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During the 2004 Sediment Acoustic eXperiment (SAX04), values of sediment pore properties in a littoral sand deposit were determined from diver-collected cores using traditional methods and image analysis on X-ray microfocus computed tomography (XMCT) images. Geoacoustically relevant pore-space properties of sediment porosity, permeability, and tortuosity were evaluated at scales ranging from the pore scale to the core scale from "mud-free" sediments collected within the 0.07-km2 study area. Porosity was determined from water-weight-loss measurements to range from 0.367 to 0.369, from 2-D image analysis to range from 0.392 to 0.436 and from 3-D image analysis to range from 0.386 to 0.427., Pub. in IEEE Journal of Oceanic Engineering, v35 n3 p488-501, Jul 2010.

X-ray computed microtomography (XMT) is used for high-resolution, nondestructive imaging and has been applied successfully to geologic media. Despite the potential of XMT to aid in formation evaluation, currently it is used mostly as a research tool. One factor preventing more widespread application of XMT technology is limited accessibility to microtomography beamlines. Another factor is that computational tools for quantitative image analysis have not kept pace with the imaging technology itself. In this paper, we present a new grain-based algorithm used for network generation. The algorithm differs from other approaches because it uses the granular structure of the material as a template for creating the pore network rather than operating on the voxel set directly. With this algorithm, several advantages emerge: the algorithm is significantly faster computationally, less dependent on image resolution, and the network structure is tied to the fundamental granular structure of the material. In this paper, we present extensive validation of the algorithm using computer-generated packings. These analyses provide guidance on issues such as accuracy and voxel resolution. The algorithm is applied to two sandstone samples taken from different facies of the Frontier Formation in Wyoming, USA, and imaged using synchrotron XMT. Morphologic and flow-modeling results are presented., Supported in part by US Dept. of Energy. Presented at the Society of Petroleum Engineers (SPE) Annual Technical Conference and Exhibition held in Dallas, TX on 9-12 Oct 2005. Published in the proceedings of the SPE Annual Technical Conference as paper no. 95887, 2005. Prepared in collaboration with Louisiana State Univ., Baton Rouge, LA, University of Walkato, New Zealand, University of Houston, TX and Naval Reseach Lab, Washington, DC.

Packing of granular media is an extremely important determinant in reservoir rock evolution, sound speed propagation, fluid flow and sediment compressibility. X-ray microfocus computed tomography (XMCT) images with high-resolution were evaluated using a grain-based algorithm that quantifies discrete components and bulk properties of sedimentary systems at different states of compaction or at approximately minimum and maximum packing densities. Angularity of these sands ranges from rounded to subrounded to subangular. Network permeability compares reasonably well to measured values; grain aspect ratios and coordination number are reasonable for sands. The grain-based algorithm provides a robust and efficient capability., Presented at the International Workshop on X-Ray CT for Geomaterials (GeoX 2006) (2nd), held in Grenoble and Aussois, France, on 4-7 Oct 2006. Published in the Proceedings of GeoX 2006, p264-268, 2006. Prepared in collaboration with Louisiana State University, Baton Rouge, LA. The original document contains color images.

X-ray computed microtomography (XMT) is used for high-resolution, non-destructive imaging and has been applied successfully to geologic media. Despite the potential of XMT to aid in formation evaluation, currently it is used mostly as a research tool. One factor preventing more widespread application of XMT technology is limited accessibility to microtomography beamlines. Another factor is that computational tools for quantitative image analysis have not kept pace with the imaging technology itself. In this paper, we present a new grain-based algorithm used for computer reconstruction and analysis of granular materials and subsequent network generation. The algorithm differs significantly from other methods because the first step is to extract the fundamental granular structure from a 3D data set, which provides a wealth of information such as grain sizes, aspect ratios, orientations, surface areas, etc. Knowledge of the basic granular structure serves as a foundation for characterizing the void morphology and creating physically representative pore networks. The algorithm is applied to a sample of sandstone from the Frontier Formation in Wyoming, USA, which was imaged using Synchrotron microtomography. Morphologic and flow-modeling results are presented., Presented at the Society of Petroleum Engineers (SPE) Annual Technical Conference and Exhibition held in Dallas, TX, on 9-12 Oct 2005. Published in the Proceedings of the SPE Annual Technical Conference as paper no. 95887, 2005. Prepared in collaboration with Louisiana State University, Baton Rouge, LA; University of Waikato, New Zealand; and University of Houston, TX. The original document contains color images.