotted using conventional scales, reversing and selecting appropriate values for the Rt scale causes the GR and the Rt curves to track, except in source shales where both the GR and Rt values increase due to the TOC content (Heslop, 2010).

The crossover between the GR and Rt curves is indicative of the TOC effect in the shale members in which these two properties increase, and the hydrocarbon potential is observed on logs as lower density relative to shale density, “hot” GR response, increased P-wave sonic (DT) relative to shale DT, and increased neutron porosity relative to shale neutron (Fig. XXX).

Passey (1990) method

Assuming that resistivity logs respond to fluids, while porosity logs (sonic, density, or neutron) respond to kerogen/matrix and fluids, the Passey (1990) method combines these two type of logs to estimate TOC in organic-rich rocks (Passey, 1990). Using either porosity curve, the method relies on porosity and deep resistivity readings separating from each other in organic-rich rocks, whereas in organic-lean rocks, the two curves overlie. The separation between the two curves or the scaled difference (∆logR) between them is related to the TOC content through the level of thermal maturation (LOM) by the following relation:

Where, ∆logR = scaled difference between deep resistivity and density logs and LOM = level of organic maturity.

Where, RT = deep resistivity log in ohm/m, RTbaseline = resistivity in the organic-lean zone in ohm/m, PHI = porosity log (i.e. sonic, density or neutron logs), PHIbaseline = porosity log reading in the organic-lean zone. The scaling factor is calculated after baselining the two curves in the organic-lean zone.

If the type of organic matter is known, the level of organic maturity (LOM) (Hood et al., 1975) can be determined from a variety of measurements such as vitrinite reflectance, thermal alteration index (Tmax) or Rock-Eval pyrolysis. In over-mature shale reservoirs with LOM values greater than 10.5, the limit of calibration of maturity to TOC is reached (Charsky and Herron, 2013). Figure XXX shows the estimated TOC logs using sonic, neutron porosity, density, and deep resistivity logs. Note the good agreement between the estimations calculated from the density and neutron porosity logs.