Abstract

In situ fractionation in shales means differential movement of the light versus heavy components of the crude oil in the shale formation. This can be due to multiple phenomenon like molecular sieving, varying diffusion coefficients for different hydrocarbon components and multi-component adsorption all acting simultaneously. Many companies have reported change in composition of produced fluid with time. Insitu fractionation is important because it has strong implications on EOR, both selecting the timing of EOR, and the solvent for EOR. Additionally, simulators for history matching, prediction and optimizing well spacing, must account for this effect. Earlier studies have proved the occurrence of the insitu fractionation both experimentally using GC-MS (gas chromatography and mass spectrometry) and theoretically using molecular dynamic simulations. However, cores are available in limited number of wells and, tools and measurements required to understand insitu fractionation are both time consuming and very expensive. We have found that dry pyrolysis can be used to effectively study insitu fractionation, the advantage being it is cheap and fast. The same experiment can be used to calculate effective diffusion coefficient and tortuosity. The study was done on samples from Berea sandstone, and Eagle Ford and Wolfcamp shales covering a wide range of petrophysical properties. The point source solution of the diffusivity equation was used to back out the effective diffusion coefficients. The effective diffusion coefficients determined for Berea, Wolfcamp and Eagle Ford samples were 5.38E-11 m2/s, 2.61E-11 m2/s and 5.35E-12 m2/s, respectively. These coefficients were then used to calculate the tortuosity of the samples which were validated by the resistivity measurements. The tortuosity values for the Berea, Wolfcamp and Eagle Ford samples were determined to be 3.1, 3.4 and 7.1, respectively. Tortuosity and diffusion coefficients are of paramount importance especially given the fact that permeability measurements in shales are unreliable and Knudsen diffusion and ordinary diffusion have to be integrated with Darcy flow to model production behavior in shales.

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