We will have five oral talks at the 2019 SEG Annual meeting
Fun with research
My 4-years old daughter Grace was interested in this research. She said “I want to hunt these colorful eggs!”
These are not easter eggs. They are anisotropic fault ellipsoids that are colored by fault probabilities and oriented by strikes and dips. The fault probabilities, strikes and dips are predicted by using a trained CNN model.
Ancient sedimentary simulation
September 16, 2016
By properly assigning a geologic age to each seismic image sample, we are able to use a seismic volume to simulate the ancient sedimentary process. I made the above simulation using only the structure information of a seismic amplitude image. More information (such as well logs, cores, chemical and biological evolution of ancient sedimentary systems ) are required to obtain a more reasonable simulation of the ancient sedimentary process.
Reversal of geologic time?
September 16, 2016
The cartoon on the left shows a processing of gradually removing the faulting and then the folding in a 3D seismic image. With this processing, the seismic reflectors are more continuous across faults after the unfaulting, and are finally all flat after the followed flattening. This processing is helpful to identify all seismic horizons in this 3D seismic image, and actually generates a seismic Wheeler volume at the end.
With this processing, I do not truly reverse geologic time. However, there should be some possibility to achieve the goal of geologic time reversal by integrating analysis of chemical and biological evolution of ancient sedimentary systems.
Looking forward to any discussions and possible research collaboration for true geologic time reversal!
The original 3D seismic image of the onshore Schoonebeek oil field in the Netherlands was provided by Kees Rutten and Bob Howard, via TNO, a Dutch research organization. It’s a geologically beautiful high-resolution image, with numerous intersecting faults.
Efficient coding with Eclim=Eclipse+Vim
September 14, 2016
It often takes time to form a good habit, which, however, will save you a lot more.
Vim/gVim is the most popular lightweight editor to most programmers, especially those people who write codes for research at school. When the convenient hot keys of Vim have become a part of muscle memory of your fingers, you will enjoy coding efficiently and rhythmically. However, when you start to work on big projects, you will probably need to use a more advanced editor, like Eclipse, to deal with the projects and multiple packages. Now, you face the dilemma of abandoning your beautiful memory of Vim or suffering from handling the big projects.
“Eclim provides the ability to access Eclipse code editing features (code completion, searching, code validation, and many more) via the command line or a local network connection, allowing those features to be integrated with your favorite editor. Eclim provides an integration with Vim, but third party clients have been created to add eclim support to other editors as well (emacs, sublime text 2, textmate).”
Review of seismic flattening or domain transformation:
September 12, 2016
Numerous methods have been proposed for seismic flattening or transforming a seismic image from input time (depth) domain to Wheeler (flattened) domain. I spent almost a whole day attempting to write a complete review of popular methods for this topic. However, I believe a lot of good and related methods are still not included. The following paragraphs about the domain-transformation methods are included in my paper “Building 3D subsurface models conform to seismic horizons, faults, unconformities, and stratigraphic features”. I would like to thank Dr. Tracy Stark for providing me a detailed summary of the domain-transformation methods and related references in his 10-page comments for the above mentioned paper.
Numerous methods, such as stratal-slicing, uvt-transform, phase-unwrapping, slope-based flattening, have been proposed to transform seismic data from the original time (depth) domain to the Wheeler domain.
The stratal-slicing method, proposed by Zeng et al. (1998a,b), uses interpreted major horizons to interpolate a “stratal time volume” and then uses it to build a “stratal slice volume” in the Wheeler domain. Dorn (2011, 2013) and Dorn et al. (2011a,b) improve the method with discussions of using interpreted major unconformities and faulted horizons to generate vertical gaps and close up spatial fault gaps in the stratal slice volume. The resolution of these methods are limited because of using only a limited number of interpreted horizons for the domain transformation. To improve the resolution, de Groot et al. (2010) and Qayyum et al. (2012) perform the transformation using “horizon cubes”, which are high-density sets of interpreted horizons.
The uvt-transform method, proposed by Mallet (2004, 2008), is a general space-time mathematical framework for the domain transform. This method has been applied to remove folding and faulting (Labrunye et al., 2009; Mallet et al., 2010), but not to handle unconformities in a seismic image.
Stark (2004, 2005, 2006) propose to use the phase-unwrapping method (Shatilo, 1992; Spagnolini, 1993) to construct an RGT volume and convert 3D seismic data to the Wheeler domain using the RGT volume. These methods can properly handle both major and minor unconformities to generate vertical gaps in the Wheeler domain, but cannot close up the fault gaps. Wu and Zhong (2012) present a similar method to compute an RGT volume and seismic Wheeler volume with constraints from fault attributes and interpreted horizons and unconformities.
The slope-based flattening method (Lomask et al., 2006; Parks, 2010; Fomel, 2010) removes the folding in a seismic image with vertical shifts computed from seismic reflector slopes. All these flattening methods use only vertical shifts which may not correctly flatten nonvertical deformations (e.g., faulting) in the seismic image. Therefore, Luo and Hale (2013) propose to use vector shifts to remove the faulting and folding in a seismic image. This method, however, cannot correctly deal with unconformities to generate vertical gaps in the unfaulted and unfolded image. Wu and Hale (2015a,b) introduce constraints from unconformities and control points picked on horizons into Parks’s (2010) method to handle complicated structures such as unconformities and faults in seismic flattening. These methods, however, still use vertical shifts for flattening and therefore produce distortions near faults, especially those with small dips. Therefore, Wu and Hale (2016a) propose a unfaulting and flattening workflow to first remove the faulting (Wu and Hale, 2016b; Wu et al., 2016) in a 3D seismic image, then extract unconformities from the unfaulted image, and finally use the unconformities as constraints in estimating slopes and flattening the unfaulted image to generate vertical gaps corresponding unconformities in the unfaulted and flattened image.
de Groot, P., A. Huck, G. de Bruin, N. Hemstra, and J. Bedford, 2010, The horizon cube: A step change in seismic interpretation!: The Leading Edge, 29, 1048– 1055.
Dorn, G., 2011, Interpretation workflows enabled by a domain transform: First Break, 29, 99–108.
Dorn, G., W. Hammon, and J. Carlson, 2011a, Extraction of depositional systems. (US Patent 8,010,294).
——–, 2011b, Extraction of depositional systems. (US Patent 8,065,088).
Dorn, G. A., 2013, Domain transform: A tool for imaging and interpreting geomorphology and stratigraphy in seismic volumes: The Leading Edge, 32, 146–153.
Fomel S., 2010, Predictive painting of 3D seismic volumes: Geophysics, 75, A25–A30.
Labrunye, E., C. Winkler, C. Borgese, J.-L. Mallet, S. Jayr, et al., 2009, New 3D flattened space for seismic interpretation: Presented at the 2009 SEG Annual Meeting, Society of Exploration Geophysicists.
Lomask, J., A. Guitton, S. Fomel, J. Claerbout, and A. A. Valenciano, 2006, Flattening without picking: Geophysics, 71, 13–20.
Luo, S., and D. Hale, 2013, Unfaulting and unfolding 3D seismic images: Geophysics, 78,O45–O56.
Mallet, J., 2008, Numerical earth models: European Association of Geoscientists and Engineers. Education tour series.
Mallet, J.-L., 2004, Space-time mathematical framework for sedimentary geology: Mathematical Geology, 36, 1–32.
Mallet, J.-R., S. Jayr, and P. Neri, 2010, New modelling technology delivers consistency: First Break, 28.
Parks, D., 2010, Seismic image flattening as a linear inverse problem: Master’s thesis, Colorado School of Mines.
Qayyum, F., P. de Groot, and N. Hemstra, 2012, Using 3D wheeler diagrams in seismic interpretation–the horizoncube method: first break, 30, 103–109.
Shatilo, A., 1992, Seismic phase unwrapping: methods, results, problems: Geophysical prospecting, 40, 211–225.
Spagnolini, U., 1993, 2-d phase unwrapping and phase aliasing: Geophysics, 58, 1324–1334.
Stark, T. J., 2004, Relative geologic time (age) volumes—relating every seismic sample to a geologically reasonable horizon: The Leading Edge, 23, 928–932.
——–, 2005, Generating a seismic Wheeler volume: 75th Annual International Meeting, SEG, Expanded Abstracts, Soc. of Expl. Geophys., 782–785.
——–, 2006, Visualization techniques for enhancing stratigraphic inferences from 3D seismic data volumes: First Break, 24.
Wu, X., and D. Hale, 2015a, 3D seismic image processing for unconformities: Geophysics, 80, IM35–IM44.
——–, 2015b, Horizon volumes with interpreted constraints: Geophysics, 80, IM21–IM33.
——–, 2016a, Automatically interpreting all faults, unconformities, and horizons from 3D seismic images, 4, T227–T237.
——–, 2016b, 3D seismic image processing for faults: Geophysics, 81, IM1–IM11.
Wu, X., S. Luo, and D. Hale, 2016, Moving faults while unfaulting 3D seismic images: Geophysics, 81, IM25–IM33.
Wu, X., and G. Zhong, 2012, Generating a relative geologic time volume by 3D graph-cut phase unwrapping method with horizon and unconformity constraints: Geophysics, 77, 21–34.
Zeng, H., M. M. Backus, K. T. Barrow, and N. Tyler, 1998a, Stratal slicing; Part 1, Realistic 3-D seismic model: Geophysics, 63, 502–513.
Zeng, H., S. C. Henry, and J. P. Riola, 1998b, Strata slicing; Part ii, Real 3-D seismic data: Geophysics, 63, 514–522.