Automatic feature detection and interpretation in borehole data

Detailed characterisation of the structure of subsurface fractures is greatly facilitated by digital borehole logging instruments, however, the interpretation of which is typically time-consuming and labour-intensive. Despite recent advances towards autonomy and automation, the final interpretation remains heavily dependent on the skill, experience, alertness and consistency of a human operator. Existing computational tools fail to detect layers between rocks that do not exhibit distinct fracture boundaries, and often struggle characterising cross-cutting layers and partial fractures. This research proposes a novel approach to the characterisation of planar rock discontinuities from digital images of borehole logs by using visual texture segmentation and pattern recognition techniques with an iterative adaptation of the Hough transform. This approach has successfully detected non-distinct, partial, distorted and steep fractures and layers in a fully automated fashion and at a relatively low computational cost. Borehole geometry or breakouts (e.g.borehole wall elongation or compression) and imaging tool decentralisation problem affect fracture characterisation and the quality of extracted geological parameters. This research presents a novel approach to the characterisation of distorted fracture in deformed borehole geometry by using least square ellipse fitting and modified Hough transform. This approach approach has successfully detected distorted fractures in deformed borehole geometry using simulated data. To increase the fracture detection accuracy, this research uses multi-sensor data combination by combining extracted edges from different borehole data. This approach has successfully increased true positive detection rate. Performance of the developed algorithms and the results of their application have been promising in terms of speed, accuracy and consistency when compared to manual interpretation by an expert operator. It is highly anticipated that the findings of this research will increase significantly the reliance on automatic interpretation

Automatic Fracture Orientation Extraction from SfM Point Clouds

Geology seeks to understand the history of the Earth and its surface processes through charac- terisation of surface formations and rock units. Chief among the geologists’ tools are rock unit orientation measurements, such as Strike, Dip and Dip Direction. These allow an understanding of both surface and sub-structure on both the local and macro scale. Although the way these techniques can be used to characterise geology are well understood, the need to collect these measurements by hand adds time and expense to the work of the geologist, precludes spontaneity in field work, and coverage is limited to where the geologist can physically reach. In robotics and computer vision, multi-view geometry techniques such as Structure from Motion (SfM) allows reconstructions of objects and scenes using multiple camera views. SfM-based techniques provide advantages over Lidar-type techniques, in areas such as cost and flexibility of use in more varied environmental conditions, while sacrificing extreme levels of fidelity. Regardless of this, camera based techniques such as SfM, have developed to the point where accuracy is possible in the decimetre range. Here is presented a system to automate the measurement of Strike, Dip and Dip Direction using multi-view geometry from video. Rather than deriving measurements using a method applied to the images, such as the Hough Transform, this method takes measurements directly from the software generated point cloud. Point cloud noise is mitigated using a Mahalanobis distance implementation. Significant structure is characterised using a k-nearest neighbour region growing algorithm, and final surface orientations are quantified using the plane, and normal direction cosines

Automated calibration of multi-sensor optical shape measurement system

A multi-sensor optical shape measurement system (SMS) based on the fringe projection method and temporal phase unwrapping has recently been commercialised as a result of its easy implementation, computer control using a spatial light modulator, and fast full-field measurement. The main advantage of a multi-sensor SMS is the ability to make measurements for 360° coverage without the requirement for mounting the measured component on translation and/or rotation stages. However, for greater acceptance in industry, issues relating to a user-friendly calibration of the multi-sensor SMS in an industrial environment for presentation of the measured data in a single coordinate system need to be addressed. The calibration of multi-sensor SMSs typically requires a calibration artefact, which consequently leads to significant user input for the processing of calibration data, in order to obtain the respective sensor's optimal imaging geometry parameters. The imaging geometry parameters provide a mapping from the acquired shape data to real world Cartesian coordinates. However, the process of obtaining optimal sensor imaging geometry parameters (which involves a nonlinear numerical optimization process known as bundle adjustment), requires labelling regions within each point cloud as belonging to known features of the calibration artefact. This thesis describes an automated calibration procedure which ensures that calibration data is processed through automated feature detection of the calibration artefact, artefact pose estimation, automated control point selection, and finally bundle adjustment itself. [Continues.

Comparing manual and remote sensing field discontinuity collection used in kinematic stability assessment of failed rock slopes

Este artículo propone una metodología de reconstrucción de superficies mediante SfM-MVS a partir de fotogragrafías y puntos de control replanteados con pequeños puntos de plastilina, posicionados en el talud mediante brújula.This work was supported by the University of Alicante, within the framework of project GRE14-04. Additional funding was obtained from the Spanish Government, project number TIN2014-55413-C2-2-P

Nanoscale geochemistry and geochronology of xenotime: application to Earth sciences

The PhD project titled ‘Nanoscale geochemistry and geochronology of xenotime: application to Earth sciences’ aims at identifying and understanding mineralogical mechanisms that impact geochronometers at the nanoscale. The project focuses on the nanoscale geochemical behaviour of xenotime and their implications in geochronology, using a multi-scale study approach. The thesis presents nanogeochronology method of xenotime dating using atom probe tomography and detailed case studies of xenotime from three different geological conditions

Development and application of atom probe tomography to complex zircon grains

Atom probe tomography (APT) is used to characterise the nanoscale geochemistry of complex zircon grains from different environments. New applications of APT to meteoritic, shocked and hydrothermal zircon grains are developed. The results of this project provide a new understanding of trace element modification of zircon and provides a framework for future investigations of the nanoscale geochemical and geochronological analysis of other minerals

Mechanisms of fatigue crack nucleation near non-metallic inclusions in Ni-based superalloys

Ni-based superalloys used for turbine discs are typically produced via powder metallurgy, a process which introduces undesirable non-metallic inclusions. Inclusions can be regarded as fatigue crack nucleation hot-spots due to their differing mechanical properties compared with the matrix they are embedded in. In this thesis, a series of models and experiments were used to investigate the mechanistic drivers of fatigue crack nucleation in the vicinity of non-metallic inclusions. The drivers of decohesion and fracture of inclusions, often precursors to crack nucleation, were found to be the normal stress acting on the interface and the inclusion maximum principal stress, respectively. Exact values of either criterion were found using a cohesive zone model in a crystal plasticity finite element (CPFE) model faithfully representative of a real microstructure under low cycle fatigue. Decohesion and inclusion fracture were contrasted against slip-driven nucleation by a stored energy criterion. The key finding here was that decohesion and inclusion fracture marginally reduce fatigue life. The comparative fatigue performance of an inclusion, a twin boundary and a triple-junction were studied in a synthetic CPFE microstructure. The inclusion recorded a significantly lower fatigue life compared with the intrinsic microstructural features. Various hardening models were used to investigate cyclic decohesion in a stress-controlled regime. Under no hardening model was cyclic decohesion predicted, strongly suggesting that decohesion is purely a function of applied stress within the first cycle. A discontinuity tolerant digital image correlation algorithm was developed to study fatigue crack nucleation near a non-metallic agglomerate at 300°C. Decohesion and fracture of inclusions occurred already within the first cycle of loading. Microcracks nucleated throughout the inclusion agglomerate after 6000 cycles. In addition, a fatigue crack nucleated adjacent a twin boundary in a coarse grain neighbouring the agglomerate. A high (angular) resolution electron backscatter diffraction (HR-EBSD) analysis and a discrete dislocation plasticity (DDP) model suggested that strong build-up of GNDs and slip near twin boundary owes to the elastic anisotropy of twin and parent.Open Acces