A REVIEW OF PREDICTIVE ANALYTICS IN THE EXPLORATION AND MANAGEMENT OF U.S. GEOLOGICAL RESOURCES
In an era where technological advancements are reshaping the landscape of resource management, this paper delves into the transformative role of predictive analytics in the exploration and management of geological resources in the United States. The study's backdrop is set against the burgeoning need for innovative approaches in geological exploration, driven by environmental, economic, and technological imperatives. The primary aim of this comprehensive review is to dissect the multifaceted contributions of predictive analytics in enhancing the efficiency, accuracy and sustainability of geological resource exploration. The scope of the paper encompasses a detailed examination of the integration of predictive analytics in geological exploration, focusing on its economic benefits, environmental sustainability implications and adherence to legal and ethical standards. Methodologically, the study employs a qualitative analysis of existing literature and case studies, juxtaposing traditional exploration methods with modern predictive analytic techniques. It further investigates the economic impact of predictive analytics implementation, the role of predictive models in identifying new geological resources and the strategic implications for sustainable resource management. The findings reveal that predictive analytics significantly enhances risk assessment, resource identification, and environmental management in geological exploration. The economic analysis underscores the cost-effectiveness and efficiency of predictive analytics, while strategic implications highlight the need for an integrated approach to sustainable resource management. Conclusively, the study recommends policy reforms and regulatory frameworks that align with technological advancements to ensure sustainable and prosperous geological resource management. It advocates for embracing advanced tools to navigate the complexities of resource exploration and management, ensuring a balance between economic viability and environmental sustainability.
Keywords: Predictive Analytics, Geological Exploration, Resource Management, Sustainability, Technological Advancements, Policy Reforms.
How to Cite
Copyright (c) 2024 Michael Ayorinde Dada, Johnson Sunday Oliha, Michael Tega Majemite, Alexander Obaigbena, Preye Winston Biu
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.Fair East Publishing has chosen to apply for the Creative Common Attribution Noncommercial 4.0 Licence (CC BY) license on our published work. Authors who wish to publish their manuscript in our journal agree on the following terms:
1. Authors retain the copyright and grant us (Fair East Publishing and its subsidiary journals) the right for first publication with the work licensed under a Creative Commons Attribution (CC BY) License which permits others to share the work with an acknowledgment of the work’s authorship and initial publication in this journal. Under this license, author retains the ownership of the copyright of their content, but anyone is allowed to download, reuse, reprint, modify, distribute, and/or copy the contents as long as the original authors and source are cited. No permission is required from the publishers or authors.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal’s published version of the work (for example, publishing it as a book or submitting it to an institutional repository), with an acknowledgment of its initial publication in Fair East Publishing owned journals.
3. We encourage our authors/contributors to post their work online (such as posting it on their website or some institutional repositories) prior to and during the submission process since it produces scholarly exchange and greater and earlier citation of published work.