Daniel Austin Earth Science Analytics
Paul Wilson SLB (Petroleum Geoscience Editorial Board)
Runhai Feng University of Copenhagen (Geoenergy Editorial Board)
Petroleum Geoscience and Geoenergy are calling for papers to be submitted to a joint collection on “Digitally enabled geoscience workflows: unlocking the power of our data”.
Data science – including automation, data analytics, machine learning and processing of extremely large datasets – is now an important part of everyday life and is transforming the way scientists conduct research and develop new technologies, enabling specific tasks to be implemented with minimal human supervision.
These techniques are providing game-changing advances in subsurface workflows in terms of time saving on complex tasks, improved consistency and repeatability of interpretation, and utilization of scarce experienced geoscientists.
This special collection of papers will present the state of the art in data science applications for geoscience, and particularly intends to highlight the recent advances of these technologies to solve subsurface problems across various disciplines including:
- Data science and statistics with geological applications.
- AI and automation on downhole production data.
- Integrated studies in subsurface analytics production and operations optimization.
- Exploration/production challenges.
- Seismic and well log interpretation.
- The interface between engineering and geoscience.
- Transfer of learning to solve geoscientific problems.
- Data science applications to the energy transition.
Submissions should be made via the Petroleum Geoscience Editorial Manager website or Geoenergy Editorial Manager website. It is up to the author to choose which journal is more suitable for their paper.
When submitting manuscripts make sure to identify the submission as being for the ‘Digitally enabled geoscience workflows: unlocking the power of our data’ collection by selecting it from the ‘Section/Category’ drop-down list.
For queries please contact the Editorial Office.
Submission deadline: 31 December 2023
Image: 3D geological model with data flowing out into an artificial intelligence, produced via DALL·E 2. Courtesy of Earth Science Analytics.