Abstract
As a high-resolution geophysical method employed by the oil and gas industry, well logging can be used to accurately investigate reservoirs. Challenges associated with shale gas reservoir exploration increase the importance of applying elastic parameters or velocity at the logging scale. An efficient shale rock physics model is the foundation for the successful application of this method. We propose a procedure for modelling shale rock physics in which an appropriate modelling method is applied for different compositions of shale rock. The stiffnesses of the kerogen and fluid (oil, gas or water) mixture are obtained with the Kuster-Toksöz model, which assumes that the fluid is included in the kerogen matrix. A self-consistent approximation method is used to model clay, where the clay pores are filled with formation water. The Backus averaging model is then used to simulate the influence of laminated clay and laminated kerogen. Elastic parameter simulations using well logging data show the importance of treating the volume fractions of laminated clay and kerogen carefully. A comparison of the measured compressional slowness and modelled compressional slowness shows the efficiency of the proposed modelling procedure.
Highlights
Rock physics concepts are widely used to establish connections between rock compositions and macroscopic properties
Research on shale rock physics models was performed by Vernik and Nur[1], and the efficiency of such models was first investigated in Bakken shale[1,2]
The Gassmann theory is more general than the Backus average method because it does not make any assumptions on the shape of the pores and grains[7]
Summary
C3∗3 ρ where ρ is the average density; and VPV is for the vertically propagating P-wave, which is the measured velocity in acoustic logging. Because we do not have the volume fraction of the layered clay and layered kerogen in the rock composition data, we first simulate the DTC result using our modelling procedure with an isotropic model. The two lines are consistent with each other, which shows the efficiency of our shale rock physics modelling procedure. After we add the layered clay and layered kerogen, the satisfactory results shown in Fig. 4 are obtained. This adjustment is a confirmation that our modelling procedure is efficient for shale rock physics modelling
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