The Rock Physics license has received several great improvements in RokDoc 2024.4. With this software release, we've focused on making it easier to execute the most fundamental quantitative interpretation workflows that help the geoscientist deliver instant value to their teams. 

Overall, the time spent in the software is more effective and users can reach and incorporate deeper understanding of their data faster than ever.

Updated Rock Physics Model Workflows

There are three new interfaces for AVO modeling. The Blocky AVO Modelling function now includes a Wedge Modelling workflow for instant tuning and thickness accuracy analysis. This addition allows users to examine the uncertainties of the minimum resolvable seismic layer thickness, enhancing the precision and expectations of subsurface interpretations. This a quick but important workflow that QI teams can deliver to support seismic interpretation and preliminary amplitude analysis feasibility. The wedge is populated with the elastic properties from the AVO modeling session, and therefore can facilitate compaction investigations (i.e. how does tuning and layer thickness accuracy change with compacting rocks?) as well as uncertainty analysis. Along with a classic tuning curve, the user can set a threshold for absolute vs interpreted thickness error to answer the question: At what minimum thickness does my time thickness map become greater than 2 milliseconds inaccurate? Further investigation into uncertainties is then possible with a Monte Carlo  simulation of more wedge models using the per-rock data statistics.

The output plot is easily screen-grabbed or exported directly to an image file with the camera button.

A new AVO Scaling Tool has been introduced to assist with seismic and wavelet scaling, ensuring that synthetic and seismic data are compatible. This tool launches a scalar map function that further provides a comprehensive view of lateral variations in datasets. These workflows have been done by hand in the past, and represent significant time savings for the services team as well as clients with similar lateral scaling and illumination challenges.

Two critical AVO investigations can be performed. Find the scale factors that match the seismic data to the synthetic data or find the scaling for wavelets such that when the scaled wavelets are convolved with reflectivities, they match the seismic. Input data may come from half space modeling or well synthetics. New AVO Response Set handling also allows windowed attributes to be saved, so scaling over RMS windows can also be calculated

As per RokDoc design philosophy, resulting images are adjustable for documentation needs are easily captured to file.

These workflows may be used to demonstrate data issues with pre-stack seismic data, for example mapping scalers to highlight areas of poor illumination, or brought into characterization workflows. Maps may be loaded into the Reservoir Characterization, SDC Workflow function or scalers shared across the project-session levels using the new Scaler Management Dialog:

The new dialog additionally allows quick switching between Relative (bulk scaling on the nearest stack and offset scalers to highlight AVO effects) and Absolute (one scaler value for each stack).

These new options all support workflow efficiency in terms of quick delivery of basic analysis and easier data integration across more complex workflows.

Multi-Well Saturation Modeling workflow

The saturation modelling workflow now allows for the creation an arbitrary number of fluid cases. This means that across multiple wells, fine steps of fluid saturation scenarios can be made and QC'd more quickly than ever. This new functionality adds additional time saving benefits and opens up modeling workflows in a way never seen before - i.e. Imagine 10 wells with 10 fluid scenarios for each well - now the RokDoc user instantly validates with Dry Rock Gassmann, AVO half space plots, elastic crossplots and a well viewer that launches to display gather and log comparison plots. For users that want to regularly execute a few simple, direct tasks in RokDoc, these options greatly ease the learning curve and produce robust results quickly.

Color Management

Color is undeniably important for visualization of scientific data. From ensuring that plots convey the same information to the color-blind and trichromats, to preventing unintentional skew of data by visualization choices, we want to provide options for visualization in a simple, but effective manner. Have a look at this paper, Change the Default Colourmap for Optimum Data Visualization and More Effective Communication, if you have the time!

Over the past year, RokDoc has added a new colorbar management system that utilizes a super-set of colorbars, categorize by applicability and a subset for active project work. For more resources on the latest colors, have a read through the sources at the bottom of the page.

With the latest update, category defaults are now available. For integrated workflow plots like wavelet estimation, zero-centered plots like Delay are considered diverging and these new options allow the user to ensure that these types of QC maps are populated with the preferred color scale.

Deep QI

RPML (automated rock physics calibration, classification and prediction function) continues to grow in functionality and applicability. With this release, we've introduced a new custom cross-plot tab so the user can further investigate the petrophysical and elastic property results.

Leveraging the custom QC plot, the user can take advantage of the newly added Hashin-Strikman model. This relatively generic RPM accelerates progress in the early data investigation phase and allows users to represent exotic rock types. The parameterization is simple: RPML simultaneously optimizes an upper/lower bound stiffness mix (Bulk and Shear Modulus domain) between a mixed mineral and fluid filled pores. The engine can alternatively optimize the mineral mix itself. These results are motivated by optimizing fits with Gamma Ray, Resistivity, Velocity, Density, etc. Cross-plotting in fundamental parameter domains (K, Mu, PR) allows for quick validation and refinement of calibrations.

With this new model, users can experiment with different mineral combinations before committing to a type-specific model. For example, iterations of quartz, clays, carbonate mineral species may be tested by simply cloning the generic model and populating the mineral endmembers with varying minerals. Results may then support selection of more appropriate sand, shale, or carbonate models. Additionally, the generic model is useful for targeting anhydrite, halite, volcanics, or any other suspected rock type that could be characterized with petro-elastic measurements.

Color Resources:

• Colour scales 'Cube 1', 'Cube YF' and 'Linear L*' by Matteo Niccoli, mycarta.wordpress.com.
• ColorCET Perceptually Uniform Colour Maps. Peter Kovesi. Good Colour Maps: How to Design Them. arXiv:1509.03700 [cs.GR] 2015
• Scientific colour maps by Fabio Crameri. Copyright (c) 2023, Fabio Crameri
• Thyng, K.M., C.A. Greene, R.D. Hetland, H.M. Zimmerle, and S.F. DiMarco. 2016. "True colors of oceanography: Guidelines for effective and accurate colormap selection." Oceanography 29(3):9-13.
• Nunez, J. R., et al. (2018). "Optimizing colormaps with consideration for color vision deficiency to enable accurate interpretation of scientific data." Plos One 13(7): e0199239.
• Green, D. A. (2011). "A colour scheme for the display of astronomical intensity images." Bulletin of the Astronomical Society of India 39: 289-295.

By Alan Mur

Alan Mur has a PhD in Geology with specialization in Geophysics from the University of Pittsburgh and has over a decade of work experience in geology, rock physics, and geophysics. As Product Manager for Quantitative Interpretation (QI) Applications at Ikon Science, he manages all applications related to QI geophysics at Ikon and directs the software development team to evolve Ikon’s software offerings with consideration for the needs of the industry.

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