Superconducting thermo-magnetic-mechanical energy conversion machine

This paper presents a superconducting thermo-magnetic-mechanical (STMM) energy conversion process. This energy conversion concept revolves around of utilizing a cryogenic coolant, e.g., liquid nitrogen, as a thermal energy facilitator to cool down the superconductor to below the critical temperature. Then, utilizing the mixed state, i.e., Meissner effect and weak vertex - which leads to partially shielding the magnetic field - an external magnetic field is used to apply force on the superconductor and create motion. The concept proposed is demonstrated using thorough Multiphysics understanding i.e., thermal, magnetic, and mechanical. The proof of concept is completed by using a combination of analytical and numerical simulations and calculations, and measurements. Using this concept, a practical automotive drive has been theoretically designed and compared with a counterpart electric drive. The proposed technology has a potential to provide a step change for the sustainable cleaner cost-effective transportation.

Human Computer Interface using Eye Gazing with error fixation in Smooth and Saccadic Eye Movement

Human Computer Interface (HCI) requires proper coordination and definition of features that serve as input to the system. The parameters of a saccadic and smooth eye movement tracking are observed and a comparison is drawn for HCI. This methodology is further incorporated with Pupil, OpenCV and Microsoft Visual Studio for image processing to identify the position of the pupil and observe the pupil movement direction in real-time. Once the direction is identified, it is possible to determine the accurate cruise position which moves towards the target. To quantify the differences between the step-change tracking of saccadic eye movement and incremental tracking of smooth eye movement, the test was conducted on two users. With the help of incremental tracking of smooth eye movement, an accuracy of 90% is achieved. It is found that the incremental tracking requires an average time of 7.21s while the time for step change tracking is just 2.82s. Based on the observations, it is determined that, when compared to the saccadic eye movement tracking, the smooth eye movement tracking is over four times more accurate. Therefore, the smooth eye tracking was found to be more accurate, precise, reliable, and predictable to use with the mouse cursor than the saccadic eye movement tracking.

Geoscience Language Processing for Exploration

Deep learning has recently been providing step-change capabilities, particularly using transformer models, for natural language processing applications such as question answering, query-based summarization, and language translation for general-purpose context. We have developed a geoscience-specific language processing solution using such models to enable geoscientists to perform rapid, fully-quantitative and automated analysis of large corpuses of data and gain insights. One of the key transformer-based model is BERT (Bidirectional Encoder Representations from Transformers). It is trained with a large amount of general-purpose text (e.g., Common Crawl). Use of such a model for geoscience applications can face a number of challenges. One is due to the insignificant presence of geoscience-specific vocabulary in general-purpose context (e.g. daily language) and the other one is due to the geoscience jargon (domain-specific meaning of words). For example, salt is more likely to be associated with table salt within a daily language but it is used as a subsurface entity within geosciences. To elevate such challenges, we retrained a pre-trained BERT model with our 20M internal geoscientific records. We will refer the retrained model as GeoBERT. We fine-tuned the GeoBERT model for a number of tasks including geoscience question answering and query-based summarization. BERT models are very large in size. For example, BERT-Large has 340M trained parameters. Geoscience language processing with these models, including GeoBERT, could result in a substantial latency when all database is processed at every call of the model. To address this challenge, we developed a retriever-reader engine consisting of an embedding-based similarity search as a context retrieval step, which helps the solution to narrow the context for a given query before processing the context with GeoBERT. We built a solution integrating context-retrieval and GeoBERT models. Benchmarks show that it is effective to help geologists to identify answers and context for given questions. The prototype will also produce a summary to different granularity for a given set of documents. We have also demonstrated that domain-specific GeoBERT outperforms general-purpose BERT for geoscience applications.

Leveraging Game AI to Transform Integrated Brownfield Well Planning

PDO is in the process of transforming its well and urban planning by adopting digital technologies and Artificial Intelligence (AI) to improve organizational efficiency and maximize business value through faster quality decision. In 2020, PDO collaborated with a third-party contractor to provide a novel solution to an industry-wide problem: "how to effectively plan 100's of wells in a congested brownfield setting?". This paper describes an innovative AI-assisted well planning method that is a game-changer for well planning in mature fields, providing efficiency in urban and well trajectory planning. It was applied in one of PDO's most congested fields with a targeted infill of 43m well spacing. The novel well planning method automatically designs and optimizes well trajectories for 100-200 new wells while considering surface, subsurface and well design constraints. Existing manual workflows in the industry are extremely time consuming and sequential (multiple man-months of work) - particularly for fields with a congested subsurface (350+ existing wells in this case) and surface (limited options for new well pads). These conventional and sequential ways of working are therefore likely to leave value on the table because it is difficult to find 100+ feasible well trajectories, and optimize the development in an efficient manner. The implemented workflow has the potential to enable step change in improvements in time and value for brownfield well and urban planning for all future PDO developments. The innovative AI assisted workflow, an industry first for an infill development of this size, evaluates, generates and optimizes from thousands of drillable trajectories to an optimized set for the field development plan (based on ranked value drivers, in this case, competitive value, cost and UR). The workflow provides a range of drillable trajectories with multi-scenario targets and surface locations, allowing ranking, selection and optimization to be driven by selected metrics (well length, landing point and/or surface locations). The approach leads to a step change reduction in cycle time for well and urban planning in a complex brownfield with 100-200 infill targets, from many months to just a few weeks. It provides potential game-changing digital solutions to the industry, enabling improved performance, much shorter cycle times and robust, unbiased well plans. The real footprint and innovation from this AI-assisted workflow is the use of state-of-the-art AI to enhance team collaboration and integration, supporting much faster and higher quality field development decisions. This paper describes a novel solution to integrated well planning. This is a tangible example of real digital transformation of a complex, integrated and multi-disciplinary problem (geologists, well engineers, geomatics, concept engineers and reservoir engineers), and only one of very few applied use cases in the industry. This application also gives an example of "augmented intelligence", i.e. how AI can be used to truly support integrated project teams, while the teams remain fully in control of the ultimate decisions. The success of this approach leans on the integrated teamwork across multiple technical disciplines, not only involving PDO's resources, but also WhiteSpace Energy as a 3rd party service provider. The enhanced collaboration allowed all parties to highlight their constraints in an integrated way from the start, strengthening the technical discussion between disciplines and learning from each constraint impact and dependencies. (e.g. dog leg severity). In summary, the change in process flow moving from a sequential well planning and urban planning method to an iterative and fast AI solution – including all technical considerations from beginning represented for PDO an added value of over 6 months of direct cycle time HC acceleration.

Developing Capability for a Continuous Improvement Culture in Petroleum Development Oman PDO

Objectives/Scope To highlight at a high level the successful method of building Continuous Improvement (CI) competence Pan Petroleum Development Oman (PDO) and the different pathways used to engage everyone at every level of the organization circa. 10,000 people as part of PDO transformation to a Continuous Improvement organization Methods, Procedures, Process PDO is developing a CI culture through 2 pathways, CI Professional & CI Generalist. CI Professionals, limited to 50 high potentials, spend 3 years full time developing CI competence to a level they can coach autonomously in the business. CI Generalists build CI skills though training and deliberate practice becoming Lean Practitioners, Lean Managers and Practical Problem Solving (PPS) practitioners & facilitators. Results, Observations, Conclusions A CI function has been created to own the development of staff, standards, and deployment. Having quarterly competence development reviews for CI Professionals, to discuss and monitor progress and establish goals for the next quarter have resulted in a step change in speed and quality of development. We have had 100+ CI Coaches through the development program as of July 2021, either returning to the business to germinate CI in their new teams or developing further to become a career CI specialist. Developing the CI competences for CI Generalist has seen an explosion in ideas circa 10,000 with 500 teams practicing CI Fundamentals, 200+ qualified PPS facilitators & 250+ Lean managers coaching in the business. Benefits to date include circa 150K M3 production gain and many millions saved from the budget. Observation is we are developing autonomous teams able to solve problems for themselves resulting in an engaged workforce:- Improving today for a better tomorrow. Sponsorship from the top is the imperative ingredient for success. Engagement of the workforce from the bottom up, staff doing the work, creates the momentum required to make a CI transformation successful. Novel, Additive Information Holistically the approach used can be transferred to any other business and although tailored for PDO is business/sector is agnostic. The coaches who have graduated through our internal certification can and are applying Continuous Improvement in our business and externally in other organizations. Looking to the future we can partner with universities to have Continuous Improvement as part of the curriculum either as modules or a whole syllabus.

Modern Drilling and Completion in Contradiction of New Artificial Lift Method Concept

In challenging times of 2020 and inconsistency with the background of a low-oil-price environment, innovative ideas needed to give a second life to all available resources such as unconventional, shallow, depleted, mature, heavy oil and by bypassed oil with a cost-effective manner (usually innovation created to fit needs). U-shaped well a combined with pigging lifting (conceptual study for new artificial lift method) is one of the selected scenarios studied under the objective of innovative, low-cost techniques to overcome many projects challenges. U shaped well accompanied with a new pigging artificial lift method are new concept studied in this lab work. Conceptual model presents many benefits of this new application such as solving most of the current wells and production challenges. The study reflects more well control with two paths, better well stimulation, low fracturing pressure and double rates, inject and lift chemical for clean without intervention, double well life "additional strings", new recompletions without rig, two horizontal side used for production or injection, step change for reservoir monitoring, improving artificial lift performance and allow creating Pigging lift "New artificial lift concept". U shaped well accompanied with a new pigging artificial lift method study shows the following progress: 1. Additional down hole barrier from the deepest point and additional open side keep the well under control more over minimize the existing well control killing procedures with low cost and risk in addition to discarding the CT operations for killing or prepare the well for W/O. 2. Decreasing stimulation pressures needs (double injection rates) and overcome the existing accessibility challenges 3. Allowing pull heading stimulation w/less displacement time and high rate and chimerical batch pumping from one side to another increase well life and eliminate PKRs risk as chimerical batches will be pigger, easier and faster. 4. Additional down hole monitoring system allowing uniform stimulation and discarding the CT operations for well stimulation and cleaning, 5. Avoiding post stimulation damage throughout fast clean-up 6. Ability to stimulate from one side with artificial lift from other side Avoiding the corrosion and erosion by faster operations 7. Allow faster plug and perf. multistage fracturing technology and overcome the unconventional well fracturing which required rate and pressure 8. Eliminate rig usage to pull the frac string to run completions 9. Step change for reservoir mentoring without S/D and real-time Logging, Sampling The deployment of U Shaped Well allows new artificial lift concept (Pigging lift) to apply. This new approach led to improved wells performance also raising efficiency of the use of the existing resources besides saving time and in return cost. This approach helps in improving well utilization and efficiency levels.

The DP5 Probability, Quantification and Visualisation of Structural Uncertainty in Single Molecules

Whenever a new molecule is made, a chemist will justify the proposed structure by analysing the NMR spectra. The widely-used DP4 algorithm will choose the best match from a series of possibilities, but draws no conclusions from a single candidate structure. Here we present the DP5 probability, a step-change in the quantification of molecular uncertainty: given one structure and one 13C NMR spectra, DP5 gives the probability of the structure being correct. We show the DP5 probability can rapidly differentiate between structure proposals indistinguishable by NMR to an expert chemist. We also show in a number of challenging examples the DP5 probability may prevent incorrect structures being published and later reassigned. DP5 will prove extremely valuable in fields such as discovery-driven automated chemical synthesis and drug development. Alongside the DP4-AI package, DP5 can help guide synthetic chemists when resolving the most subtle structural uncertainty. The DP5 system is available at https://github.com/Goodman-lab/DP5.

Innovation and opportunity: review of the UK’s national AI strategy

The publication of the UK’s National Artificial Intelligence (AI) Strategy represents a step-change in the national industrial, policy, regulatory, and geo-strategic agenda. Although there is a multiplicity of threads to explore this text can be read primarily as a ‘signalling’ document. Indeed, we read the National AI Strategy as a vision for innovation and opportunity, underpinned by a trust framework that has innovation and opportunity at the forefront. We provide an overview of the structure of the document and offer an emphasised commentary on various standouts. Our main takeaways are: Innovation First: a clear signal is that innovation is at the forefront of UK’s data priorities. Alternative Ecosystem of Trust: the UK’s regulatory-market norms becoming the preferred ecosystem is dependent upon the regulatory system and delivery frameworks required. Defence, Security and Risk: security and risk are discussed in terms of utilisation of AI and governance. Revision of Data Protection: the signal is that the UK is indeed seeking to position itself as less stringent regarding data protection and necessary documentation. EU Disalignment—Atlanticism?: questions are raised regarding a step back in terms of data protection rights. We conclude with further notes on data flow continuity, the feasibility of a sector approach to regulation, legal liability, and the lack of a method of engagement for stakeholders. Whilst the strategy sends important signals for innovation, achieving ethical innovation is a harder challenge and will require a carefully evolved framework built with appropriate expertise.

Mechanical properties of sunflower oil under pressure

This article presents the results of research on the influence of high pressure on the mechanical properties of sunflower oil. The pressure value was changed by the stepwise method to obtain thermodynamic equilibrium. Dependencies of changes in the volume and compressibility of sunflower oil on pressure were investigated. A discontinuous (step) change was observed indicating the appearance of the first order phase transformation. The phase transition for sunflower oil was observed in the pressure range from 450 to 500 MPa after about 170 h. Most likely, then, there was a change to the double crystal phase. The time after which this transformation took place was the longest of all times that the authors have observed so far for the study.