Advances in machine learning-driven pore pressure prediction in complex geological settings

Computer Science & IT Research Journal, Год журнала: 2024, Номер 5(7), С. 1648 - 1665

Опубликована: Июль 25, 2024

Advances in machine learning (ML) have revolutionized pore pressure prediction complex geological settings, addressing critical challenges oil and gas exploration production. Traditionally, predicting accurately heterogeneous anisotropic formations has been fraught with uncertainties due to the limitations of conventional geophysical petrophysical methods. Recent developments ML techniques offer enhanced precision reliability estimation, leveraging vast datasets sophisticated algorithms analyze interpret complexities. ML-driven approaches utilize a variety data sources, including well logs, seismic data, drilling parameters, train predictive models that can handle non-linear multi-dimensional nature subsurface conditions. Techniques such as neural networks, support vector machines, ensemble methods shown significant promise capturing intricate relationships between variables pressure. These adaptively learn from new improving their capabilities over time. A notable advantage is its ability integrate disparate types scales, providing holistic understanding regimes. This integration enhances accuracy forecasts, which crucial for wellbore stability, safety, hydrocarbon recovery. For instance, real-time operations be fed into dynamically update estimates, allowing immediate adjustments plans reducing risk blowouts or other hazards. Moreover, facilitate identification subtle patterns trends might overlooked by traditional capability particularly valuable deep-water environments, tectonically active regions, unconventional reservoirs, where often fall short. Despite promising advances, remain widespread adoption prediction. include need extensive training datasets, interpretability models, workflows existing geoscientific practices. Addressing these requires interdisciplinary collaboration geoscientists, scientists, engineers develop robust, user-friendly solutions. In summary, represents advancement managing complexities geology. By enhancing reliability, technologies are poised improve efficiency, productivity industry, challenging settings. Keywords: Advance, ML, Pore Pressure, Prediction, Geological Settings.

Язык: Английский

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

Engineering Science & Technology Journal, Год журнала: 2024, Номер 5(7), С. 2304 - 2322

Опубликована: Июль 24, 2024

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

Язык: Английский