Resolve GeoSciences, Inc.

This one is for all you seismic data loading professionals. Tell us what can be done to make your life easier when it comes to loading seismic and segy data. Are your biggest gripes with incomplete ebcdic headers? What about bizarre trace headers? Maybe the filenames don’t describe what’s actually in the file? Are there common problems with the actual data? Are the amplitudes out-of-whack? Do you have large spikes? Missing data? Maybe the navigation information is incorrect? Common ftp delivery problems? Whatever makes your life difficult as a data loader (or makes it better!), feel free to comment below. Maybe this will help future deliverables. I was having a casual conversation with Don Robinson at Resolve GeoSciences, Inc. and it got me to thinking about this topic. https://lnkd.in/gAPAUyUc Interested in a seismic training class? https://lnkd.in/gN3-RZa5 * I have almost 2 hours of online presentations introducing various aspects of seismic velocities and processing. There’s a modest cost – https://lnkd.in/gw3eQcCB #houstonseismic

Processing/Reprocessing Challenges and Insights: When loading 3D poststack datasets into workstations or repositories, key processing details often get lost—especially if communication between the interpreter and processor is no longer active. This is a common issue with dual-processed surveys or reprocessing efforts, where critical insights shared with the initial processor may not carry over to subsequent teams. Case Study: USA Land Survey A recent USA land survey east of the Rockies was processed and reprocessed using identical acquisition and field data. With surface elevations and geology unchanged, the key differences lay in workflows, software, and expertise. Both processing runs applied refraction statics with a floating datum finalized to a fixed datum. While amplitudes and original frequencies were nearly identical, challenges arose due to varying time shifts, requiring horizons to be repicked for each version. Key Observations: Multiple prestack static corrections (up to five) were applied, including refraction statics, residual statics (twice), surface-consistent automatic statics, trim statics, and final datum statics. Can we pinpoint which adjustments are driving the largest time shifts? Surface elevations appeared smeared, likely from widely spaced source and receiver points, and differed significantly from DEMs (digital elevation models). Could this smoothing affect surface-consistent statics? When spacing is sparse, do processing companies use DEMs for better elevation control? Synthetic Seismogram Correlation: Wells were available for geologic and synthetic seismogram correlation, but minor time shifts gave the misleading impression of a good tie with slight stretching and squeezing. This issue could potentially stem from refraction statics. Reprocessing Best Practices When reprocessing to improve signal-to-noise, frequency, and imaging, it is critical to share previous processing versions. Side-by-side comparisons help identify time shifts and character changes, allowing processors to address differences and align results with interpretation goals. It’s also important to distinguish between reprocessing, which builds on prior work, and dual processing, which starts fresh from the same field data. The Role of Expertise With staff reductions affecting experienced professionals, the risk to data quality increases while confidence in acquisition and processing decreases. Hiring acquisition and processing specialists with expertise in both legacy and modern equipment/software is critical to mitigating risks and maintaining high data quality. If you’re one of these specialists, share your name, areas of expertise, and the countries or basins you’re most familiar with. For example, Ron Kerr will definitely have insights worth exploring. #SeismicDataProcessing #Geophysics #SeismicReprocessing #ExplorationData #GeoscienceExperts

???????????????? ??????????: ????????-???????????????? ???????????? Originally developed in the mid-1990s, SeisShow was designed to simplify viewing 2D and 3D poststack seismic data—without requiring a full 3D interpretation system. It became a go-to for data loaders to preview datasets before workstation imports and for seismic data brokers showcasing library data. Additional features enabled 2D/3D cuts for licensed area delivery. Back then, SEG-Y implementations were even more inconsistent than today. To tackle this, we built wizards to auto-detect byte locations for lines, traces, and coordinates—even in datasets lacking clear EBCDIC headers or loadsheets. With each dataset, we uncovered new irregularities and evolved the tool to handle them seamlessly. We've enhanced SeisShow with seismic attribute calculation services, enabling interpreters to efficiently visualize attribute volumes, time slices, and extracted horizons. New features were specifically designed to support this workflow. Today's highlight: Automatic identification of loading parameters, indexing, and display of SEG-Y files using SeisShow. These algorithms now scale to analyze hundreds or thousands of SEG-Y datasets, with metadata stored in JSON files and data models. Stay tuned for updates on our batch application, AnalyzeSE. ???????????????? ???????????????? ??????????: ? PostStack & Gather volume cutting ? Pane sections & timeslice displays ? 360° rotation analysis ? Frequency band exploration ? Interactive filtering, mutes, and spectral decomposition ? Dynamic section and timeslice visualizations ? Rapid multi-section, horizon extractions, and timeslice displays ? Blending, masking, and joint section/gather displays ? JSON file creation, reports, and stats Check out our website to watch the full video and explore other shorter clips: https://lnkd.in/g8QA5-TN #SeismicData #Geophysics #SEGYFormat #SeismicVisualization #DataManagement

IBM Float vs IEEE Float In the late '70s and early '80s, seismic interpretation workstations used IBM Floating-Point format. With the rise of personal computers in the mid-'80s, the IEEE format became standard—even adopted by IBM for mainframes by the late '90s. SEG-Y Rev 1 (2002) officially supported IEEE format, yet IBM Floating-Point persists. Are there still technical benefits to using it today? The answer seems to be NO. Here’s why across key areas: 1. Transmission IBM float offers no advantage for data transmission. Both formats use the same storage space (32 bits), but IEEE 754 is the modern standard universally supported by software and hardware. 2. Calculation IBM float is inefficient for modern computations. Processors are optimized for IEEE 754, meaning IBM float must be converted to IEEE for calculations. This adds unnecessary computational overhead, slowing down workflows. 3. Storage While IBM float uses the same 32-bit size, its base-16 exponent sacrifices precision compared to IEEE 754. IEEE provides better accuracy and consistency, especially for scientific and engineering data. Converting back to IBM float for storage to comply with SEG-Y Rev 0 or other legacy standards. This double conversion (IBM-to-IEEE and IEEE-to-IBM) introduces computational redundancy and potential for rounding errors. Why IBM Float Persists The only reason IBM float survives is legacy compatibility with older standards like SEG-Y Rev-0 in geophysics. SEG-Y Rev-1 and Rev-2 both support IEEE. It’s not a matter of technical superiority but historical inertia. Conclusion By storing data in IEEE 32-bit floating-point format and removing the need for IBM-to-IEEE and IEEE-to-IBM conversions: Computational overhead for each dataset processing cycle can be halved (no double conversion). The processing pipeline becomes simpler and more robust. Resources are saved, particularly for large datasets common in geophysics. The industry's reliance on legacy formats poses challenges, but phased transitions or dual-format support can help. SEG-Y Rev 1 and Rev 2 already address this by supporting both formats during migration. There's no shortage of opinions on this topic—otherwise, we wouldn’t still be using IBM Float. Share your thoughts, experiences, or suggestions in the comments! #SeismicData #Geophysics #SEGY #DataProcessing #ExplorationInnovation

Bin Grid Definitions - Loading to Workstations Precise location data is crucial for accurate seismic interpretation. While the "4 corners" method can introduce risks, extracting coordinates directly from trace headers improves spatial accuracy, minimizing misalignment from cumulative azimuth and spacing errors. Loading corner coordinates from load sheets and EBCDIC headers is efficient, but manual data entry raises error risks. Studies indicate that 20-30% of these errors are transpositions (e.g., "43" entered as "34"), with the rest being random digit additions or omissions. Analyzing XY values from hundreds of thousands of 3D poststack volumes confirms that trace headers—populated directly by processing software—provide more reliable spacing and azimuth data than load sheets and EBCDIC headers, with far fewer manual-entry errors. However, trace headers can still have issues, which can often be identified and corrected automatically. The images from the Waihapa 3D dataset included here are ?Crown Copyright, reproduced with permission from New Zealand Petroleum and Minerals (www.nzp&m.govt.nz), and are used to showcase the Bin Grid Calculator. We're launching a new Grid Definition Calculator, available soon for Beta testing. This tool allows users to enter or paste line, trace, and XY corner values to calculate spacings, azimuths, area, and create a grid polygon using either three corners or a Point + Spacing method. Currently, Projection (CRS) is for display only, but an upcoming feature will check corner orthogonality (90-degree angles). Interested in Beta testing? Reach out! We welcome feedback on the interface and are especially keen on your input for handling 4-corner data from load sheets/EBCDIC headers versus XYs from trace headers. #SeismicDataIntegrity #GeophysicalAnalysis #SEG_YFormat #SeismicGridCalculation

??We’re here at IMAGE Booth #1553! Stop by to learn how AnalyzeSE and SeisShow can prepare your seismic data for modern AI and ingestion workflows.