Project Abstract

This project aims to utilize advanced seismic attribute analysis techniques to enhance the identification and characterization of potential hydrocarbon reservoirs within a sedimentary basin. Seismic data, which provides a wealth of information about the subsurface geology, is a crucial tool in the exploration and development of hydrocarbon resources. By applying various seismic attributes, this study seeks to uncover hidden patterns, anomalies, and facies changes that can provide valuable insights into the presence and distribution of hydrocarbon-bearing formations. The importance of this project lies in the significant impact it can have on the oil and gas industry. Accurate and reliable identification of hydrocarbon reservoirs is essential for efficient exploration, development, and production activities. Traditional seismic interpretation methods often rely on the subjective analysis of seismic data, which can be time-consuming and may miss critical features. This project aims to overcome these limitations by leveraging advanced computational techniques and machine learning algorithms to automate the seismic attribute analysis process, leading to more objective and comprehensive interpretations. The primary objectives of this project are threefold 1) to develop a robust and adaptable seismic attribute analysis workflow that can be applied to various sedimentary basins; 2) to integrate multiple seismic attributes, including amplitude-based, impedance-based, and geometric attributes, to enhance the identification of hydrocarbon-bearing formations; and 3) to incorporate geological and geophysical knowledge to improve the interpretation and validation of the seismic attribute analysis results. The project methodology will involve the following key steps 1. Data acquisition and preprocessing Gathering seismic, well log, and other relevant geological data from the target sedimentary basin, followed by data quality control and preprocessing. 2. Seismic attribute computation Calculating a suite of seismic attributes, including but not limited to acoustic impedance, reflection strength, curvature, and spectral decomposition, to capture various geological and geophysical signatures. 3. Attribute integration and interpretation Combining the computed seismic attributes using advanced statistical and machine learning techniques to identify potential hydrocarbon-bearing zones, distinguish lithological variations, and delineate structural features. 4. Validation and calibration Integrating well log data, core analysis, and other geological information to validate the seismic attribute analysis results and refine the interpretation. 5. Uncertainty quantification Implementing robust uncertainty quantification methods to assess the reliability and confidence levels of the seismic attribute analysis, enabling informed decision-making. The expected outcomes of this project include the development of a comprehensive seismic attribute analysis workflow, the identification of promising hydrocarbon-bearing zones within the target sedimentary basin, and the generation of high-quality 3D geological models that can guide future exploration and development activities. Furthermore, the project's findings will contribute to the broader understanding of the geological history and depositional environments of the basin, potentially leading to the discovery of new hydrocarbon resources and optimizing the exploitation of existing fields. This research project has the potential to significantly impact the oil and gas industry by providing a robust and efficient seismic attribute analysis methodology that can be replicated and adapted to various sedimentary basins worldwide. The successful implementation of this project will not only enhance hydrocarbon exploration efforts but also contribute to the sustainable and responsible development of energy resources, ultimately benefiting both the industry and society as a whole.

Project Overview