Halal transportation services is one of the crucial components of producing Halal products. Since Halal is unique and involves elaborate regulations and executions, therefore it requires huge investment. Like any other supply chain, the transportation cost will be transferred to the end users, normally the customers, thus increasing the price of final products. It is notably common to find studies done on Muslim customers and their preference on Halal products, however, studies on Muslims preferences towards Halal transportation could still be considered as novel. By adopting the Theory of Planned Behavior and religiosity; and by taking into account the moderating effect of knowledge, this study aims to identify the factors that lead to the customers’ willingness to pay for the Halal transportation cost. Using a purposive sampling method, the data was collected among Muslim consumers in a prominent shopping complex in Malaysia and was analyzed using Smart Partial Least Squares (PLS). Based on the finding, it is shown that the attitude and perceived behavioral control gave a positive relationship with the willingness to pay for Halal transportation. Meanwhile, subjective norm and religiosity were on the opposite as there were both hold an insignificant effect towards the willingness to pay for the Halal transportation. Knowledge has moderated the relationship between attitude and willingness to pay for Halal transportation, but not for the relationship between subjective norm and perceived behavioral control. It is expected that this study could provide a better understanding of Muslim consumers’ behavior on purchasing for Halal transportation, as well as other Halal supply chain activities.

The integrated approach to sand management is crucial to address the sanding risk in the producers and injectors in the North Sea mature field. The concepts incorporates the LEAN approach and developed with major focus on the rehabilitation of mature fields where each barrel of oil counts and uncertainty, both technical and economical, are becoming more challenging at industry level. High decline in productivity and increased operational challenges are common issues for mature fields.The sand management is divided into 4 major live phases which are sand prediction, sand prevention, sand production and evaluation/feedback. Each stage is mapped and associated with field redevelopment plan, project management control level, the time cycle (short: operation efficiency, medium: production optimization and long: reservoir management), digital oilfield, roles and responsibilities, enabling technologies and fine-tuned workflows.History case including the utilization of dynamic multiphase flow simulator to fully understand the water hammer sanding behavior and the remedial job enabling technologies will be discussed briefly to demonstrate the utilization of the integrated sand management approach.The paper will also highlight the key challenges to ensure that the sand management is a continuous improvement effort that is suitable for high level planning and yet practical for day to day operation.The sand management has been developed based on multidisciplinary approach, lessons learnt and best practices acquired in mature field rehabilitation projects with major consideration to maximize the recoverable reserves and optimize the matured asset added value creation.

The deposition of carbonate and sulphate scales is a major problem during oil and gas production. Managing scale with chemical application methods involving either scale prevention and/or removal are the preferred methods of maintaining well production. However, chemical scale control is not always an option, depending upon the nature of the reservoir and well completion and, in cases of severe scaling, the problem can render chemical treatments uneconomic unless other non-chemical methods are utilised. A variety of non-chemical scale control methods exist, the most common being injection of low salinity brines or low sulphate seawater (LSSW) using reverse osmosis and a sulphate removal plant (SRP) respectively. In addition, careful mixing of lift gas, produced waters and reinjection, coatings, smart well completions with active inflow control devices (ICD) and sliding sleeves (SS) are other methods. All of these techniques, including combinations thereof, are currently in use and the advantages and disadvantages of the key techniques are compared to chemical methods for both carbonate and sulphate scale control. A detailed example from a North Sea field demonstrates where downhole chemical scale control has not been required through a strategy of careful mixing of lift gas, brines and produced water re-injection. This was combined with understanding fluid flow paths in the reservoir and their likely breakthrough at production wells. Consideration is given to the injection of smart brines to scale deep in the reservoir, and data from North Sea chalk fields shows how "in situ" geochemical reactions between the reservoir and the injected fluid can precipitate sulphate scales. The necessity to understand these geochemical reactions and their implications for improved oil recovery and the design of smart injection brines for scale control are discussed. This paper presents a comprehensive review of non-chemical methods for downhole scale control and discusses how the use of these techniques can provide alternative scale management strategies through minimising or alleviating the need for downhole chemical treatments.

The Reserve Technical Potential Management System (RTPMS) is divided into 5 main stages and associated together with the Petroleum Reserve Management System by SPE. The main aim by merging these two concepts is to improve understanding of the reserves pool and therefore provide a practical guideline on a standard definition for high level planning and day-to-day operations. The concept is being developed with major focus on the rehabilitation of mature fields where each barrel of oil counts and uncertainty, both technical and economical, are becoming more challenging at industry level. High decline in productivity and increased operational challenges are common issues for mature fields. Recurrently, lower recovery factors are mainly driven by reservoir characterization uncertainty and management, geological complexity, limited resources and operational efficiency. This paper addresses some of these challenges in an integrated manner. Each stage is mapped and associated with the SPE Petroleum Reserve Management System, the project management control level, the time cycle (short: operation efficiency, medium : production optimization and long: reservoir management), a digital oilfield concept, the roles and responsibilities of the stakeholders, the technology groups and their key technologies. The five stages are defined as; 1) Actual Potential, 2) Operational Technical Potential, 3) Constrained Technical Potential, 4) Theoretical Technical Potential and 5) Ultimate Technical Potential. The concept has been developed based on lessons learnt and best practices acquired in mature field rehabilitation projects.

This integrated management system is design to efficiently manage and optimize the production excellence opportunities portfolio especially in mature field where higher risk presence technically and economically. Project management, LEAN process, lesson learnt and best practices were incorporated in developing the standardized workflow. The portfolio optimization model provides comprehensives technical and economical evaluation.The technical success probability sub-model incorporates the technical KPIs and the project criticality index to generate project level probability. At this level, due to lack of local experience, the outcome can be either optimistic or pessimistic. To prevent this and recognizing the similar technology has been utilized elsewhere to solve similar problem, the industry track record can be combine with local perception via Bayes' Theorem to generate more realistic probability. The potential way forward is to incorporate the sub-model with case based reasoning and Bayes network for a more robust decision and evaluation.The economic sub-model combined with project schedule incorporates probabilistic assumption to the benefit for each technology, hydrocarbon price, cost and time. The portfolio optimization risk-gain model incorporated both the forecast results from technical and economical sub-models to optimize the new technology portfolio. The model will run 1000 iterations to achieve the objective by maximizing the P50 NPV (net present value) of the project but within the predefined constrained and acceptable risk. The optimization results will be further undergo multidisciplinary peer review prior continuing the standardize workflow.The management system is currently used in mature field project in North Sea to efficiently identify, manage, optimized the opportunities portfolio, and has demonstrated good execution and success cases.