Advance Injection Strategy Optimization: Maximize Benefit-Cost Ratio by Integration of Economic Spreadsheet in Excel to Assisted History Matching Using Python Scripting

Oil prices see large fluctuations peculiarly over the last eight years due to natural disasters, political instability, and Covid-19 pandemic shock. These prompt to anxiety towards expenditure in planning and forecasting of a field development plan (FDP). Economic optimization of a reservoir under water drive can be extremely tedious and time consuming especially for complex field. Traditionally, upon completion of forecast optimization on fluid production, reservoir engineer willhand over the reservoir models to petroleum economist for economical evaluation. If the chosen development strategy is not economically viable, the model strategies will have to be updated, and continue the repetition of financial evaluation all over again. Hence, this paper established an automated workflow that diminished the dilemma on iterations obligation between simulation runs and financial reviews in searching for most efficient waterflooding strategy. The automated workflow is accomplished by bridging three tools together seamlessly utilizing python scripting. These include the cash flow economic spreadsheet model, the dynamic simulator, and an assisted uncertainty analysis tool. The process first started with defining the economic parameters such as OPEX, CAPEX, oil price, taxes, discounted rates, and other financial parameters on an annual basis in spreadsheet. The uncertainty parameters: water injection rate, maximum water cut, and injection duration will be evaluated during forecast optimization to produce project efficiency indexes: Net Present Value (NPV) and Benefit-Cost Ratio (BCR). This integration was achieved by python script that automatically creates a coding path which exchanges simulation production and economic spreadsheet data at every simulation time step and each development strategy, that require no manual intervention. The integrated economic-dynamic model workflow has successfully applied on West Malaysian field and Olympus model, a development strategy that maximize oil recovery without neglecting cost of water disposal, storage for total water produced from the reservoir. This paper successfully identified the most efficient waterflooding strategy and production constraints for each well using BCR as objective function for optimization. The optimum development scenario does have a BCR which is more than 2 which show that investment on that particular development strategy is profitable. The results also demonstrated a crucial impression that the highest oil cumulative production may not results in high BCR due to cost involvement in resolving water production and field maintenance services. This paper outlined the methodology, python scripting codes, and how integration automation works that successfully optimized an injection strategy in a development project using economic model from third-party application. The results of this automated workflow demonstrate a successful utilization of new technologies and simple customize programming knowledge that promote cross-discipline integration for enhanced work-time efficiencies in problem solving that is suitable for all reservoir model type to determine its success rate and economic viability during FDP.

Competition Laws and Regulations For a Digital Industry Platform

During the last two decades, several nations have enacted or reinforced competition legislation. In most countries, at the same time, indigenous sectors are under ever-greater import demand. Towards an analysis, to monitor over time and the presence of imports and the number of domestic companies, on the influence of competitive legislation and rules (CLR) on the domestic competition for several nations. To see the direct impact of the Competition Law on competitiveness as industries with more import exposure or bigger local businesses are tending to be more competitive. However, it should be concluded that industries operating under competition legislation tend to have more domestic companies. This implies that by stimulating entrance, competition legislation may have an indirect influence on domestic competition. In terms of the function of government in industrial growth and the position of the public and private sector in country industrialization, the comparative role for small and big industries, an industrial policy may be described as the declaration of importance. It is essential to introduce new laws and regulations to encourage competition and constrain large industries. The problems of Industry 4.0 will be met through digitalization and automation. The vast amount of data produced on the industrial Internet of Things (IIoT) must be collected, understood, and used. This is precisely what the digital company does by integrating the real world with the digital world. Therefore, the endless quantity of data enables the industry to make the CLR-IIOT technique more sustainable by employing final resources efficiently. Competition results in greater economic dynamic efficiency through innovation, technical advancement, reduced prices, and improved quality and customer service. Competition legislation is necessary since the market may be affected by faults and distortions, and diverse consumers may have recourse to anti-competitive actions such as cartels, abuse of predomination, etc.

The Hegemony’s Contest in the South China Sea

Constantly analyzed in scientific, theoretical, and empirical studies, the “ Asian Mediterranean” region has received renewed attention as a consequence of the rise of China. China’s emergence combines its strong economic dynamic with increased confidence, positioning it as a potential regional hegemony. On that conceptual basis, this study aims to answer whether a power transition has already occurred in the South China Sea and how the process of a regional hegemonic transition took place. Through an examination of the instruments used by the United States and China to exercise power, articulated with the power transition theory, it establishes that a transition in the South China Sea dispute could have already occurred. However, the study disclaims that Beijing’s evolution and sudden change of behavior aim to overthrow the U.S. global leadership but rather intends to reclaim its position of regional hegemony.

A Fuzzy Economic Dynamic Model

In the study presented here, fuzzy logic was used to analyze the behavior of a model of economic dynamics that assumes income to be in equilibrium when it is composed of consumption and investment, that is, when savings and investment are equal. The study considered that consumption and savings depend on the income of the previous period through uncertain factors, and, at the same time, that investment is an uncertain magnitude across various periods, represented as a fuzzy number with a known membership function. Under these conditions, the model determines the factor of income growth and investments required to maintain equilibrium, as well as the uncertain values of income for the different periods, expressed through fuzzy numbers. The study also analyzes the conditions for their convergence and the fuzzy value that income represents in equilibrium.

An E-Commerce Economic Dynamic Data Evaluation Model Based on Multiuser Demand Constraints

Forecasting the future earnings of listed companies based on multiuser constraints is the focus of investors, securities dealers, creditors, and management. Some empirical studies at home and abroad indicate that the financial reports issued by listed companies regularly contain information about future changes in earnings. On this basis, this article uses the Bayesian dynamic regression model to predict the changes in the future earnings of listed companies and compares the results with traditional analysis models. Through case analysis, it can be seen that the prediction effect of the Bayesian dynamic regression model is generally better than that of the traditional regression model. The Bayesian model can better predict the results, and through the prediction results, it can also establish an evolutionary game model of the industrial innovation replication dynamic system, which can assist enterprises in making profit decisions.

Economic Dynamic Modelling of Climate Policy in Poland

Poland is responsible for 9% of CO2 emission in the European Union (EU), making it the fifth biggest emitter in the region. The energy sector is dominated by electricity produced from coal (around 70%). The country currently uses massive subsidies to boost the coal sector. We propose a dynamic intertemporal hybrid general equilibrium model to simulate the economic effects of sector regulations and new policy targets within environmental taxation scenarios, by accounting for a complex set of linkages between the energy sector and other components of the economy. Our simulation results suggest that positive economic growth is possible with a realistic energy mix, but it will not offer considerable emission reduction, as required by the European Commission. In the short-time horizon, the best choice is renewable energy sources indicated by less capital-intensive technologies (such as biomass). In the long-time horizon, more capital-intensive technologies (such as wind turbines) will be a better choice for economic growth. Carbon tax plays a crucial role in optimal energy mix targets, since its elimination ceteris paribus implies negative economic growth.

An economic D-RTO for thermal solar plant: analysis and simulations based on a feedback linearization control case

This work proposes an economic dynamic real-time optimization (D-RTO) strategy to control a solar collector eld in order to maximize the amount of thermal power energy delivered to multi-eect seawater distillation plant. A validated model of the compound parabolic concentrator collector eld of the AQUASOL plant, available at the Plataforma Solar deAlmera (Spain), is used as case study. The optimization algorithm is based on receding horizon optimization problem, in which an economic function takes into account the energy produced by the solar plant and the electricity consumption costs by the water pump. The D-RTO strategy is compared to a feedback linearization controlling in dierent temperature setpoints, intending to analyze economic benets and viability of the proposed algorithm. Simulation results showthe D-RTO algorithm is capable of handling process disturbances and operating in economic benet conditions, bringing good perspectives for implementation in real applications.