Layer | Fill | Outline |
---|
Map layers
Theme | Visible | Selectable | Appearance | Zoom Range (now: 0) |
---|
Fill | Stroke |
---|---|
Collaborating Authors
SGB
ABSTRACT The radial basis function link network (RBFLN) machine learning method is a neural network technique that has gained favor in the mineral exploration realm for its robustness and ability to discriminate between deposits and non-deposits. As mineral deposit targets become deeper and harder to find, spatial data modelling and machine learning techniques that help to predict regions that hold potential for new deposits are sought. The identification of new mineral deposits becomes possible with greater understanding of the mineral systems that were involved in the deposition of mineral deposits. The Swayze greenstone belt hosts a few low-grade high-tonnage deposits and reviewing the mappable criteria that resulted in gold mineralization could help in the discovery of new drill targets and possibly new mineral deposits. Using geological, geochemical, structural and geophysical datasets that are markers for processes that led to gold deposition and proxies to mineralization, RBFLN can make predictions to produce mineral prospectivity maps. Receiver operator characteristic (ROC) curves are used to evaluate the sensitivity and specificity of predictive models. Overall, RBFLN shows an area under curve of 0.88 and an efficiency of classification of 83%. The results show that RBFLN was successful at delineating new areas for more detailed exploration. Presentation Date: Wednesday, October 17, 2018 Start Time: 1:50:00 PM Location: 213B (Anaheim Convention Center) Presentation Type: Oral
ABSTRACT Mineral deposits are becoming increasingly difficult to locate; thus, new methods are required to locate undiscovered deposits in both greenfield and brownfield exploration areas. Mineral prospectivity mapping (also known as mineral potential mapping) is a method for determining locations where a mineral deposit is more likely to occur in a study area. This is achieved using geographical information systems (GIS) to help overlay and integrate multiple geoscience datasets in the study area; then, knowledge-driven, and data-driven mathematical tools, such as weights-of-evidence, artificial neural networks, logistics regression and fuzzy logic are used to determine their spatial relationships with already known mineral occurrences to produce the mineral prospectivity maps. The geoscience datasets include geochemical, geophysical, structural, satellite remote sensing and geological datasets. The area selected for our study is the Swayze Greenstone Belt (SGB) in Ontario, Canada. The results for part 1 of the study, from integrating geology, geochemistry and structural data and using the weights-of-evidence tool shows that both known and potential mineral deposits can be predicted with a small number of training points and evidential layers. Presentation Date: Wednesday, September 27, 2017 Start Time: 4:20 PM Location: 360C Presentation Type: ORAL
- Research Report (0.96)
- Overview > Innovation (0.48)
- Geology > Mineral (1.00)
- Geology > Geological Subdiscipline > Geochemistry (1.00)
- Geophysics > Seismic Surveying (0.48)
- Geophysics > Electromagnetic Surveying (0.36)
- Materials (0.69)
- Energy > Oil & Gas > Upstream (0.50)
- Government > Regional Government > North America Government (0.48)
- Data Science & Engineering Analytics > Information Management and Systems > Artificial intelligence (0.90)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (0.71)
- Reservoir Description and Dynamics > Fluid Characterization > Geochemical characterization (0.68)
- Data Science & Engineering Analytics > Information Management and Systems > Neural networks (0.56)
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (0.56)
- Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning (0.48)
- Information Technology > Artificial Intelligence > Representation & Reasoning > Uncertainty > Fuzzy Logic (0.36)
ABSTRACT INTRODUCTION Stress corrosion cracking (SCC) test specimens of Al-LiCu alloy that were subjected to fixed-displacement loading and exposed to aerated 3.5 wt% sodium chloride (NaCl) solution for 1 week failed<24 h after removal into ambient atmospheres. Anodic dissolution-based mechanisms proposed previously for this phenomenon were amended based upon further characterization of the rapid cracking process. Amendments were based on studies of the relative electrochemical behavior of the microstructural elements in the subgrain boundary (SGB) region, time-tofailure SCC testing in a simulated crack solution, evolution of crack potential and pH with time, fractographic examination of failed samples, and x-ray diffraction (XRD) of films passivating Crack walls. Results suggested an active path existed along SGB that was composed of the highly reactive T1 (Al2CuLi) precipitate phase and a solutedepleted zone that did not passivate readily when exposed to the crack environment. The matrix phase along crack walls appeared to passivate in the crack environment, thereby confining attack to the SGB region. This active path was enabled when cracks were isolated from a bulk environment, but it was disabled otherwise. Potential and pH conditions required for cracking were reviewed, along with the formation of a hydrotalcite, Li2[Al2(OH)6]2·CO3·3H2O,
- Materials > Metals & Mining (1.00)
- Energy > Oil & Gas > Upstream (1.00)
- Well Completion > Well Integrity > Subsurface corrosion (tubing, casing, completion equipment, conductor) (1.00)
- Reservoir Description and Dynamics (1.00)
- Facilities Design, Construction and Operation > Pipelines, Flowlines and Risers > Materials and corrosion (1.00)
- Production and Well Operations > Production Chemistry, Metallurgy and Biology > Corrosion inhibition and management (including H2S and CO2) (0.88)
ABSTRACT Stress corrosion (SC) behavior of the alloy 2090-T83 (UNS A92090) was evaluated in artificial seawater (ASW) under constant immersion. For comparison, some tests were performed in a 3.5 wt% NaCl solution, and, as a reference, the cracking behavior was also studied in N2 gas. Smooth specimens machined from a 4-mm thick sheet were tested in the longitudinal and in the long transverse direction using the constant-load and the slow strain rate (SSR) techniques. Both methods suggested that the alloy was susceptible to stress corrosion cracking (SCC), ASW being a much more aggressive solution for SCC than the NaCl solution. The SCC mechanism was studied using the SSR method. The effects of strain rate, deaeration of the solution, or electrode potential were examined. During SSR testing, either the corrosion potential or the current at constant potential was monitored. The fractured specimens were examined in a scanning electron microscope (SEM) equipped with a backscatter electron detector and an energy dispersive x-ray analysis system to distinguish various local cracking and corrosion morphologies. SEM and a transmission electron microscope were used for characterizing the microstructure of the alloy. The experimental observations suggest that SCC of 2090-T83 in ASW is a result of local anodic dissolution along subgrain boundaries and is primarily induced by the preferential dissolution of T1 (Al2CuLi) precipitates. Al6(Fe,Cu) constituents played a minor role in the SCC process. INTRODUCTION Alloy 2090 (UNS(1) A92090) in the near peak-aged (PA) temper is meant to replace the high-strength alloy 7075-T651 (UNS A97075), currently used in aircraft structures, with 8% reduction in density and 10% increase in elastic modulus.1 For a successful application of the 2090 alloy, a basic knowledge is required of the combined effect of an aggressive environment and a (tensile) stress on the durability performance, manifesting itself as stress corrosion cracking (SCC). Previous investigators2-6 have evaluated the influence of aging, resulting in different microstructures, on the stress corrosion (SC) resistance in aqueous NaCl solutions. The alloy in the near PA condition appeared to be highly resistant to SCC compared to 7075-T651. The longitudinal (L) and long transverse (LT) directions were virtually immune. At the same time, the SC susceptibility in the near PA temper was influenced by small variations in fabrication procedures,6 which controlled the microstructural features. In NaCl solutions, two models for the mechanism of SCC in the Al-Li-Cu-(Zr) alloys were proposed, namely hydrogen-induced embrittlement (HE)7,8 and film rupture local-anodic dissolution (LAD).4,6,9 The HE model postulates that atomic hydrogen is absorbed and somehow weakens the material, allowing cracking. Hydrogen entry could occur only when the passive oxide film was unstable7,8 and was enhanced
- Europe (1.00)
- North America > United States > Pennsylvania (0.46)
- Materials > Metals & Mining (1.00)
- Energy > Oil & Gas > Upstream (1.00)
- Well Completion > Well Integrity > Subsurface corrosion (tubing, casing, completion equipment, conductor) (1.00)
- Production and Well Operations > Production Chemistry, Metallurgy and Biology > Corrosion inhibition and management (including H2S and CO2) (1.00)
- Facilities Design, Construction and Operation > Pipelines, Flowlines and Risers > Materials and corrosion (1.00)
- Well Completion > Hydraulic Fracturing (0.94)