Project Abstract

This project aims to develop a robust and comprehensive approach to seismic inversion for the characterization of hydrocarbon reservoirs in complex geological settings. Accurate reservoir characterization is crucial for the effective exploration, development, and production of oil and gas resources, particularly in challenging environments where traditional methods may fall short. In complex geological settings, such as those with significant structural deformation, lateral heterogeneity, or the presence of igneous intrusions, the interpretation of seismic data can be particularly challenging. Conventional seismic inversion techniques often struggle to provide reliable estimates of key reservoir properties, such as porosity, permeability, and fluid content, which are essential for informed decision-making in the upstream oil and gas industry. This project aims to address these challenges by developing advanced seismic inversion algorithms that can effectively handle the complexities of diverse geological environments. The research will focus on integrating various geophysical and geological data sources, including well logs, seismic attributes, and structural information, to enhance the accuracy and reliability of the inversion process. The project will investigate the use of advanced machine learning and deep learning techniques to optimize the seismic inversion workflow, enabling the rapid and automated processing of large seismic datasets. This will involve the development of novel neural network architectures and training strategies tailored to the specific requirements of reservoir characterization in complex geological settings. Furthermore, the project will explore the integration of rock physics modeling and uncertainty quantification into the seismic inversion process. This will allow for a more comprehensive understanding of the uncertainties associated with the estimated reservoir properties, which is crucial for risk assessment and informed decision-making. The project's expected outcomes include the development of a robust and versatile seismic inversion framework that can be applied to a wide range of complex geological settings. This framework will provide oil and gas operators with reliable and high-resolution estimates of reservoir properties, enabling them to optimize exploration and production strategies, reduce drilling and completion risks, and ultimately enhance the overall efficiency and profitability of their operations. The research findings will also contribute to the broader scientific understanding of the relationship between seismic data and subsurface geological properties, particularly in structurally complex and heterogeneous reservoirs. This knowledge can be leveraged to improve the accuracy and reliability of various geophysical interpretation techniques, benefiting the entire upstream oil and gas industry. In conclusion, this project addresses a critical challenge in the field of reservoir characterization and offers the potential for significant advancements in the exploration and development of hydrocarbon resources. By developing innovative seismic inversion methods that can effectively handle complex geological settings, the project will have a transformative impact on the oil and gas industry, enabling more informed decision-making and ultimately contributing to the responsible and sustainable management of energy resources.

Project Overview