[ad_1]
This study creates an evaluation system based on an interpretive structural model to form a CIPP for comprehensive oil investment potential evaluation. This workflow integrates elements from petroleum geology as well as political, economic and cultural aspects and adapts complex models commonly used in other fields for this assessment. In doing so, we fill the research gap in the area of transboundary oil investments at the basin level and increase the focus beyond the primarily economic aspects that have dominated past research in this area (e.g.11, 12, 15, 30).
This study is mainly innovated by quantitatively evaluating 17 representative oil fields in Africa through an integrated assessment model and distinguishes between these fields in terms of exploration, development potential and investment attractiveness of oil resources. The purpose is to identify and compare differences. In this study, we applied AHP (Analytic Hierarchy Process), Entropy Weight Method, and Fuzzy TOPSIS method to build a comprehensive evaluation system that quantitatively analyzes CIPP in each basin from three aspects: exploration status, development production, and local environment. To do.
This result suggests that the Iridji Basin and the Ivory Coast offshore basin are highly favorable for investment and development in oil resource exploration, especially for various companies, including China. This attraction is based not only on its rich oil resources and good infrastructure, but also on its political and economic stability. However, basins such as the Tanzania Offshore Basin, the Ruvuma Basin, and the South West Africa Basin are rated as options that require very careful investment consideration. They rank low on the overall level, and their limitations do not limit him to only one aspect. This approach will help Chinese or other oil and gas companies gain a clearer understanding at the basin level when investing in upstream oil and gas in Africa.
The optimal results of this ranking are derived from extensive experience and closely align with our expert opinion, which is based on thorough research and analysis of a large number of expert results. Based on our comprehensive assessment, we believe that the Iridji Basin and the Ivory Coast offshore basin are the most favorable areas at the basin level for investment and development by Chinese oil and gas companies. These basins have been receiving global oil and gas investment for some time and have relatively well-developed infrastructure and regulatory frameworks. With effort, we can successfully secure a share of the profits. However, although the Tanzania Basin, Ruvuma Basin, and Southwest African Basin have large oil and gas reserves, the local development environment is relatively harsh, and there are concerns about political risks and the investment environment. Therefore, the model analysis is amenable to manual interpretation with a very cautious approach to these areas.
This study uses the standard deviation method to classify 17 African oil fields into four levels based on exploration status, development and production, and regional environment. This classification helps investors and decision makers identify specific investment opportunities and assess potential risks. Basins are ranked from best (Type II) to best investment value, to those requiring improvement (Type III), to least performing (Type IV) on all three indicators. , reflecting different investment attractiveness and development potential. Furthermore, Spearman rank correlation analysis shows a moderate positive correlation between exploration status and development and production, with a weak correlation with the local environment. This highlights the importance of exploration status as a predictor of basin development potential, but also the need to consider a wide range of factors for comprehensive investment decisions. This approach will help with more accurate resource allocation and risk management of oil and gas investments in Africa.
This study enhances the ranking of oil and gas exploration potential across different basins in Africa, including detailed dimensional rankings and comparisons between same-level dimensions. This aspect was not present in previous studies, even in the global oil investment field.8, 9, 10which was mainly limited to aspects of financial investment.16, consideration of geological aspects of oil and gas at the basin and downstream infrastructure level is lacking. Furthermore, complex decision-making models have rarely been applied to such oil and gas investments.23,24 . Our work differs slightly in analysis details and incorporates more parameters for evaluation and classification compared to similar algorithms in other fields, but it also reduces decision-making related to complexity. Effectively helps prioritize analysis goals.27,28. The application of this model provides a very good example of its integration with real investment behavior and can serve as a reference for similar decision-making areas and stimulate research on the application of similar models.
This approach improves decision-making accuracy, addresses uncertainty, provides clear and interpretable results, and ultimately facilitates more effective decision-making. This advanced approach contributes to algorithmic advancement by handling complexity and enhances its transferability to different contexts, as well as its applicability in decision-making across industries and geographies. More importantly, it is possible to evaluate in detail the ranking of each basin based on various sub-indicators and determine its priority status.
This modeling methodology focuses on assessing the oil investment potential of oil and gas basins by leveraging the practical experience of Chinese companies’ overseas investments, especially considering the unique complexities in the mentioned aspects. It has been tailored for Africa. Comparisons across regions, such as the Middle East and South American basins, are not considered within the framework of this model. For evaluation of specific watershed groups, indicators with high commonality can be excluded in favor of new indicators with more heterogeneity, and human interpretation and real data can be integrated to rebalance the weights. . This model emphasizes the fusion of subjective and objective evaluations in the ranking of indicators, and moves away from the traditional separation of subjective and objective indicators to comprehensively and effectively integrate both evaluations. has a revolutionary impact on weight calculations.
This evaluation system provides the practical application of a new combined method for evaluating African oil basins. By classifying and quantitatively scoring these basins, oil investment companies can not only better understand each basin’s specific strengths and weaknesses, but also systematically assess its potential risks and returns. I can. This workflow is based on complex evaluation model techniques that have already been applied in other fields.23, 24, 25, 26. This adaptation is expected to significantly contribute to investment in upstream petroleum resources.
Furthermore, classification and correlation work enriches this comprehensive evaluation system. As a result of the correlation investigation, it was found that there is a certain interdependence among the three classification indicators: “exploration status,” “regional environment,” and “development/production.” Specifically, the first two show a moderate positive correlation, and the latter two are also related. This suggests that oil basins with low oil reserves but high exploration potential already have significant involvement from international oil companies, or are likely to be given due consideration by local governments.
Although this study effectively assesses the investment potential of oil basins, it also highlights limitations that should be addressed in future research. First, current metrics need to be refined to better capture the complexity of investment decisions, especially when considering multiple factors such as the economy and the environment. Additional data such as geological discoveries and market demand should be included. Second, models for assessing CIPP have limitations, particularly in the interpretation of metrics such as exploration well density and success rate. A high value does not always mean a high probability. This is primarily due to deviations of extremely high or low data levels from the study’s expectations. It is assumed that within reasonable limits (all indicators apply here) these values show a proportional relationship and that no indicator experiences excessive conditions. Third, advanced data analytics such as big data and AI should be used to improve the accuracy of investment and risk predictions.
Finally, robust model validation is essential to minimize bias and provide a stable basis for decision-making. Due to the subjective nature of the evaluation process, the results presented may be biased. However, qualitative rankings of subjective interpretations rely on a thorough understanding of the local context, strong domain expertise, and extensive discussion followed by multiple sorts and comparisons to reduce errors. It is important to note that We suggest several measures for future efforts to further reduce bias. These include incorporating independent data sources for cross-validation, implementing blind expert reviews or expert validation panels, utilizing Monte Carlo simulations to address uncertainties, conducting sensitivity analyses, and comparing cases. This includes verification of results through studies. These measures will increase the credibility of investment strategies in the field of oil exploration and development.
This study will help China and other countries deepen their social policy analysis and planning related to African oil and gas investment decisions. Streamlining Africa’s oil and gas investments is critical to strengthening energy security, promoting the Belt and Road Initiative, and strengthening economic and political ties between China and Africa. These investments will not only increase China’s diplomatic influence in Africa through deepening energy cooperation and strengthening friendly relations with African countries, but also support China’s global foreign policy. For African countries, rational oil and gas investment can significantly boost regional economic development and job creation, particularly in oil and gas development and infrastructure. Furthermore, infrastructure improvements not only boost Africa’s economic growth and improve living standards for local populations, but also contribute to the Sustainable Development Goals. In the long term, China-Africa energy cooperation is expected to create a mutually beneficial situation, strengthen bilateral economic cooperation, and promote the stability and development of the world energy market.
[ad_2]
Source link
