Unsettled Aspects of Insourcing and Outsourcing Additive Manufacturing

Additive manufacturing (AM), also known as “3D printing,” has transitioned from concepts and prototypes to part-for-part substitution—and now to the creation of part geometries that can only be made using AM. As a wide range of mobility OEMs begin to introduce AM parts into their products, the question between insourcing and outsourcing the manufacturing of AM parts has surfaced. Just like parts made using other technologies, AM parts can require significant post-processing operations. Therefore, as AM supply chains begin to develop, the sourcing of AM part building and their post-processing becomes an unsettled and important issue. Unsettled Aspects of Insourcing and Outsourcing Additive Manufacturing discusses the approaches and trade-offs of the different sourcing options for production hardware for multiple scenarios, including both metallic and polymer technologies and components.

Digital Field Development Planning: A Collaboration Between Technology & Process to Enable Fast and Efficient Field Development Planning

O&G industry is facing difficult business climate with many uncertainties and challenges. Companies including National Oil Companies, NOCs have to be more efficient particularly in developing fields. The challenge is to create an environment to allow E&P companies to efficiently optimize their Field Development Plan, FDP processes and align with technology that enables integration & collaboration between different E&P domains. The environment should be agile to allow changing of circumstances while providing in-depth understanding of the risks and uncertainties involved. PETRONAS has a large portfolio of domestic and international oil & gas assets and is one of the leading NOCs in the world. With the ongoing potential of uncertainty of oil price, it is even more important to fast track field development planning while understanding the risk across domains and recognizing value from investments. PETRONAS has embarked on a digital field development pilot project called Live FDP that enriches internal existing FDP processes & tools to provide integration and generate efficiencies across multi-discipline in E&P workflows and systems that leverage on capabilities enabled by a Digital Cloud based solution. The Digital Planning Application methodology starts with Project Orchestration: Building FDPs using multi-disciplinary inputs and sensitivities followed by managing and framing via capturing an opportunity framework and concept decision. The process will then lead to generating multiple scenarios and evaluations for development options via seamless connectivity and integration with other systems in an Open Platform. At this point, process automation via connectivity of technical domain inputs to Value Based Decision Making will take place alongside Data Discovery & Benchmarks, underpinned by insights, Optimization & Advisory. The Data Analytics will then enable powerful business intelligence & analytics reporting capabilities translated into a Digital Dashboard: alignment with the UPMS process and management systems. Such systems allow project maturation to be completed fast and thus future scalability with expansion apart from Development phase to other phases such as Exploration, Drilling, Facility & Business Planning Workflows can be implemented. Based on recent internal evaluation on a pilot project in Peninsular Malaysia, by conducting Live FDP, the process efficiency in FDP evaluation scenarios was improved by up to 50% while simulation runs were shortened from 2 hrs to 20mins. On top of that, Integration & Collaboration involving benchmarking capability and via Data Ecosystem that allow cross domain collaboration between departments. This provides business continuity through data log for auditing purpose, single source of truth that leads to the increase of confidence and less uncertainties with breadth of multiple scenarios that allow techno-commercial evaluations and benchmarking with internal and external data. This paper will open up the mindset on the ways of how FDP can be developed with a new digital application that improves the project efficiency involving online cloud-based technology that allows multiple iterative processes in both technical and commercial aspects of the project. This is the new way of working that suits the difficult business climate that the O&G industry is currently facing.

Streamlining the Well Location Optimization Process - An Automated Approach Applied to a Large Onshore Carbonate Field

Infill drilling is a proved strategy to improve hydrocarbon recovery from reservoirs to increase production and maximize field value. Infill drilling projects address the following questions: 1) Where should the wells be drilled? 2) What should be their optimum trajectories? 3) What are the realistic ranges of incremental production of the infill wells? Answering these questions is important yet challenging as it requires the evaluation of multiple scenarios which is laborious and time intensive. This study presents an integrated workflow that allows the optimization of drilling locations using an automated approach that comprises cutting-edge optimization algorithms coupled to reservoir simulation. This workflow concurrently evaluates multiple scenarios until they are narrowed down to an optimum range according to pre-set objectives and honoring pre-established well design constraints. The simultaneous nature of the workflow makes it possible to differentiate between acceleration and real incremental recovery linked to proposed locations. In addition, the technology enables the optimization of all the elements that are relevant to the selection of drilling candidates, such as location, trajectory, inclination, and perforation interval. The well location optimization workflow was applied to a real carbonate large field; heavily faulted; with a well count of +400 active wells and subject to waterflooding. Hence the need for an automated way of finding new optimal drilling locations enabling testing of many locations. Also due to the significant full field model size; sector modelling capability was used such that the optimization, i.e. running many scenarios; could be carried out across smaller scale models within a reasonable time frame. Using powerful hardware and a fully parallelized simulation engine were also important elements in allowing the efficient evaluation of ranges of possible solutions while getting deeper insights into the field and wells responses. As a result of the study, 8 out of the original 9 well locations were moved to more optimal locations. The proposed optimized locations generate an incremental oil recovery increase of more than 70% compared to the original location (pre-optimization). In addition, the project was completed within 2 weeks of equivalent computational time which is a significant acceleration compared to a manual approach of running optimization on a full field model and it is significantly more straight forward than the conventional location selection process. The novelty of the project is introduced by customized python scripts. These scripts allow to achieve practical ways for placing the well locations to explore the solution space and at the same time, honor well design constraints, such as maximum well length, maximum step-out from the surface well-pad, and well perforation interval. Such in-built flexibility combined with automation and highly advanced optimization algorithms helped to achieve the project goals much easier and faster.

Clustering Technique for Scenario Reduction in Post-Energy Transition Voltage Dips Assessment

The Dutch transmission system operator makes multiple scenarios to predict the future developments. These scenarios will help to define the risk factors and constraints in the grid, for which reinforcement planning is necessary. The developed grid after these reinforcements should continue to fulfil the power quality assessment criteria specified in the Dutch grid code. The reduction in system strength due to partial phase out of the conventional generation may have an adverse impact on the PQ, especially the voltage dips. Precise assessment criteria for voltage dips have been stipulated by the Dutch grid code that also need to be met after the energy transition. Evaluating all possible grid future scenarios can provide insight in possible future operating conditions. In practice, due to various combinations of network configurations, loading scenarios and dispatch scenarios, it is not possible to analyze all operating scenarios in detail. This paper presents a method to determine the most important scenarios for voltage dip assessments using a clustering technique. The proposed clustering technique reduces the number of scenarios that are needed to be assessed that makes the whole process doable in practice.