Additional Reserves Research Articles

Оценка предложений по формированию сети альтернативных маршрутов следования коридора «Север — Юг»

Purpose: to develop proposals for the development of the expected growth in traffic volumes along the North–South transport corridor. To assess the capacity of the Upper Baskunchak — Astrakhan — Olya port section as the most heavily loaded, where cargo flows from several directions merge. To show the need to unload the main direction of the North-South corridor and form a network of alternative routes in the transport corridor to ensure transportation guarantees in case of force majeure. Consider the possibility of attracting parallel routes through the North Caucasus Railway (SKZHD). Methods: the calculation of throughput was carried out using the methodology used in JSC “Russian Railways” and the author’s proposals, taking into account additional reserves of throughput. General logical methods were used — quantitative and qualitative analysis and synthesis, induction and deduction, analogies, classifications, a combination of historical and logical analyses. The proposed universal algorithm, which makes it possible to evaluate the possibility of choosing parallel moves, can be recommended for practical use. Results: the maximum number of trains that can be redirected to parallel routes has been established, taking into account the available capacity and their workload with export cargo traffic in the direction of the ports of the Azov-Black Sea basin. The relevance of the direction of development of heavy traffic aimed at reducing the required capacity and reducing inter-train intervals to increase the available capacity is shown. A universal algorithm has been formed that allows evaluating the possibility of choosing parallel moves. Practical significance: the necessity of mastering the expected cargo flow and preventing its departure to competing destinations, for example, through the Suez Canal, is shown. In the current political and economic conditions, the North — South International Transport Corridor (ITC) is changing its status: from an alternative to the Suez Canal, it is becoming one of the priority routes for Russian export cargo traffic.

Numerical modeling of discharge modes and evaluation of the major characteristics of latent heat thermal energy storage at a nuclear power plant

Under conditions of uneven power consumption schedules, construction of renewable power plants and low maneuverability of nuclear power plants (NPPs), combining NPPs with latent heat thermal energy storage systems (LHTES) can improve efficiency and maneuverability of NPPs. Combination of the LHTES with an additional low-capacity steam turbine will allow not only meeting peak electricity loads, but also increase the NPP safety by additional reservation of its own needs using this multifunctional turbine in emergency situations of complete blackouts. A scheme for combining a PCM-based thermal storage system with a two-circuit nuclear power plant is proposed, where the LHTES is charged with part of fresh steam from steam generators in the night hours of off-peak loads in the power grid and heating feed water above the nominal temperature during the peak loads. Non-stationary heat transfer between the heat storage material and feed water during the LHTES discharge was modeled using the finite volume method. The design characteristics of the LHTES as part of the NPP and the weight-size parameters of the thermal accumulator have been determined. The rational phase change material and the types of finned tubes have been determined. A solution has been proposed to ensure stable water temperature at the outlet of the PCM-based thermal accumulator during its discharge within the NPP that will significantly increase efficiency of its performance. Heat losses from the LHTES to the environment during the day have been calculated.

THE NEED TO CREATE AN ADDITIONAL RESERVE FUND OF ASSETS IN TIMES OF INFLATION / ՍՂԱՃԻ ՊԱՅՄԱՆՆԵՐՈՒՄ ԱԿՏԻՎՆԵՐԻ ՀԱՎԵԼՅԱԼ ՊԱՀՈՒՍՏԱՅԻՆ ՖՈՆԴԻ ՍՏԵՂԾՄԱՆ ԱՆՀՐԱԺԵՇՏՈՒԹՅՈՒՆԸ

The object of study of the article is scarcity and the replaceability of depreciable/depreciated assets with similar assets and the goal is the acquisition of new assets during the inflation conditions and the neutralization of the poverty effect of the inflation by creating an additional reserve fund of assets. In Armenia, as in every developed and developing country, the permissible rate of inflation is fixed by law, with its deviations. For example, in RA, according to Article 4 of the RA Law "On the State Budget of RA 2024" (previous years similarly) and until these last years as well, the permissible amount of inflation is 4% ± 1.5%. In UK - 2%, in the USA - from 5%-1/4 to 5%-1/2, etc. Given that price stability or the restoration of price stability does not, in fact, mean a return to a fixed price or point, but rather a state of slow and steady price growth, this raises the question of when inflation deviates from the legally defined above the permissible limit, how it relates to the context of substitutability of real sector assets. In other words, during the useful life of assets, in addition to the effects of obsolescence and physical depreciation, there is a certain difference between the current value and the amount of accumulated depreciation at the time of acquisition of a similar asset, as a result of which the acquisition of a new or modern asset requires additional expenses. In this context, the article raises the issue of replaceability of depresiable fixed assets with new ones and the creation of an additional reserve fund during inflation in the form of an expense, as a deduction from the tax base in a given year. As a scientific result, it is proposed to define the amount of the reserve fund as a deduction from the tax base, and the calculation methodology as presented in the point of scientific result.

The Impact of ESG Regulations and Taxonomy on the Credit Process in Commercial Banks

The purpose of the article is to present the impact of legal regulations in the field of sustainable development (ESG) and taxonomies on the course of credit processes in commercial banks. Methodology refers to studies of legal regulations, comparative analysis of cases (case study) and inference. Results of the research show that the implementation of ESG regulations and taxonomies and the adaptation of credit processes in commercial banks will result in structural changes in loan portfolios in the near future while moving away from financing dirty industries towards the green ones. As a result, the financing stream for green assets and those supporting sustainable development will be increased, while the financing of dirty assets will be significantly reduced due to the increase in risks and accompanying costs for customers and banks. It is expected that even if some banks grant loans to finance dirty assets, they will only be short-term loans and will require high servicing costs (commission, margin, legal security, and insurance). This is due to the fact that the portfolio with credit exposures in the so-called dirty industries (mining, construction, trade) will escalate the increase in ESG risk. Such a portfolio with dirty exposures will require banks to secure additional reserve capital to maintain higher general and sector systemic risk buffers. Some banks will completely stop financing assets from dirty industries, which will mean that some of them will be abandoned due to the lack or high costs of their modernization, intensifying the negative socio-economic consequences. The ongoing process of redirecting the financing stream to green assets in banks means that enterprises and households need to take earlier adaptation actions. These include actions against financing constraints in dirty sectors and likely future losses in infrastructure and assets related to them.

Hygienic aspects of mortality of the population of an industrial city

Introduction. The target indicators of the Federal Project “Clean Air” include a reduction in emissions of chemical pollutants by at least 20%. However, the main socially significant goal remains to improve the medical and demographic situation by reducing environmental and hygienic health risks.
 The purpose of the study was to preliminary assess the reserves for reducing mortality in the city of Omsk by identifying the most unfavourable territories in terms 
 of atmospheric air quality and identify priority chemicals, presumably causing negative trend in mortality.
 Materials and methods. To assess the quality of atmospheric air in the city of Omsk, the results of social and hygienic monitoring, environmental monitoring 
 of Federal Service of Russia on Hydrometeorology and Monitoring of the Environment (RosGidromet) for the multi-year period over 2009–2022 were used. 
 An analysis of the mortality rate of the population of Omsk for 2017–2022 was carried out. The data were studied in the context of municipal districts of the city of Omsk and in dynamics. Statistical methods were used in the study: ANOVA, correlation analysis, assessment of relative mortality risks. 
 Results. The relative risk (RR) of mortality for persons living in the most polluted areas of the city is 23–25% higher than in conditionally clean areas. Strong positive associations have been established: between the levels of actual total mortality and the specific gravity of atmospheric air samples exceeding the maximum single limit concentrations (R = 0.86; p < 0.05); between perennial average annual carbon monoxide concentrations and standardized rates of total mortality 
 (R = 0.93; p<0.05) and male mortality rates from all natural causes (R = 0.89; p<0.05).
 Limitations. The study is limited to the statistical research methods used. 
 Conclusion. The results of the study can become the basis for more efficient use of administrative resources in municipal districts of the city. As additional reserves for reducing mortality, the development of primary prevention measures at the outpatient level is important. It is necessary to optimize methodological approaches in the health control system of the population living in risk areas with developed industry.

Phosphorus applications adjusted to optimal crop yields can help sustain global phosphorus reserves

With the longevity of phosphorus reserves uncertain, distributing phosphorus to meet food production needs is a global challenge. Here we match plant-available soil Olsen phosphorus concentrations to thresholds for optimal productivity of improved grassland and 28 of the world’s most widely grown and valuable crops. We find more land (73%) below optimal production thresholds than above. We calculate that an initial capital application of 56,954 kt could boost soil Olsen phosphorus to their threshold concentrations and that 28,067 kt yr−1 (17,500 kt yr−1 to cropland) could maintain these thresholds. Without additional reserves becoming available, it would take 454 years at the current rate of application (20,500 kt yr−1) to exhaust estimated reserves (2020 value), compared with 531 years at our estimated maintenance rate and 469 years if phosphorus deficits were alleviated. More judicious use of phosphorus fertilizers to account for soil Olsen phosphorus can help achieve optimal production without accelerating the depletion of phosphorus reserves.

Wind power deviation charge reduction using long short term memory network

High penetration of variable generation like wind in modern power systems results in frequent load-generation imbalances. Additional spinning reserves and balancing services are deployed to reduce or avoid such imbalances. However, these additional balancing services result in increased total operation costs and it is generally shifted to Wind Power Generation Companies (WPGC) as Deviation Charges (DCs). The high DCs diminish the profitability of WPGCs. DCs are directly proportional to forecasting errors and can be reduced by enhancing forecasting accuracy. This paper proposes a Long Short-Term Memory (LSTM) network to reduce DCs. LSTM is a special kind of recurrent neural network and it is capable of learning long-term and short-term dependencies effectively. Therefore, the LSTM network can produce minimal error wind power forecasts and this helps to reduce DCs. The performance of the proposed LSTM network is realized using the real system data. Results obtained from the proposed LSTM model are compared with various forecasting models like ARIMA, ANN, and SVR. The comparison shows that the proposed LSTM model shows the least total DCs on most of the days followed by ANN, SVR, and ARIMA. The proposed LSTM, ANN, SVR, and ARIMA models show an average total DC of 6194.25$, 8459.32$, 15822.22$, and 38269.89$ respectively. Thus, the proposed LSTM model is capable of reducing 517.82%, 155.43%, and 36.56% DCs from ARIMA, SVR, and ANN models respectively, and helps the WPGCs to enhance their profitability.

FORECASTING ORF BY THE MARTOS METHOD AND THE STATISTICAL METHOD USING THE EXAMPLE OF DEPOSIT X

The article discusses the effectiveness of the Martos method and the statistical method for predicting oil recovery factor using the example of the X field. Today's values of oil recovery factors (ORF) for Triassic horizons were determined taking into account the active water pressure regime with artificial maintenance of reservoir pressure (RPM) and the drilling of 16 new production wells. This approach required a revision of ORF values due to the transition to natural reservoir development and the cessation of maintaining reservoir pressure by water injection. The failure to drill new wells has also had a significant impact on ORF. At current production, when 44.7% of the field's reserves have been extracted, and taking into account the remaining reserves, the development period of the field will not exceed 42 years. It is also planned to increase the number of hydraulic engineering measures to expand drainage zones and involve additional reserves in development. Having compared the two methods for calculating ORF, we can conclude that although V.N. Martos’ method is based on reservoir parameters, and the statistical method uses historical data, the results of their calculations differ slightly.

Sports Tournament Design as a Source of Economic Impact (Through the Example of Russian Premier League)

In today's restricted environment, sport continues to face a lack of funding and to be perceived as an industry that can survive without support. Meanwhile, numerous studies have proven that sport is not about significant investments only, but also creates an economic impact. The aim of this work is to consider such a specific driver of economic impact as tournament design and evaluate the corresponding impact through the example of the Russian Premier League (RPL). The research hypothesis states that changing the design of the RPL tournament will lead to an increase in the total revenue of participating teams, in consumption in the host cities and a reduction in greenhouse gas emissions, which together will lay the foundation for an economic impact at the country level and for individual regions. The paper examines three reform scenarios, which differ in the assumptions made. The authors have developed a calculation model that quantifies the economic impact of these reforms. The main triggers are the attendance at RPL matches and its derivatives (the number of away fans, the distance traveled by away fans), as well as monetary metrics: ticket & travel costs, carbon unit costs. The impact is calculated as the difference between the results achieved in the current tournament design and in potential scenarios. The study showed that the current RPL design has significant potential for economic impact. Thus, the implementation of the Optimum scenario, which does not require additional calendar reserves, will create a positive economic impact in the amount of 479 million rubles. With additional calendar opportunities and implementing the “Maximum” scenario, the effect will be 932 million rubles. This study may be useful for managers of sports competitions, heads of regional and municipal authorities, as well as sports leagues and federations.

Grid Secondary Frequency Control by Fuzzy PI–PD Controller

This paper develops a new approach for controlling the frequency in a two-area power system using a fuzzy PI PD controller. Frequency stabilization is one of the important factors for any power system to operate efficiently and reliably. The fluctuating characteristics of RES, like solar PV and wind energy, due to changing atmospheric conditions, require additional reserves to compensate for fluctuations in generated power. With growing application of EVs and their charging requirement, charting huge loads may add to the power grid and lead to stability problems if not properly regulated. This paper coordinates EV charging into the secondary frequency regulation, aided by an enhanced fuzzy controller designed for dealing with fluctuating imbalances between electricity demand and generation. In this context, a control technique is suggested that incorporates the flexibility of fuzzy logic with the accurate PI and PD methods for control. The controller continuously monitors changes in frequency at each node in the power system network. The fuzzy logic works on uncertain input data in terms of prescribed linguistic variables and rules that allow it to achieve a reasoned output. The difference between the desired and actual frequencies alters the control variable through the PI component of the controller, while the PD component considers the rate of change of this error to make the system's response time better. The effectiveness of the fuzzy PI PD controller is proven through detailed simulation experiments under different operational conditions and disturbances. It can be rundown that the controller efficiently reduces these frequency deviations, which guarantees smooth and reliable operation of the two-area power system network. In addition, it can be seen that the controller has robust performance but is rather reactive to dynamical changes in system parameters. Case studies are included in the research to test the performance of the proposed control approach in reducing frequency deviations; simulation findings always prove its efficacy. This paper therefore presents a complex method of frequency regulation in power systems using fuzzy logic and combined PI PD control to deal with problems caused by RES integration and EV charging. The proposed technique enhances the frequency stability in order to enhance both the reliability and efficiency of power grid operations due to the ever-changing energy demands and conditions.

МОДЕЛИРОВАНИЕ ЭКОНОМИЧЕСКИХ ПРОЦЕССОВ: ВЛИЯНИЕ НА ИНВЕСТИЦИОННУЮ ПРИВЛЕКАТЕЛЬНОСТЬ И ТЕХНОЛОГИЧЕСКОЕ РАЗВИТИЕ КОМПАНИИ

Economic-technological development model of a company that includes unique economic technology level indicator is considered in the article. The research of economic technology level model allowed to identify investment attractiveness of a project in the company, while in medium-term it allowed to identify additional reserves in order to expand investment programs. At the same time economic-technological company development model, that was investigated via the PJSC “Mosenergo” allowed to analyze current economic-technological production processes and to summarize means of production.

Prediction of adverse clinical outcomes in pregnant women with severe and extremely severe forms of coronavirus infection

The objective was to identify prognostic criteria for unfavorable outcome in pregnant women with severe and extremely severe forms of COVID-19 and to build a model for predicting clinical outcome.Materials and methods. The cohort single-center retrospective study was conducted, which included 83 patients who were treated in the intensive care unit (ICU) from January 1 to December 31, 2021. Of these, 13 patients had an unfavorable outcome – death, and 70 patients with a successful outcome – recovery. The differences in the main clinical and laboratory parameters of patients of both groups during hospitalization in the ICU and on the 3rd day of treatment (Δ – delta) were analyzed.Results. The Cox regression analysis identified laboratory parameters, the difference of which (Δ) on admission to the ICU and on the 3rd day of treatment is associated with the development of the unfavorable outcome (death). These indicators were used as variables in a linear regression equation. The equation for calculating the prognostic index met the criteria of a statistically significant model (sensitivity 84.6 %, specificity 85.7 %, area under the operating characteristic curve (AUROC – Area Under Receiver Operator Curve) – 0.959 (95 % confidence interval [95 % CI] 0.918 – 1.0).Conclusion. The calculation of the prognostic index can be an additional clinical tool that allows one to predict the development of an unfavorable outcome, concentrate the work of a multidisciplinary team, attract additional reserves of a medical institution and/or evacuate such patients to high-level hospitals.

Sustainable future bonds: Boosting multilateral development banks lending and improving the global reserve system

AbstractMultilateral development banks (MDBs) are crucial players to finance a greener, more socially inclusive and sustainable future, given their unique financial model that provides low‐cost and long‐term investments in areas aligned with the Sustainable Development Goals (SDGs) and the Paris Climate commitments. To fulfill their potential, MDBs need a stepwise increase in financing, which has been a challenge given the reluctance of their shareholders to provide additional paid‐in capital. We present a novel proposal for MDB hybrid capital that is designed to boost MDB funding while supplying the international reserve system with a new safe asset, the Sustainable Future Bonds (SFB). Under the SFB proposal, a tiny fraction of the global foreign reserves would be rechanneled to MDBs, and given liquidity enhanced mechanisms, SFB would serve as an additional safe reserve asset for central banks' portfolios. As our conservative estimation shows, by deploying just 0.5 percent of global foreign reserves for the Sustainable Future Bonds, at least $45 billion per year in fresh capital to MDBs would be mobilized. At that pace, by 2030, MDBs will have $360 billion in capital injections, which, depending on their leverage capacity, could result in new lending from $1.6 trillion to $1.9 trillion.

Antioxidant feed additive Dihydroquercetin in the feeding of broiler chickens

Currently, the production of poultry products intended for healthy nutrition is relevant. Consumption of such products allows us to stabilize the metabolism in the body and improve human health. Raw meat is susceptible not only to rapid microbiological spoilage, but also to oxidative spoilage, which preservatives help combat. Oxidative processes reduce the shelf life of fi nished products due to the deterioration of organoleptic characteristics and nutritional value of products. Therefore, one of the modern trends in the production of poultry products for a healthy diet is a focus on the use of natural feed additives when obtaining raw meat, through the lifetime development of quality. The purpose of the work was to study the antioxidant feed additive Dihydroquercetin in feeding of broiler chickens. When carrying out a scientific and farm experiment using the method of analogous groups, 4 groups of broiler chickens (control and three experimental) were formed at one day of age. Chickens of the 1st control group received only special compound feed as the main diet (MD), chickens the 2nd experimental group in addition to the MD received the antioxidant additive Dihydroquercetin in the amount of 0,50 g per 100 g of compound feed, chickens the 3rd group received 0,75 g per 100 g of compound feed and chickens of the 4st group received 1 g per 100 g of compound feed. It was found that the studied antioxidant additive contributed to better realization of the productive potential of poultry, increasing the livability of livestock, increasing meat productivity and improving the quality of meat raw materials. It has been proven that there is no negative impact of the feed additive on the main safety indicators of broiler chicken meat. Additional reserves have been identifi ed for increasing the economic effi ciency of broiler chickens rearing and producing of meat products from the resulting raw materials.

Wind Power Deviation Charge Reduction using Machine Learning

High penetration of wind power plants in power systems resulted in various challenges such as frequent system imbalances due to highly uncertain and variable wind generation. Additional spinning reserves and specific balancing products such as flexible ramp products are used to handle such frequent imbalances. Incorporation of these ancillary services leads to increased total operational costs. Increased operational costs should be transferred to wind power producers as it is caused by wind power plants. This leads to penalizing the wind power producers for the deviation of power generation from forecasts, called deviation charges. These deviation charges can be reduced by improving the forecasting accuracy. Existing forecasting models show performance in terms of error matrices. Such error matrices do not indicate the financial loss associated with it. This can be overcome by expressing forecasting performance in terms of deviation charge and it will directly encourage wind power producers to improve forecasting accuracy or arrange reserves to accommodate the error. This paper proposes a backpropagation-based artificial neural network model for reducing deviation charges in this context. An analysis is conducted on the data collected from the Bonneville Power Administration (BPA) Balancing Area. Seasonal analysis (Spring, Summer, Fall, and Winter) is conducted to show the performance of the proposed model throughout the year. The proposed model performance is compared with linear regression and ARIMA models. The comparison shows that the proposed ANN model gives the least deviation charges in the Spring, Summer, and Winter seasons and deviation charges in the Fall season are higher than the ARIMA model.

Analysis of a 131-year longitudinal dataset of the Eurasian otter Lutra lutra in Hong Kong: implications for conservation

AbstractHong Kong is one of the busiest metropolises, and the Eurasian otter Lutra lutra is one of its most threatened species. We collected published data for 1890–2020 to document changes in local otter abundance and distribution over time. The 108 records revealed new distribution data and showed that decline began as early as the 1930s. The local Eurasian otter is strongly associated with coastal and alluvial wetlands, and its last refugium, the Yuen Long floodplain draining the Mai Po Inner Deep Bay Ramsar Site, has always been a critical habitat. Our analysis suggests that hunting is unlikely to be a major cause of the otter's decline. Rather, dependence on lowland wetlands makes it particularly susceptible to habitat loss caused by increasing urbanization. Auxiliary infrastructures and water pollution have also exacerbated wetland degradation to the detriment of otters and their prey. There is a need for greater cooperation amongst government agencies and landowners to guarantee otter survival: priority steps include the establishment of additional and interconnected wetland reserves, better stakeholder engagement and enforcement efficiency to tackle entrenched pollution problems, and flood prevention schemes that preserve or restore functional riverine ecosystems within critical otter habitats. The current otter distribution range has been earmarked for development in a government-led mega urbanization plan; the plight of the local Eurasian otter needs to be widely publicized to garner stakeholders' support and galvanize immediate conservation actions across society.

STATISTICAL ASPECTS OF THE STUDY OF THE DYNAMICS OF INDUSTRIAL ENTERPRISES DEVELOPMENT

The article presents practical aspects of statistical research of the dynamics of development of industrial enterprises. It is determined that the main task of a statistical study of industrial enterprises is to determine the volume of industrial production, its structure; analysis of plan implementation by volume and assortment, grade, completeness, rhythm; identification of additional reserves. It is proved that in order to raise the level of industrial production statistics in Ukraine, it is necessary to make certain changes in the proportions of individual industries, and they should be consistent and interrelated. The study found that the main factors of industrial recovery will be: a gradual improvement in the situation on world markets, the resumption of production in certain sectors of the economy, improvement of the financial condition of enterprises, as well as an increase in investment and consumer demand. The following mathematical and statistical methods are used depending on the purpose of the statistical study and the nature of the source data: 
 1) mathematical methods of quantitative characterization of relationships: correlation and regression analysis; operations research and queuing theory; economic cybernetics; classical methods of elementary mathematics; simulation modeling; functionally hierarchical (forecast scenarios); methods of structural analogy; method of expert estimates; 
 2) statistical methods of quantitative characterization of relationships: analysis of variance; correlation analysis; method of analytical groupings; rank correlation; complex statistical coefficients; statistical equations of dependencies; statistical indices; indicators of dynamics analysis.
 When choosing statistical methods for studying socio-economic phenomena, it is necessary to take into account their interconnectedness and interdependence. Any phenomenon is the result of a certain set of causes and is the cause of other phenomena and processes. Therefore, the statistical study of the interrelationships of economic phenomena and processes should be approached comprehensively, trying to classify a wide range of methods that allow them to be quantified.

Assessing the relation between financial performance and long-term bank loan interest rates for healthcare providers in the Netherlands: a panel data analysis

The Dutch health system is financed predominantly by commercial bank loans, especially after the market-oriented reform in 2006, when government investment guarantees were abandoned. Commercial capital markets were envisaged to improve efficient capital allocation and management. We analyzed the effects of commercial bank loans on interest rates, investments and allocative efficiency in the Dutch healthcare sector. We aimed to explain variation in interest rates by financial performance of healthcare providers, hypothesizing that the reform reduced interest rates for financially well-performing providers. Using financial data from publicly available annual reports, we explored the effect of financial performance on long-term loan interest rates through pooled linear regressions. Our data showed that financial reserves have steadily increased, although profitability margins have declined since 2011–2013 (depending on the sector). While nominal interest rates have generally declined since 2006, the risk surplus on healthcare loans has steadily increased. Furthermore, we observed no significant relation between the financial performance of healthcare providers and interest rates on capital loans. Maintaining additional financial reserves provided no apparent benefit to capital costs. This suggests that healthcare providers may consider whether financial reserves should be maintained at current levels or can better be used for direct investments. Moreover, healthcare policymakers should evaluate whether the increase in risk surplus combined with an apparent lack of reward for financial scrutiny is a desired outcome of the reform.

BP’s Argos FPU Offers Fresh Lessons for the Future of Deepwater GOM Projects

Tipping the scales at well over 60,000 tons, BP’s Argos platform is a giant among giants in the deepwater US Gulf of Mexico (GOM). Standing 27 stories tall, the platform has a deck the length and width of an American football field and is one of BP’s largest in the region. One-time KBR subsidiary GVA designed the semisubmersible, the centerpiece of the supermajor’s $9 billion Mad Dog II project built to unlock additional production potential of the Miocene-aged reservoirs estimated to hold more than 5 billion bbl of oil in place. But that wasn’t always the plan. Over a decade ago, BP’s Mad Dog II looked quite different. On paper, the producer was looking at an all-subsea development tied back to another large spar platform—dubbed Big Dog—to host the additional reserves. The development plan envisioned a massive truss spar. Its topsides would need to be installed via three separate offshore lifts then fully integrated at the field site. Any offshore heavy lift is an execution risk. In 1998, an accident while lifting the south module onto Texaco’s Petronius compliant tower in the GOM resulted in the loss of that section of the topsides and delayed the project for a year and a half. That module weighed 3,600 tons. Another hesitation for BP? The price tag. All-in, the spar-based Mad Dog II solution was estimated to cost around $19 billion. That included 30-plus wells. Ultimately, the spar concept was scrapped, and BP moved back to square one and a blank sheet of paper. “The reserves were there,” said Chris Ruthven, project general manager, Mad Dog II. “We knew the reserves were there. In fact, ironically, the team developed the field with the smallest of the four big platforms that BP did back at that point in time: Thunder Horse, Holstein, Atlantis, and Mad Dog. It was the smallest, but ultimately, it was the second-biggest field. It turned out to be huge. All that appraisal showed we’ve got a lot of reserves. So, we went back and went with an analog to Atlantis. Atlantis was seen as a good fit requiring much less offshore integration work. Operations loved the asset, and it was a very safe design. We landed on that concept, and we tried to keep it almost pretty much the same in terms of the overall layout of the facility, but it’s a little bit bigger footprint.” Mad Dog proper was discovered in 1998 via an exploration well in over 6,100 ft of water located in Green Canyon Block 826. The well was drilled to a measured depth of 22,410 ft and encountered around 215 ft of hydrocarbon-bearing Miocene reservoirs. The discovery was followed by a 1999 well drilled to a total depth of 22,410 ft and a further successful appraisal well in February 2000. Mad Dog, covering Green Canyon blocks 825, 826, and 782, was sanctioned as a spar-based development in 2002. The project came online in early 2005.

Investment into Individual Farming Households as a Requirement of Ukrainian Food Security

The aggravation of the food crisis in the world highlights the problem of finding additional reserves to increase food production. In this context, personal farms of Ukraine attract special attention. They ensure the production of much of the country’s food; contribute to the employment of peasants and the development of rural areas. The aim of this article is to assess the resource and production potential of private farms, as well as to justify the feasibility of using their existing investment instruments. General scientific and special methods are used in the work. The main emphasis is on assessing the resource and production potential of the studied categories of farms. Methods of structural analysis and evaluation of time series have made it possible to establish the link between the level of crisis phenomena and the growing importance of personal farms in the country’s food supply, as well as to compare their potential with the potential of the agricultural sector of the country as a whole. Results of the research. It was found that personal farms play an important role in the country’s food security, as well as in the formation of a system of self-employment and socio-cultural relations. It is established that such farms successfully provide food needs for the rural population, as well as sell surplus products on the market. It has been proved that these economic entities have significant resource and production potential, but expanding the scope of their activities requires a number of measures, including changing the public policy to support farms, as well as ensuring active investment in their development. In the process of assessing the production and resource potential of private farms, it was determined that they have significant resources to invest their own resources in their development. Recommendations on intensification of investment activity of personal peasant farms are generalized; as a result, a number of measures, which can be applied in Ukraine, are resulted. It is established that the key areas for the application of these measures are information and educational activities, strengthening the competitive position of private farms, improving access to public and private investment, as well as diversification of activities. It was agreed that the complex combination of these measures within a single strategy would allow achieving maximum results in terms not only of food supply of the country, but also the development and improvement of welfare of individual rural households.