Advances in Seismic and Well Log in the Exploration in North Africa

In the last few years, exploration interest in discovering new hydrocarbon resources in North Africa’s various concessions has resulted in many new and important oil and gas reservoirs being found. However, tight reservoirs in different regions of the North African region are distinguished by their complexity and heterogeneity. Therefore, there are many challenges to reducing exploration costs and risk in order to identify those target zones with economically productive sand reservoirs of onshore and especially offshore hydrocarbon exploration in deep marine regions in North Africa and the Mediterranean. Hence, this chapter introduces several modern frameworks and methodologies based on using new and various modern techniques to improve the imaging of the gas channels, chimneys, and various features to reduce the exploration cost and risk. Examples are several classes of post-stack seismic attributes, partial-stack attributes through the Amplitude Variation with Offset (AVO) analysis, and various Machine Learning (ML) techniques such as supervised and unsupervised Artificial Neural Networks (ANNs). Furthermore, the methodology in its application to different basins with similar geological settings in the North African region.