Description of The ProblemReflection seismology allows us to image the inner structure of Earth’s surface layer by sending down test seismic waves, and recording their “echo”, i.e. their reflection from heterogeneities inside the ground. One important type of heterogeneity is called a fault, which is defined as a planar fracture or discontinuity in a volume of rock across which there has been significant displacement as a result of rock-mass movement. The location of planar faults is an important topic in geophysics and geology because faults with high stress within them are the cause of most earthquakes. The successful interpretation (extraction) of these faults is a critical step in subsurface exploration. Typically the faults planes are extracted via a manual process where a human interpreter “draws” fault sticks on a series of slices visualized in the volume. These sticks are then images together as a triangulated plane (see later images). This is an extremely time-consuming & manually intensive process.
Today there are various methods to process the input seismic volume & generate an output that highlights the faults making them easier to visualize. One such process generates a 3D Fault Likelihood volume. In a nutshell it is a 3D grid, with two coordinates corresponding to the geographical coordinates on the Earth surface, and the third coordinate corresponding to the depth inside the ground. The value associated with each grid node specifies the estimated likelihood (probability) that the node lies on a geological fault, or it is located close to it. The problem our client looks to solve is to develop an algorithm able to, given a 3D Fault Likelihood volume, automatically extract fault planes contained within that volume. See the following images to better understand the problem.
Figure 1. The raw 3D seismic amplitude volume displays how well seismic waves are reflected inside different points of an Earth’s surface and images its structure.
Figure 2. A 3D Fault Likelihood volume calculated from the raw 3D seismic data displays at each point the likelihood that the point lies at a fault. Bright colors (most of the volume) represent low probability, and the dark colors represent high probability of a fault. Seen together these points image fault planes found in the original data. Fault likelihood volumes are the input to the problem we want solved.
As you see from the illustration, most of the dark points are arranged into planes cutting through the surface slab, and possibly intersecting each other. The goal of this project is to come up with an algorithm that automatically recognizes fault planes.
Figure 3. Manual extraction of fault planes. An expert examines visually cross-sections of 3D Seismic (at this illustration) or Fault Likelihood volume, and marks by “fault sticks” the lines where a fault crosses the cross-section. The fault plane is then triangulated based on the positions of corresponding sticks in a series of cross sections.
In the challenge forum you will find an example 3D Fault Likelihood volume in SEG-Y format. The original seismic volume is also provided in the forum. We believe that the generation of 3D Fault Likelihood volume is accurate, and the fault locations can be reliably extracted out of it, thus the goal of this project is to use 3D Fault Likelihood volume as the only input and extract fault locations from it. However, in case you believe additional data contained in the original seismic volume may be helpful for understanding the problem, or may be used to improve the fault extraction, we provide it for your reference, and we are open for approaches that use it as an additional or alternative input, if it is demonstrated to be beneficial.
You should be able to find a bunch of existing libraries and tools for manipulation and visualisation of SEG-Y data, including but not limited to:
- https://github.com/equinor/segyio - C library for SEG-Y manipulation, with language bindings for Python and Matlab.
- https://cultpenguin.gitbooks.io/segymat/content/ - Matlab and Octave library for SEG-Y manipulation.
- https://www.dgbes.com/index.php/download - Free software for interpretation of seismic data.
- https://github.com/dhale/ipf contains sample programs for manipulation and processing of seismic data
- Also two articles covering existing approaches to the problem are shared in the challenge forum.
- A separate output file for each detected fault plane
- Payload in the file should be in text format, and describe the fault plane as a mesh. We are likely to specify the preferred data format during the challenge.