A Practical Model for Water Injection Evaluation and Optimization in Typical Offshore Reservoirs Considering Formation Heterogeneity Based on Experimental Study

A major concern with water injection in offshore oil reservoir is the water breakthrough. The formation heterogeneity is the main reason for it. In order to evaluate the water injection efficiency, a visualized 2-D experiment was carried out to obtain the distribution law of injected water and the variation of injection parameters in homogeneous and heterogeneous formation. In addition, a coupled wellbore/reservoir model was established by applying microelement method, superposition principle and imaging. This model considers the formation heterogeneity and pressure drop caused by wellbore friction. The visualized 2-D sand filling displacement experiment indicates that the injection rate at the horizontal well heel is greater than that at the toe and the injection front is more irregular in heterogeneous formation. The injection rate and injection pressure distribution along the horizontal well are obtained analytically based on the proposed model, the results show that the injection rate at the two sides of the wellbore is much higher than that in the middle when the formation is homogeneous and the wellbore is infinite-conductive. In this case, the injection rate curve along horizontal well shows a "U" shaped distribution. When a finite-conductive horizontal wellbore is considered, the injection rate at the heel of the wellbore is higher than that of the toe, although the injection rate curve along horizontal well also exhibits a deformed "U" shape distribution. For the formation heterogeneities along the horizontal wellbore, the injection rate distribution curve is not continuous anymore, but a deformed "U" shape is also observed for each wellbore segment. At last, the established model was applied to an ultra-heterogeneous offshore reservoir. It is concluded that the profile control effect of typical well is obvious. The results of this study are of great significance for the calculation of the injection rate profile and improving the water injection efficiency.

Modeling of the Heat Release Rate Curve of Rigid Plastic Combustibles Based on their Geometrical Properties and Constituent Materials

In this study, we conducted the modeling and generalization of the heat release rate of rigid plastic combustibles with respect to their geometrical properties. The modeling and generalization was carried out using the model proposed by Natori, which is based on the combustion behavior of wooden furniture. Previous studies that have reported the combustion of printers were used for the modeling of the heat release rate of rigid plastic combustibles. The reported heat release rate measurements of the printers were examined to determine their applicability to Natori's model. After their applicability was confirmed, to generalize the heat release rate curve, heat release rate parameters of the combustibles were analyzed with respect to their geometrical properties and constituent materials. The combustibles were classified into two groups based on their geometrical properties, and the fire growth rate, maximum heat release rate, and decay rate represented the heat release rate parameters. Furthermore, the parameters were analyzed as a function of the apparent density of the combustibles. The fire growth rate and maximum heat release rate exhibited a relatively evident correlation with the apparent density, which indicated that an accurate estimation of the heat release rate curve can be obtained from the external dimensions and weight of the combustibles.

The application of different term-structure models to estimate South African real spot rate curve

The purpose of this study is to investigate the suitable arbitrage-free term-structure model that might be able to fit the South African inflation-indexed spot-rate curve. The instrument has relatively less tradability in the market, which then translates into a lack of adequate data for bond valuation/pricing. Pricing deviations might give inflated/deflated projections on the value of government debt; consequently, higher estimated interest cost to be paid. A proper valuation of these instruments is mandatory as they form part of government funding/borrowing and the country’s budgeting processes in the medium term. The performance of newly developed non-linear multifactor models that follows the Nelson-Siegel (1987) framework was compared to the arbitrage-free Vasicek (1977) model and linear parametric models to assess any significant deviations in forecasting the real spot-rate curve over a short period. Models with constant parameters (i.e. linear parametric, cubic splines, Nelson-Siegel (1987) and Svensson (1994)) gave a perfect fit, they proved to marginally lose fitting capabilities during periods of higher volatility. Therefore, it could be concluded that the application of either Nelson-Siegel (1987) model or Svensson (1994) model on forecasting South African real spot-rate curve gave a perfect fit. However, for a solid conclusion to be derived, it is imperative to explore the performance of these models over a period of stressed market and economic conditions.

Does the slope of the yield curve of the interbank market influence prices on the Warsaw Stock Exchange? A sectoral perspective

The interest rate curve is often viewed as the leading indicator of economic prosperity in a broad sense. This paper studies the ability of the slope of the yield curve in the term structure of interest rates to impact the sectoral indices on the Warsaw Stock Exchange, using daily data covering the period from 1 January 2001 to 30 September 2020. The results of the research indicate an ambiguous dependence of the logarithmic rates of return of sub-indices on the change of the interbank interest rate curve. The only sectors showing a clear relationship of this type is energy and pharmaceuticals.

Assessment of Flood Susceptibility Using Support Vector Machine in the Belt and Road Region

Floods have occurred frequently all over the world. During 2000–2020, nearly half (44.9 %) of global floods occurred in the Belt and Road region because of its complex geology, topography, and climate. However, the degree of flood susceptibility of each sub-region and country in the Belt and Road region remains unclear. Here, based on 11 flood condition factors, the support vector machine (SVM) model was used to generate a flood susceptibility map. Then, we introduced the flood susceptibility comprehensive index (FSCI) for the first time to quantify the flood susceptibility levels of the sub-regions and countries in the Belt and Road region. The results reveal the following. (1) The SVM model used in this study has an excellent accuracy, and the AUC values of the success-rate curve and prediction-rate curve were higher than 0.9 (0.917 and 0.934 respectively). (2) The areas with the highest and high flood susceptibility account for 12.22 % and 9.57 % of the total study area respectively, and these areas are mainly located in the southeastern part of Eastern Asia, almost the entirely of Southeast Asia and South Asia. (3) Of the seven sub-regions in the Belt and Road region, Southeast Asia is most susceptible to flooding and has the highest FSCI (4.49), followed by South Asia. (4) Of the 66 countries in this region, 16 of the countries have the highest flood susceptibility level (normalized FSCI > 0.8) and 5 countries (normalized FSCI > 0.6) have a high flood susceptibility level. These countries need to pay more attention to flood mitigation and management. The above findings provide useful information for decision-making in flood management in the Belt and Road region. In the future study, higher quality flood points, and climate change factors should be considered.

Numerical and Experimental Fracture Mechanical Investigations of Clinchable Sheet Metals Made of HCT590X

In many areas of product manufacturing constructions consist of individual components and metal sheets that are joined together to form complex structures. A simple and industrial common method for joining dissimilar and coated materials is clinching. During the joining process and due to the service load cracks can occur in the area of the joint, propagate due to cyclic loading and consequently lead to structural failure. For the prevention of these damage cases, first of all knowledge about the fracture mechanical material parameters regarding the original material state of the sheet metals used within the clinching process are essential.Within the scope of this paper experimental and numerical preliminary investigations regarding the fracture mechanical behavior of sheet metals used within the clinching process are presented. Due to the low thickness of 1.5 mm of the material sheets, the development of a new specimen is necessary to determine the crack growth rate curve including the fracture mechanical parameters like the threshold against crack growth ΔKI,th and the fracture toughness KIC of the base material HCT590X. For the experimental determination of the crack growth rate curve the numerical calculation of the geometry factor function as well as the calibration function of this special specimen are essential. After the experimental validation of the numerically determined calibration function, crack growth rate curves are determined for the stress ratios R = 0.1 and R = 0.3 to examine the mean stress sensitivity. In addition, the different rolling directions of 0° and 90° in relation to the initial crack are taken into account in order to investigate the influence of the anisotropy due to rolling.

Assessment of Landslide Susceptibility using Weight of Evidence and Frequency Ratio Model in Shahpur Valley, Eastern Hindu Kush

This study assessed landslide susceptibility using Weight of Evidence (WoE) and Frequency Ratio (FR) model in Shahpur valley, situated in the eastern Hindu Kush. Here, the landslides are recurrent phenomena that disrupt the natural environment and causes huge property damages as well as human losses every year. These damages are expected to increase due to the high rate of deforestation in the region, population growth, agricultural expansion and infrastructural development on the slopes. Initially, the landslide inventory map was prepared from the SPOT-5 satellite image and was verified from frequent field visits. Seven landslide contributing factors including surface geology, fault lines, slope aspect and gradient, land use, proximity to roads and streams were selected. To analyze the relationship between landslide occurrence with its causal factors, WoE and FR models were used. Based on WoE and FR model landslide susceptibility zonation maps were prepared and reclassified into very low to very high landslide susceptible zones. Finally, the resultant maps of landslide susceptibility were validated using the success rate curve and prediction rate curve approach to validate the models.

Title: Modeling Study: Characterizing the Spatial Heterogeneity of the COVID-19 Pandemic through Shape Analysis of Epidemic Curves

Background: The COVID-19 incidence rates across different geographical regions (e.g., counties in a state, states in a nation, countries in a continent) follow different shapes and patterns. The overall summaries at coarser spatial scales, that are obtained by simply averaging individual curves (across regions), hide nuanced variability and blur the spatial heterogeneity at finer spatial scales. For instance, a decreasing incidence rate curve in one region is obscured by an increasing rate curve for another region, when the analysis relies on coarse averages of locally heterogeneous transmission dynamics. Objective: To highlight regional differences in COVID-19 incidence rates and to discover prominent patterns in shapes of incidence rate curves in multiple regions (USA and Europe). Methods: We employ statistical methods to analyze shapes of local COVID-19 incidence rate curves and statistically group them into distinct clusters, according to their shapes. Using this information, we derive the so-called shape averages of curves within these clusters, which represent the dominant incidence patterns of these clusters. We apply this methodology to the analysis of the daily incidence trajectory of the COVID-pandemic for two geographic areas: A state-level analysis within the USA and a country-level analysis within Europe during late-February to October 1 st , 2020. Results: Our analyses reveal that pandemic curves often differ substantially across regions. However, there are only a handful of shapes that dominate transmission dynamics for all states in the USA and countries in Europe. This approach yields a broad classification of spatial areas into different characteristic epidemic trajectories. In particular, spatial areas within the same cluster have followed similar transmission and control dynamics.Conclusion: The shape-based analysis of pandemic curves presented here helps divide country or continental data into multiple regional clusters, each cluster containing areas with similar trend patterns. This clustering helps highlight differences in pandemic curves across regions and provides summaries that better reflect dynamical patterns within the clusters. This approach adds to the methodological toolkit for public health practitioners to facilitate decision making at different spatial scales.