Involvement from companies in oil and gas and other sectors is critical to the NDC’s success. We are seeking industry partners with experience, ideas and equipment, who want to co-invest to deliver a step change in performance, with support from the Oil & Gas Authority, the Offshore Petroleum Regulator for Environment and Decommissioning and the Health & Safety Executive.

There are a number of ways to get involved:

An Anchor Partnership requires a financial investment and a three to five-year commitment which secures a seat on the NDC Steering Group.  You will also be given an office for two or three people within the NDC and direct access to the research team and NDC facilities. This provides direct oversight of the research programme and the ability to drive the focus of the R&D programme. It also offers an additional network opportunity across the OGTC Solution Centre activities to provide oversight on new technology developments.

A Research Partnership, which requires a minimum two-year commitment, assures direct involvement in R&D projects. As a Research Partner you will be delivering R&D activity in the decommissioning arena in collaboration with the NDC, sharing capabilities, experience and personnel. You will have access to the NDC and OGTC network of industry and supply chain organisations and the opportunity to submit collective funding requests.

A Project Partnership requires a project specific commitment. As a Project Partner you will support a specific project, with access to personnel and facilities associated with the project together with the opportunity to network across the wider NDC activities.

Industry Relevant Projects:  The following PhD proposals have secured part-funding from the NDC and the University of Aberdeen and are seeking to attract part-funding from industry and/or related organisations.

NDC logoOUTLINE PHD PROPOSAL

Title: To investigate mechanisms to provide explanations of AI driven decision support systems in real-world settings

Lead Investigator: Professor Nir Oren, School of Natural and Computing Sciences, University of Aberdeen

Contact: Professor Nir Oren, Tel.: +441224274162  Email: n.oren@abdn.ac.uk

Aim:

This project aims to investigate mechanisms to provide explanations of AI driven decision support systems in real-world settings. In previous work, with input from a major oil and gas contractor, we developed a prototype tool for explaining complex plans to non-technical users, using formal argumentation theory and dialogue. The most significant limitation of the tool was its ability to work only with symbolic, qualitative data. In this project, we will investigate how concepts such as duration (e.g., an action to remove a pipe taking days) and uncertainty (e.g., having some chance of asbestos being present) can be handled, allowing for planning and explaining decommissioning specific tasks given large volumes of data.

Objectives:

  1. Investigate how dialogues and arguments about uncertain information can be created
  2. Investigate how arguments about continuous domains, and over long time-spans, can be generated
  3. Conduct a user study to evaluate the effectiveness of the approach

Deliverables:

Apart from scientific outputs, the student will create a prototype tool to demonstrate the approach; working with a partner from industry will allow for its effectiveness across the decommissioning domain to be evaluated.

Impact:

Decommissioning requires the generation and execution of complex plans, optimising and balancing across multiple criteria. It is difficult for humans to ensure that an optimal solution has been found, and existing tools are unable to demonstrate that all appropriate factors have been considered, and our work would directly tackle these issues. Given the opacity of decision support systems, both due to their increased complexity and the sheer volume of data now available, we believe that our work is both timely, and critical.

Our work is applicable to the following areas of the decommissioning roadmap:

  • Artificial intelligence assisted late life management
  • Artificial Intelligence assisted decommissioning management
  • Optimise, schedule and sequencing

This outputs from the project would bring benefits to the decision-making processes of companies working with the large-scale aspects of decommissioning, and in particular those that have to deal with both the legal and engineering aspects of the problem.

NDC logoOUTLINE PHD PROPOSAL

Title: Realistic Simulation: Synthetic to Realistic Underwater Scene Translation

Lead investigator: Dr Dewei Yi, School of Natural and Computing Sciences, University of Aberdeen

Contact: Dr Dewei Yi, Email: dewei.yi@abdn.ac.uk

Aim:

This project aims to minimise the gap between simulation and real world, so as to achieve realistic simulation. To achieve this, we will develop high-fidelity virtual sensor models and identify potential hazard before conducting real-world testing.

Objectives:

  1. To identify potential hazard and unsafe actions by advanced safety analysis
  2. A high-fidelity sensor model and a realistic noise model will be developed
  3. Hazard analysis report for underwater operation will be produced
  4. The developed model will be evaluated by real-world data to show the performance

Deliverables:

The specific deliverables include:

  • A high-fidelity sensor model and a realistic noise model
  • Hazard analysis report for underwater operation
  • A demo for testing the developed model

Impact:

This project focuses on digitalisation and simulation which will benefit industry through significantly reducing costs and improving efficiency. The outcomes of the project will be helpful for achieving the agile development of building high-fidelity simulation and facilitate development of intelligent simulation for industry. In addition, this project fits with the theme of “Basin Wide Simulation” and the industry-led focus of area of “skills and capacity development”.

NDC logoOUTLINE PHD PROPOSAL

Title: Underwater Semantic Understanding

Lead investigator: Dr Dewei Yi, School of Natural and Computing Sciences, University of Aberdeen

Contact: Dr Dewei Yi, Email: dewei.yi@abdn.ac.uk

Aim:

Semantic understanding is one of the most important functionalities of autonomous or semi-autonomous systems. However, the existing solutions for underwater semantic segmentation and scene parsing are significantly less advanced. This is because the visual content of underwater imagery is entirely different from overland imagery, where the object categories, background patterns, and optical distortion in underwater scenes are quite different from these in overland scenes. Therefore, it is an urgent task to develop semantic understanding techniques for autonomous or semi-autonomous underwater vehicles.

The aim of the project is to develop novel vision semantic segmentation techniques for underwater scenes and then smart decision-making strategies will be developed using semantic segmentation results.

Objectives:

  1. Develop a semantic segmentation model for underwater scenes
  2. Develop a hazard analysis strategy for underwater intelligent decision-making
  3. The developed model will be evaluated using real-world data to show its performance

Deliverables:

The specific deliverables include:

  • A semantic segmentation model for underwater scenes
  • A hazard analysis strategy for underwater intelligent decision-making
  • A demo for testing the developed model

Impact:

This project focuses on remote monitoring making surveying of marine environment safer, more efficient, and more intelligent. The outcomes of the project will help to achieve fully autonomous remote surveying, such as, situation awareness, hazard identification, smart decision-making, for marine and other related industry. In addition, this project fits with the industry-led focus area of “skills and capability development”.

NDC logoOUTLINE PHD PROPOSAL

Title: Underwater Vision Enhancement

Lead Investigator: Dr Dewei Yi, School of Natural and Computing Sciences, University of Aberdeen

Contact: Dr Dewei Yi, Email: dewei.yi@abdn.ac.uk

Aim:

In underwater scenes, wavelength-dependent light absorption scattering degrades the visibility of images and videos. The degraded water images and videos affect the accuracy of pattern recognition, visual understanding, and key feature extraction in underwater scenes. Therefore, underwater vision enhancement is significant for underwater vehicles and aquatic robotics due to the complicated underwater environment and lighting conditions.

This project aims at developing novel vision enhancement techniques for underwater scenes. This is a rapidly growing area and focuses on a class of far-reaching scientific and technical problems. To help robots and/or operators see better underwater, we will transfer videos/images from underwater style to on-the-land style.

Objectives:

To achieve the aim of the project, three objectives need to be satisfied:

  1. A model of underwater vision enhancement will be developed
  2. The interface of developed model and test beds will be implemented
  3. The developed model will be evaluated by real-world data to show the performance

Deliverables:

The specific deliverables include:

  • A model of underwater vision enhancement
  • The interface of developed model and test beds
  • A demo for testing the developed model

Impact:

This project focuses on safety critical systems, which make the operations of robots safer and smarter as required by industry (e.g. marine, automotive, and other related industry). The outcome of project will enhance vision of robots themselves and their remote operators. For industry, remote monitoring and safe critical applications will benefit from the project. In addition, this project fits with two industry-led focus areas well: “skills and capability development” and “Facilities clean up and disposal”.

NDC logoOUTLINE PHD PROPOSAL

Title: Economic and technical determinants of the cessation of production date – a comparison of decision-making criteria

Lead Investigators: Dr Yakubu Abdul-Salam, Email: y.abdul-salam@abdn.ac.uk and Dr Marc Gronwald, Business School, University of Aberdeen

Aim:

This project analyses the impact of factors such as operating and decommissioning cost, cost of capital, production decline rates, and oil price behaviour (volatility, cyclicality and unpredictability) on the determination of the cessation of production (COP) date. The economic environment in which the decommissioning decision is taking place recently became increasingly challenging. First, oil prices exhibit a more volatile, less predictable pattern. Second, shifts in investment behaviour away from fossil fuels imply changing cost of capital for investments in oil and gas. These factors add to geological and technical factors which determine production decline rates, operating and decommissioning cost. The COP date is commonly determined using the economic limit criterion, which, however, does not take into account all future cost and revenues. The alternative criterion of the maximisation of the remaining net present value (rNPV) not only takes all future cost and revenues into account, but also their timing. The aim of the project is, thus, to develop a decision-making tool which allows one to take all these factors into account and, thus, is appropriate in a challenging investment environment characterised by changing cost of capital and less predictable oil prices.

Objectives:

WP (1) Analysis of technical and geological factors: Collection of data on operating and decommissioning cost as well production decline rates

WP (2) Analysis of economic environment: Identification of appropriate stochastic process that captures the idiosyncratic behaviour of oil prices. Focus on how the change in the role

OPEC/OPEC+ and the shale oil revolution affects predictability of oil prices

WP (3) Construction of financial economic model that accounts for oil price behaviour, operating cost, production decline rate, decommissioning cost, cost of capital, and value of tax reliefs

WP (4) Comparison of decision-making criteria: economic limit vs maximisation of remaining NPV

WP (5) Valuation of option to postpone decommissioning using real options approach

Deliverables:

WP 1 and 2: Collection and analysis of data on both technical factors as well as economic environment, including empirical modelling of oil price behaviour and analysis of impact of shift in energy investments on cost of capital. Expected completion: end of Year 1.  Potential for publication in peer-reviewed energy economic journal

WP 3 and 4: Construction of financial economic model and comparison of decision-making criteria. This model has the potential for being used in actual decommissioning decisions. Expected completion: end of Year 3

WP 5: Valuation of option to postpone decommissioning using real option analysis.  Potential for publication in peer-reviewed energy economic journal

Impact:

The outcome of this project is a refined tool for decision-making in decommissioning. This is of direct benefit for the industry as this helps improve decision processes. In addition, the project supports the industry with aligning with the MER UK strategy.

OUTLINE PHD PROPOSAL NDC logo

Title: Developing a modelling tool for feasibility analysis of CO2 sequestration on mature reservoirs: a combined approach of considering injectivity, gas trapping and economic factors

Lead Investigators: Dr Amin Sharifi and Dr Roozbeh Rafati (School of Engineering, UoA), and Dr Stefano Bagala BatiGea Ltd

Contact: Dr Amin Sharifi, Tel: +441224272977  Email: amin.sharifi@abdn.ac.uk

Aim:

This research project takes the steps from the current debate on the use of mature, depleted reservoirs in the North Sea as storage units for Carbon Capture Usage and Storage (CCUS). The aim of this project is to couple dynamics of the flow with reactions in pore spaces for safe carbon dioxide injection operations.

Objectives:

  1. Including the CO2-related reactions in pore spaces to CCUS process;
  2. Predicting the CO2 storage capacity with dynamic reactions;
  3. Predicting the carbon dioxide migration in the reservoir;
  4. Analysing the economic and operational factors on the decision-making process.

Deliverables:

  • A coupled model for reservoir properties and reactions into a simulator
  • Sensitivity analysis outcomes on a case study from the North Sea

Providing an algorithm or workflow for economic analysis using the developed model for potential late-life plans of a reservoir with a view on CO2 sequestration.

Impact:

The developed model can be used as a benchmark in oil and gas companies for their reservoir management and decision-making process where CO2 sequestration is considered. This gives the companies a tool to investigate the feasibility of such process and predict its performance.

OUTLINE PHD PROPOSAL NDC logo

Title: Examining the alignment between (a) the legal and regulatory requirements for the decommissioning of offshore oil and gas infrastructure on the UKCS and (b) the issues raised by the climate emergency in terms of protection of ecosystems and efficient and timely access to opportunities for the implementation of technologies relevant to the transition to a low-carbon economy

Lead investigators: Professors John Paterson and Greg Gordon, School of Law, University of Aberdeen

Overview:

The legal and regulatory requirements for the decommissioning of offshore oil and gas infrastructure on the UKCS are well-developed and broadly understood. This is in no small measure due to the impact of OSPAR Decision 98/3 which in turn may be best understood as a reaction to the Brent Spar controversy in the mid-1990s.  In short, whilst by no means as draconian as a return to the complete removal requirement contained in the Geneva Convention on the Continental Shelf 1958, Decision 98/3 does have the effect of substantially restricting the decommissioning options that would otherwise be available under UNCLOS 1982/IMO Guidelines 1989 and indeed under the OSPAR Convention 1992. Thus, unless a platform falls under one of the narrowly-defined derogation cases, then it must be entirely removed. Furthermore, the wording of Decision 98/3 means that periodic reviews can only modify those derogations in the direction of further restrictions. This approach no doubt captures the public mood that existed in the context of the Brent Spar case, but it is a question whether it is consistent with more recent studies which suggest that, far from achieving environmental protection, the removal of infrastructure may actually be damaging to marine ecosystems. Whilst it might be thought unlikely that there will be any appetite within OSPAR in the foreseeable future for a modification of this position, questions do need to be asked about the consistency of this approach with more modern understandings of ecosystem services and indeed OSPAR’s own focus on environmental protection and its preference for the reuse of materials at the top of the waste hierarchy.

Further questions arise, nevertheless, as to the extent to which the current regime is sufficiently accommodating of the need to ensure that decommissioning plans properly consider reuse options for redundant offshore oil and gas infrastructure. Whilst OSPAR is not open to leaving infrastructure in place for ecosystem purposes on the basis that any artificial reef must be constructed of new materials, it is open to the idea of such infrastructure being reused for other purposes. Thus, it would be possible for a platform to be reused in connection with a renewable energy or carbon sequestration project and Guidance Notes issued by BEIS (the competent authority) require these possibilities to be considered in the context of the preparation of a decommissioning plan. The question is, however, whether the absence of an immediately available option relating to renewables allows the obligation under the Guidance Notes to be fulfilled too easily without there having been sufficient thought given the possible need for that infrastructure in the future.

It can, of course, be easily objected that it will most often be unlikely that a platform will prove suitable for long-term retention on the basis of the likely condition of such infrastructure at the point of decommissioning (many are beyond their design life; maintenance in the run-up to decommissioning will not have been a priority; etc), but does this observation indicate that perhaps the MER UK Strategy is unduly narrowly focused upon hydrocarbons to the exclusion of the role of hydrocarbon infrastructure in the energy transition? Insofar as that can be argued to be the case, what legal and regulatory conclusions can be drawn? Even if these questions are thought to be a step too far in relation to platforms, the same may not be true in relation to pipelines, umbilicals and even reservoir data in the case of CCS. Equally, is sufficient thought given to the potential role of oil and gas infrastructure in the context of the hydrogen economy, the development of geothermal opportunities and others?

Aim and Objectives:

This project will allow researchers to focus in on the elements of the above observations. Lead supervisors, Professors John Paterson and Greg Gordon and the School of Law have a relatively large pool of expertise to draw upon and can cover a wide range of issues in this field.

This could include a more holistic approach which seeks to understand how the top level legal framework (perhaps at a regional level) would need to be adapted to incorporate contemporary knowledge and to provide room for evidence-based decommissioning/reuse solutions. Equally, it could include more narrowly focused studies of individual components (for example, examining the OSPAR approach through the lens of ecosystem services or considering the legal and regulatory reforms that may be required to allow better integration of decommissioning and reuse decisions.

Deliverables and Impact:

Independent and unbiased evidence-based research on a number of the elements discussed above, that will inform industry and the regulator and potentially advance the current legal and regulatory landscape.

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