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While the prediction of spatial distribution of potential landslide occurrences is a primary interest in landslide hazard mitigation, it remains a challenging task. To overcome the scarceness of complete, sufficiently detailed geomorphological attributes and environmental conditions, various machine-learning techniques are increasingly applied to effectively map landslide susceptibility for large regions. Nevertheless, limited review papers are devoted to this field, particularly on the various domain specific applications of machine learning techniques. Available literature often report relatively good predictive performance, however, papers discussing the limitations of each approaches are quite uncommon. The foremost aim of this paper is to narrow these gaps in literature and to review up-to-date machine learning and ensemble learning techniques applied in landslide susceptibility mapping. It provides new readers an introductory understanding on the subject matter and researchers a contemporary review ...

Decommissioning of offshore structures is not a novel issue in the oil and gas industry. Malaysia is now dealing with a fleet of ageing platforms slated to be decommissioned. There are several alternatives of decommissioning such as “complete removal” and conversion to artificial reefs; “partial removal”, “remote reefing” and “topple in-situ”. Given the list of options, the decision to undertake the best option is challenging as the current method of comparative Best Practicable Environmental Option (BPEO) assessment is only implemented at the end of platform’s life. Therefore, the main goal is to develop a management decision making tool which is incorporated throughout the life cycle of an oil field. Expert elicitation is conducted to verify the relevant decommissioning criteria. The criteria were then ranked accordingly through calculation of Relative Importance Index (RII), and a conceptual system is established to complement the existing asset management system. In summary, this study could benefit the knowledge of offshore decommissioning planning through prioritization of decommissioning criteria.

For many of the offshore jacket structures in Malaysia, their design lives of 25–30 years is approaching the end, signifying the urgent implementation of decommissioning efforts. While current regulatory guidelines strongly recommend complete removal of the structures, in view of sustainability issues, other options of decommissioning should not be overlooked. As a way forward, this paper suggests an approach of reusing offshore jacket platforms as an opportunity to derive economic and/or scientific benefits. To utilize a structure beyond its design life, a thorough control of the structural safety must be executed. Integrating a risk-based structural assessment, weighting factors and the concept of hazard functions, the approach gauges the failure probabilities and risk events involved in the reusing of redundant offshore platforms. The principles of a risk-based structural assessment are thus described and the proposed conceptual framework is illustrated, linking the operational and structural risks in connection with reusing of an offshore jacket structure. This semi-probabilistic support system (Semi-PSS) provides a valuable outline in improving the selection of appropriate platforms to be refurbished and transformed into livable hubs.