Extracting horizons and detecting faults in a seismic image are basic steps for structural
interpretation and important for many seismic processing schemes. A common ground of the …

Implicit neural representation (INR) networks are emerging as a powerful framework for
learning three-dimensional shape representations of complex objects. These networks can …

In this contribution we introduce LoopStructural, a new open-source 3D geological
modelling Python package (http://www. github. com/Loop3d/LoopStructural, last access: 15 …

Leveraging a high resolution geological and structural dataset acquired over decades of
fieldwork, we build the 3D structural model of a portion of the highly deformed core of the …

Implicit structural modeling using sparse and unevenly distributed data is essential for
various scientific and societal purposes ranging from natural source exploration to …

It is well known that seismic data (or seismic volumes/images) are one of the primary work
materials of the oil and gas industry. Nevertheless, the manual interpretation of such data …

Three-dimensional unfavourable geology models with complex structures and various
attributes have become crucial for optimal design and risk control during tunnel construction …

Abstract Three-dimensional (3D) stratigraphic modeling is capable of modeling the shape,
topology, and other properties of strata in a digitalized manner. The implicit modeling …

We introduce a new method for implicit structural modeling. The main developments in this
paper are the new regularization operators we propose by extending inherent properties of …

Geologists' interpretations about the earth typically involve distinct rock units with contacts
between them. Three-dimensional geologic models typically comprise surfaces of …