Analyzing technology landscape of carbon capture storage and utilization in Baltic Sea region through patents

Capturing CO2 and preventing it from being released into the atmosphere was first suggested in 1977; using existing technology in new ways. CO2 capture technology has been used since the 1920s for separating CO2 sometimes found in natural gas reservoirs from the saleable methane gas. More recently, investment in CCS is being driven by the oil and gas industries as well as cement, iron and steel, and chemical production industries in the push for decarbonization. Once it is separated from other gases, the carbon dioxide is then compressed, transported, and injected underground for permanent storage. About 90-100 % of produced carbon dioxide can be captured in this manner. Many are betting on CCS as a key to greenhouse gas emission reductions, since leveraging CCS is expected to achieve 14-19 % of the reductions needed by 2050 (1,2,3). In 2020, we sent 40 billion metric tons (t) of carbon dioxide into Earth’s atmosphere. We need to cut that number to 0 by 2050 if we are to avoid the worst consequences of climate change, according to the Intergovernmental Panel on Climate Change (IPCC). The objectives of this paper is to present the patent landscape of Baltic sea region countries (BSR), which includes Lithuania, Latvia, Estonia, Finland, Denmark, Sweden, Russia, Poland and Norway. To perform the analysis searches have been conducted to identify patents related to Carbon capture and sequestration for the BSR. Patent analytics searches have been restricted to dates from 2000-2020. Technologies investigated mainly focuses on CO2 storage, monitoring, utilization and transport. The patent analytics searches have been conducted to identify patents related to CCUS technology. The search resulted in 3299 patent families. A relevancy analysis was done to identify patents which are related to CCUS & resulted in 497 patent families. Identified relevant patents have been categorized in a classification scheme. Results of this patent analytics work shows that in 2009 we have the greatest number of IP activity for CCUS. Exponential growth in patent filing since 2005-2009, showing an increasing trend for CCUS activities, 2010-2015 has an exponential decreasing trend for CCUS activities. In northern and eastern Europe, Russia & Poland are leading the research & patent filing in the CCUS domain. From industry point of view General Electrics (GE)has the highest number of publications followed by Mitsubishi and Siemens. 85 % of 497 relevant Patent families are Alive. GE has around 78 % of its families alive. The top patents are related to capture, storage, sequestration or disposal of greenhouse gases and followed by patents related to separation processes. CO2 capture is the most explored technology/CCUS type along with storage. Unfortunately, there is a decreasing trend in patent filings since 2016. The CCUS technologies are striving to gain traction in the set of options for dealing with climate change, but growth is very slow due to absence or low intervention of government action on climate change, public scepticism, increasing costs, and advances in other options including renewables and shale gas

Caloric vestibular stimulation for the management of motor and non-motor symptoms in Parkinson's disease

Introduction: A recent case study showed that repeated sessions of caloric vestibular stimulation (CVS) relieved motor and non-motor symptoms associated with Parkinson's disease (PD). Here we sought to confirm these results in a prospective, double-blind, randomized, placebo treatment-controlled study. Methods: 33 PD subjects receiving stable anti-Parkinsonian therapy completed an active (n = 16) or placebo (n = 17) treatment period. Subjects self-administered CVS at home twice-daily via a portable, pre-programmed, solid-state ThermoNeuroModulation (TNMTM) device, which delivered continually-varying thermal waveforms through aluminum ear-probes mounted on a wearable headset. Subjects were followed over a 4-week baseline period, 8 weeks of treatment and then at 5- and 24-weeks post-treatment. At each study visit, standardized clinical assessments were conducted during ON-medication states to evaluate changes in motor and non-motor symptoms, activities of daily living, and quality of life ratings. Results: Change scores between baseline and the end of treatment showed that active-arm subjects demonstrated clinically-relevant reductions in motor and non-motor symptoms that were significantly greater than placebo- arm subjects. Active treatment was also associated with improved scores on activities of daily living assessments. Therapeutic gains were still evident 5 weeks after the end of active treatment but had started to recede at 24 weeks follow-up. No serious adverse events were associated with device use, and there was high participant satisfaction and tolerability of treatment. Conclusion: The results provide evidence that repeated CVS can provide safe and enduring adjuvant relief for motor and non-motor symptoms associated with PD

CVD-MPFA full pressure support, coupled unstructured discrete fracture–matrix Darcy-flux approximations

Two novel control-volume methods are presented for flow in fractured porous media, involving coupling the control-volume distributed multi-point flux approximation (CVD-MPFA (c.f. Edwards et al.)) constructed with full pressure support (FPS), to two types of discrete fracture-matrix approximation for flow simulation on unstructured grids; (i) involving hybrid grids and (ii) a lower dimensional fracture model. Flow is governed by Darcy's law together with mass conservation both in the rock matrix and in fractures, where large discontinuous permeability tensors can occur. Finite-volume FPS schemes are more robust than the earlier CVD-MPFA triangular pressure support (TPS) schemes for problems involving strongly anisotropic homogeneous and heterogeneous full-tensor permeability fields. We use a cell-centred hybrid-grid method, where fractures are represented by lower-dimensional interfaces between matrix grid cells in the physical mesh, and expanded to equi-dimensional cells in the computational domain. We present a simple procedure to form a consistent hybrid-grid locally for a dual-cell. We also propose a novel hybrid-grid for intersecting fractures, for the FPS method, which improves the condition number of the global linear system and permits larger time steps for tracer transport. The tracer flow transport equation is coupled with the pressure equation and the results provide flow parameter assessment of the fracture models. Transport results obtained via TPS and FPS hybrid-grid formulations are compared with corresponding results of fine-scale explicit equi-dimensional formulations. The results show that the hybrid-grid FPS method applies to general full-tensor fields and provides improved robust approximations compared to the hybrid-grid TPS method for fractured domains, for both weakly anisotropic permeability fields and in particular for very strong anisotropic full-tensor permeability fields where the TPS scheme exhibits spurious oscillations. The hybrid-grid FPS formulation is extended to compressible flow and the results demonstrate the method is also robust for transient flow. Furthermore, FPS is coupled with a lower-dimensional fracture model, where fractures are strictly lower-dimensional in the physical mesh. Comparisons of the hybrid-grid FPS method and the FPS lower-dimensional fracture model are presented for several cases of isotropic and strongly anisotropic fractured media which illustrate the benefits of the respective methods

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Modeling of induction stirred ladles

Over the years numerous computational fluid dynamics models have been developed in order to study the fluid flow in gas and induction stirred ladles. These models are used to gain insight in the industrial processes used in ladle treatment of steel. A unified model of an induction stirred Ladle in two and three dimensions is presented. Induction stirring of molten steel is a coupled multi-physics phenomena involving electromagnetic and fluid flow. Models presented in this thesis gives a more accurate description of the real stirring conditions and flow pattern, by taking into account the multi-physics behavior of the induction stirring process in an induction stirred ladle. This thesis presents a formulation of coupled electromagnetic and fluid flow equations. The coupled electromagnetic and fluid flow equations are solved using the finite element method in two and three-dimensions. The simulation model is used to predict values of steel velocities and magnetic flux density. The simulation model is also used to predict the effect of increased current density on flow velocity. Magnetic flux density values obtained from the model are verified against experimental values.  QC 2012061

Upscaling Porous Media Using Neural Networks: A Deep Learning Approach to Homogenization and Averaging

In recent years machine learning algorithms have been gaining momentum in resolving subsurface flow issues related to hydrocarbon flows, Carbon capture utilization and storage, hydrogen storage, geothermal flows, and enhanced oil recovery. This paper presents and attempts to solve subsurface flow problem using neural upscaling method. The neural upscaling method, described in the present work, is a machine learning approach to calculate effective properties in each grid block for subsurface flow modeling. This method is intended to be more accurate than traditional analytical upscaling methods (which are only accurate for layered or homogeneous media) and numerical upscaling methods (which are more accurate for heterogeneous media but involve higher computational cost and are dependent on boundary conditions). The neural upscaling method is based on learning from a large number of geological realizations, which allows it to account for uncertainty in geology. It is also computationally fast and accurate. The method is demonstrated through a series of 2D test cases, and its accuracy is compared to that of analytical and numerical upscaling methods

Exploring the Potential of Carbon Capture, Utilization, and Storage in Baltic Sea Region Countries: A Review of CCUS Patents from 2000 to 2022

Carbon capture, utilization, and storage (CCUS) refers to technologies that capture carbon dioxide (CO2) emissions from sources such as power plants, industrial facilities, and transportation, and either store it underground or use it for beneficial purposes. CCUS can play a role in reducing greenhouse gas emissions and mitigating climate change, as CO2 is a major contributor to global warming. In the Baltic Sea region countries (BSR), patent searches from 2000 to 2020 reveal that CCUS technologies are focused on CO2 storage, monitoring, utilization, and transport. However, the adoption and deployment of these technologies has been slow due to a variety of factors, including a lack of government action on climate change, public skepticism, increasing costs, and advances in other options such as renewables and shale gas. Overall, CCUS has the potential to significantly reduce CO2 emissions and contribute to climate change mitigation efforts, but more work is needed to overcome the barriers to its widespread adoption in the BSR and elsewhere. This could include policy measures to incentivize the use of CCUS technologies, public education and outreach efforts to increase understanding and support for CCUS, and research and development to improve the efficiency and cost-effectiveness of these technologies

Detecting Underwater Concrete Cracks with Machine Learning: A Clear Vision of a Murky Problem

This paper presents the development of an underwater crack detection system for structural integrity assessment of submerged structures, such as offshore oil and gas installations, underwater pipelines, underwater foundations for bridges, dams, etc. Our focus is on the use of machine-learning-based approaches. First, a detailed literature review of the state of the current methods for underwater surface crack detection is presented, highlighting challenges and opportunities. An overview of the image augmentation approach for the creation of underwater optical effects is also presented. Experimental results using a standard network-based machine learning approach, which is used for surface crack detection in onshore environments, are presented. A series of test cases is presented in which existing networks’ performance is improved using augmented images for underwater conditions. The effectiveness and accuracy of the proposed approach in detecting cracks in underwater concrete structures are demonstrated. The proposed approach has the potential to improve the safety and reliability of underwater structures and prevent catastrophic failures

Assessing Geothermal Energy Production Potential of Cambrian Geothermal Complexes in Lithuania

Lithuania has a geothermal anomaly situated in the southwestern region of the country. This anomaly is comprised of two primary geothermal complexes located in western Lithuania. The first complex is characterized by the Pärnu–Kemeri Devonian sandstone aquifers, which exhibit exceptionally good flow properties. However, the reservoir temperatures in this complex only reach up to 45 °C. The second complex encompasses Cambrian sandstone reservoirs. Although these Cambrian sandstone reservoirs exhibit high temperatures, with the highest reservoir temperatures reaching up to 96 °C, these Cambrian sandstone reservoirs have less favorable petrophysical properties. This study focuses on the high temperature Cambrian Geothermal sandstone reservoirs. The study aims to conduct a geological screening of the existing and depleted hydrocarbon reservoirs with high water production rates. After initial data gathering, numerical modeling is employed with the help of mechanistic box models to evaluate the geothermal potential of the selected sites for commercial development. Ultimately, the study identifies the top five screened sites, which could be developed further for techno-economical modelling