0900 Lowell Geoteric Combining Artificial Intelligence with Human Reasoning for Seismic Interpretati
Channel: Force Seminars
Date: 2019-10-04

2019 Force Symposium machine learning and subsurface data
Presentations https://www.npd.no/en/force/archive/hackathon-2019/

Combining Artificial Intelligence with Human Reasoning for Seismic Interpretation
By James Lowell Geoteric
we present a new Al workflow that utilizes deep learning techniques to work alongside
interpreters to improve efficacy as well as understanding. A bespoke deep learning
architecture has been developed and trained using real data including many fault signatures
from different geological environments across varying data quality. This foundation network
can be applied directly onto unseen data cubes, or can be appended with interpretations
from new data sets; capturing additional knowledge from an E&P company's own
interpretations. It is expected that calibration will be carried out to understand the nuances
of the new environment as shown in figure 1. The proposed interpreter centric Al workflow,
captures and integrates both the deep learning, as well as more established workflows for
interpretation. Centered around the interpreter, improvements to either the foundation
network model, or previously evolved (fined tuned) network model can be applied to
different data sets, transferring the learning between different geological units and regions.
This opens up the ability, if desired, to have workflows designed to avoid anchoring and
single views of complex system. Processing the foundation deep learning fault network on a
3D cube shows promising results, as can be seen in figure 2. The Al fault cube can be used
directly in other parts of the workflow or to extract individual faults sticks/ surfaces.
Without interpreter confidence in the results, deep learning will struggle to get out of the
starting blocks. Putting the interpreter at the heart of the process, as this workflow does,
presents an opportunity for a deep learning environment to be adopted in the subsurface
arena where its benefits can be leveraged to aid effective, accurate and appropriate
understanding