62nd Annual Report on Research 2017

SUMMARY

This project has been an important step in taking into account actual rock fabric and geochemistry of organic-rock mudrocks in rock physics models used for characterization of such complex formations. The initial objective proposed and achieved by the PI was quantifying spatial connectivity of kerogen in organic-rich mudrocks and quantifying its impact on electrical properties of organic-rich mudrocks. Pursuing this objective has led to development of a new model for interpretation of electrical measurements in organic-rich mudrocks, which takes into account rock fabric and geochemistry of organic-rich mudrocks for assessment of rock properties such as spatial distribution of electrically conductive components of the rocks as well as water saturation. During the past three years, the PI’s research group demonstrated how sensitive can electrical conductivity measurements be to directional connectivity and volumetric concentration of kerogen using numerical modeling. They also performed geochemical characterization on pure kerogen samples at different thermal maturity levels, quantified aromaticity of the samples and investigated the possibility of graphitization as thermal maturity increases, and measured electrical conductivity of pure kerogen and mudrock samples as a function of thermal maturity. Finally, they developed a new resistivity model that takes into account directional connectivity of kerogen and other conductive rock components and tested their model on synthetic and actual rock samples. 

OBJECTIVES

The objectives pursued during the third year included:

Objective No. 1: Develop a new electrical resistivity model that quantitatively takes into account directional connectivity of conductive rock components and their electrical properties, which is a function of rock geochemistry

Objective No. 2: Apply the developed model to synthetic and actual rock samples to improve estimates of water saturation and enable assessment of rock fabric (e.g., spatial distribution and connectivity of rock components such as kerogen and clay minerals) in organic-rich mudrocks

ACCOMPLISHED TASKS: METHODS AND RESULTS

Model Development and Inversion Algorithm

The underlying petrophysical model includes clay networks (clay particles and clay-bound water), conductive matrix components (e.g., pyrite and kerogen), non-conductive grains, and hydrocarbon. We assume that there is a fully percolating network through porous media. This network is composed mainly of clays, but its conductivity can be altered by the contacting kerogen and pyrite elements in a dispersed form. We quantify the effect of dispersed conductive inclusions into the electrical conductivity of the percolating networks by sequentially applying the Pore Combination Modeling via

where σ_c is the conductivity of the clay, σ_c,k is the combined conductivity of the clay network and kerogen, σ_bk is the bulk conductivity of kerogen, ^cϕ_c,k is the volumetric concentration of clay in the clay-kerogen mixture, L_p and L_k are depolarization factors, σ_c,k,p is the combined conductivity of the clay, kerogen, and pyrite, ^c,kϕ_c,k,p is the volumetric concentration of the clay and kerogen in the clay-kerogen-pyrite mixture. In order to incorporate the spatial distribution of the percolating network on its conductivity, we define its effective conductivity in the i-direction, σ_CN,i, as

where C_CC,i is the constriction factor in the i-direction, ^c,p,kϕ_R is the volumetric concentration of the conducting components and ^c,p,kτ_e,i is the directional electrical tortuosity of the percolating network along i direction. Finally, the conductivity of the organic-rich mudrock in the i-direction, σ_ORR,i, is assumed to be the sum of the conductivity of all the individually percolating conducting networks.

Application of this new model for assessment of rock properties such as directional connectivity of conductive rock components and water saturation in organic-rich mudrocks requires an inversion algorithm demonstrated in Figure 1.

Figure 1: Inversion algorithm that uses the new model for assessment of rock properties

Model Verification

The reliability of the proposed method is tested on synthetic and actual rock samples covering a wide range of rock properties. Figure 2 compares the electrical conductivity calculated using the introduced method and the Waxman-Smits model against the actual electrical conductivity of synthetic and actual samples, respectively. The new model decreased the errors in estimates of electrical conductivity from 74.6% to 29.7% and from 71.5% and 21.3% in actual and synthetic rock samples, respectively.

Figure 2: Electrical conductivity calculated using the introduced method and the Waxman-Smits model against the actual electrical conductivity of (a) synthetic and (b) actual samples, respectively.

CONCLUSIONS

In previous reports, we showed that rock fabric (directional connectivity and spatial distribution of rock components) and geochemistry significantly affect electrical properties of organic-rich mudrocks. In this reporting period, we used our introduced directional connectivity parameter for developing a new rock physics model that incorporates spatial distribution of kerogen network as well as other rock components and their electrical properties (which can be a function of thermal maturity) in interpretation of electrical measurements. We applied the introduced method to several synthetic and actual pore-scale images of organic-rich mudrocks. The results of numerical simulations showed that the sensitivity of electrical conductivity to spatial distribution of conductive components such as pyrite and kerogen, can be significant, depending on their volumetric concentration and electrical properties, which can vary as a function of thermal maturity (quantified through experimental work in the previous report). Experimental results of this project also suggest that wettability of kerogen can be altered as a function of thermal maturity, which can significantly affect electrical properties of organic-rich mudrocks. If saline water can be proven to occupy the organic pores, the effective conductivity of the kerogen can significantly increase. Furthermore, the amount of graphite within kerogen can increase its electrical conductivity and lead to a more significant influence of kerogen on the electrical properties of the rock. The developed model in this project can be used not only for assessment of spatial distribution of kerogen (in the case of high thermal maturity), but also for assessment of other rock properties such as water saturation. For instance, comparison of the introduced method against conventional Waxman-Smits model showed that the error in water saturation estimates could be decreased by up to 35% when spatial distribution of all the conductive components (e.g., pyrite, clay, and kerogen) was taken into account in the introduced method.