Implication of heterogeneities on core porosity measurements

Heterogeneities within core samples affect the accuracy of the laboratory measured core plug interconnected porosity. The laboratory measures the volume averaged porosity of the interconnected pores, <ϕm>. For homogeneous cores this is the correct porosity ± any experimental error. However for heterogeneous cores when any embedded material (unknown or ignored) has a differing porosity, ϕi, to that of the containing outer shell, ϕo, there will be increased uncertainty. We show that the difference between the measured volume averaged porosity, <ϕm>, and the porosity of the outer shell of the core, ϕo can be quantified by our Heterogeneity Factor, H. H is defined as (<ϕm> - ϕo)/ϕo and given by H = F(R-1), where F is the ratio of the bulk volume of the embedded material to the total core bulk volume (measured), VBi/VBm, and R is the ratio of the embedded and the host outer porosity, ϕi/ϕo. The core plug homogeneous model can create increased error bounds in porosity for heterogeneous plugs.

When H is zero there is no error in the porosity measurement due to heterogeneity, but when H≠ 0 then the differences can be significant and increases the experimental error bound. We present graphs for relevant industry scenarios to demonstrate the effect of any inclusions in the measured porosity. We find that when F is ∼0.1 i.e., inner included porosity is 10% of bulk volume, the relative error between <ϕm> and ϕo can reach ∼30% and even larger differences when F > 0.1. We then give a real example from a faulted vuggy outcrop carbonate which demonstrates extra porosity uncertainties, even for a very small vug. Finally we discuss the possible effect of embedded clay intrusions emitting adsorbed gas on grain/pore volume determinations of porosity using gas expansion, a common laboratory method of porosity determination.

Appreciation of core heterogeneity on the precision of the laboratory porosity measurements is essential to improve the confidence in the error bounds for the quality control of laboratory core porosity measurements, and of the porosity distribution frequency for inputs to statistical methods such as Monte Carlo analysis for oil-in-place estimations, STOIIP.