[1] The vadose zone of the Miami limestone is capable of draining several centimeters of rainfall within a fraction of an hour. Once the water enters the ground, little is known about the flow paths in the oolitic rock. A new rotary laser-positioned ground-penetrating radar (GPR) system enables centimeter-precise and rapid acquisition of time-lapse surveys in the field. Two-dimensional (2-D) GPR time-lapse surveying at a 3-min interval before, during, and after rainfall shows how buried sand-filled dissolution sinks efficiently drain the bulk of the rainwater. Hourly repeated 3-D imaging of a dissolution sink in response to surface infiltration shows how the wetting front propagates at a rate of 0.6-1.2 m/h traversing the 5-m-thick vadose zone within hours. At the same time, some of the water migrates laterally into the host rock guided by stratigraphic unit boundaries. Average lateral propagation measured over a 28-hour period was of the order of 0.1 m/h. On a seasonal time frame, redistribution involves the entire rock volume. Comparing 3-D surveys acquired after wet summer and dry winter conditions shows good GPR event correspondence, but also time shifts up to 20 ns caused by the change of overall water content within the vadose zone. High-precision time-lapse GPR imaging can therefore be used to noninvasively characterize natural drainage inside the vadose zone ranging from transient loading to seasonal variation.

Characterizing the pore space of rock samples using three‐dimensional (3D) X‐ray computed tomography images is a crucial step in digital rock physics. Indeed, the quality of the pore network extracted has a high impact on the prediction of rock properties such as porosity, permeability and elastic moduli. In carbonate rocks, it is usually very difficult to find a single image resolution which fully captures the sample pore network because of the heterogeneities existing at different scales. Hence, to overcome this limitation a multiscale analysis of the pore space may be needed. In this paper, we present a method to estimate porosity and elastic properties of clean carbonate (without clay content) samples from 3D X‐ray microtomography images at multiple resolutions. We perform a three‐phase segmentation to separate grains, pores and unresolved porous phase using 19 μm resolution images of each core plug. Then, we use images with higher resolution (between 0.3 and 2 μm) of microplugs extracted from the core plug samples. These subsets of images are assumed to be representative of the unresolved phase. We estimate the porosity and elastic properties of each sample by extrapolating the microplug properties to the whole unresolved phase. In addition, we compute the absolute permeability using the lattice Boltzmann method on the microplug images due to the low resolution of the core plug images. In order to validate the results of the numerical simulations, we compare our results with available laboratory measurements at the core plug scale. Porosity average simulations for the eight samples agree within 13%. Permeability numerical predictions provide realistic values in the range of experimental data but with a higher relative error. Finally, elastic moduli show the highest disagreements, with simulation error values exceeding 150% for three samples.

Abstract. Pore spaces heterogeneity in carbonates rocks has long been identified as an important factor impacting reservoir productivity. In this paper, we study the heterogeneity of carbonate rocks pore spaces based on the image analysis of scanning electron microscopy (SEM) data acquired at various magnifications. Sixty images of twelve carbonate samples from a reservoir in the Middle East were analyzed. First, pore spaces were extracted from SEM images using a segmentation technique based on watershed algorithm. Pores geometries revealed a multifractal behavior at various magnifications from 800x to 12 000x. In addition, the singularity spectrum provided quantitative values that describe the degree of heterogeneity in the carbonates samples. Moreover, for the majority of the analyzed samples, we found low variations (around 5 %) in the multifractal dimensions for magnifications between 1700x and 12 000x. Finally, these results demonstrate that multifractal analysis could be an appropriate tool for characterizing quantitatively the heterogeneity of carbonate pore spaces geometries. However, our findings show that magnification has an impact on multifractal dimensions, revealing the limit of applicability of multifractal descriptions for these natural structures.

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