Advances in rock physics for pore pressure prediction: A comprehensive review and future directions

Abstract

Advances in rock physics have significantly enhanced pore pressure prediction, a critical aspect of subsurface exploration and drilling operations. This comprehensive review delves into the latest developments in rock physics methodologies, integrating empirical, theoretical, and computational approaches to predict pore pressure more accurately. Traditional pore pressure prediction methods often rely on well log data and seismic attributes, but recent advancements have introduced innovative techniques that leverage the physical properties of rocks to provide more reliable predictions. Key advances include the development of improved rock physics models that better account for the complexities of subsurface environments, such as heterogeneity and anisotropy. These models integrate data from various sources, including well logs, core samples, and seismic surveys, to create a more comprehensive understanding of the subsurface. Additionally, the application of machine learning and artificial intelligence to rock physics has opened new avenues for analyzing large datasets, identifying patterns, and refining predictive models. This review also examines the role of laboratory experiments and field studies in validating and calibrating rock physics models. High-pressure and high-temperature experiments have provided valuable insights into the behavior of rocks under different conditions, which are essential for accurate pore pressure prediction. Field studies, on the other hand, offer real-world data that help in fine-tuning models and methodologies. Future directions in rock physics for pore pressure prediction include the integration of advanced geophysical techniques, such as full-waveform inversion and distributed acoustic sensing, which offer higher resolution data and more detailed subsurface imaging. The use of cloud computing and high-performance computing platforms is also expected to enhance the processing and analysis of large datasets, making predictive models more efficient and scalable. The comprehensive review concludes by highlighting the importance of interdisciplinary collaboration in advancing rock physics methodologies. By combining expertise from geophysics, petrophysics, geomechanics, and data science, the field can continue to innovate and improve the accuracy and reliability of pore pressure predictions, ultimately enhancing exploration and production efficiency in the oil and gas industry. Keywords: Advances, Rock Physics, Pore Pressure, Prediction, Future Directions.