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This paper presents a quantitative characterisation of the fracture openings obtained in triaxial shear tests on several cement mortar samples. The comparison was carried out on three samples with various apertures using different methods of semi-destructive and non-destructive characterisation: optical microscopy, scanning electron microscopy, X-ray computed tomography, digital volume correlation and the 14C-polymethylmethacrylate method. The fracture aperture distribution results are in good agreement between the different methods. Although the opening results obtained are comparable, the most advantageous method was considered to be XRCT profile analysis based on the size of the target area studied and the specific characteristics of each technique. [ABSTRACT FROM AUTHOR]

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The feedforward backpropagation technique provides a model-free estimation with neural networks. The algorithm was used to estimate fracture aperture of natural fractures in three dimensional space. A three-layer neural network with at least 5 nodes in a hidden layer was trained on a data set consisting of formation imaging microscanner logs ( FMS) from horizontal boreholes. Sensitivity studies were performed to account for the rate of learning convergence, convergence to local error minima, etc. Among the factors contributing mostly to the overall good or bad performance of the network, the following are worth mentioning: number of data points, data spacing, and data variability. It is shown that a smoothing operation applied to aperture data along the wellbore often helps to reduce 'disorientation' of the network and to switch from oscillations or chaotic 'jumps' to convergence. [ABSTRACT FROM AUTHOR]