The primary objective of this symposium is to facilitate knowledge sharing and  collaboration among professionals who are engaged in implementing digitalization technologies and machine learning algorithms in geoscience applications. The joint effort of AAPG, EAGE and SEG societies aims to set up industry standards on reproducible AI and distribute key solutions on: data standardization and optimization, data quality, storage and model accuracy assessment, performance profiling, code optimizations, pervasive real-time and remote monitoring and more for advanced prototyping and delivery. We will explore diverse schools of thought, discuss advantages and limitations, compare results, and debate emerging approaches in the realm of artificial intelligence and digitalization as applied to geosciences. This symposium will focus on the utilization and evaluation of subsurface data not the implementation of digital infrastructure and strategies.

Digital transformation has emerged as a catalyst for progress and innovation within the geosciences, reshaping the energy sector by leveraging cutting-edge technologies and methodologies. By harnessing the power of machine learning/artificial intelligence (ML/AI), geoscientists are now able to acquire, analyze and integrate vast seismic, geological and well data, conduct field simulations, and perform other complex tasks with more efficiency and accuracy. This technological revolution has not only streamlined traditional operational approaches but has also unlocked new avenues for oil and gas exploration, development and sustainability. As the geoscience domain continues to embrace digital transformation, it is essential to assess its potential for driving further advancements, fostering collaboration, and expanding knowledge to address the challenges in the energy sector.