Digital Seismic File Ingestion and Normalization
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Solution Overview
Problem
The oil and gas industry faces challenges in ingesting large volumes of digital seismic files due to their heterogeneous formats and structures, which vary across different acquisition tools and software packages, making it difficult to load and interpret seismic data efficiently.
Innovation Solution
A computer system is developed to perform autodetection of parameters in digital seismic files, normalize the seismic data, extract metadata, identify parent virtual surveys, and store the normalized data in a common data platform, ensuring compatibility and preventing duplicate data storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If individual parameters of different digital seismic files are determined manually, then parameter accuracy is improved, but processing time and labor requirements increase significantly
Solution Approach 1:
The system performs autodetection of parameters by automatically analyzing the digital seismic file structure, header information, and data patterns to extract parameters such as sampling rate, bit depth, channel configuration, and geographic coordinates without manual intervention. This self-service approach eliminates manual parameter extraction while maintaining high accuracy through algorithmic analysis of the file contents.
Solution Approach 2:
The patent replaces manual parameter extraction processes with automated computational algorithms that scan file headers, detect data formats, and infer parameters from the seismic data structure. This substitution of mechanical manual analysis with automated digital processing significantly reduces processing time while maintaining measurement precision.
2Quantity of substance
If seismic data from multiple acquisition tools and software packages is loaded, then data volume and analysis capability are improved, but system complexity and compatibility issues increase
Solution Approach 1:
The system creates a universal parameter detection framework that can handle multiple seismic file formats from different acquisition tools and software packages. By implementing a standardized autodetection algorithm that analyzes various file structures and generates unified parameter sets, the system achieves multi-format compatibility without requiring separate processing pipelines for each data source.
Solution Approach 2:
The patent standardizes parameters across different seismic file formats by detecting the original format-specific parameters and transforming them into a unified set of standardized parameters. This parameter normalization process allows data from diverse sources to be consistently represented and processed, reducing system complexity while increasing data volume handling capability.
3Reliability
If digital seismic files are stored in their original formats, then data integrity is preserved, but interoperability and data processing efficiency deteriorate
Solution Approach 1:
The system segments the data processing into distinct stages: (1) autodetection of original file parameters to preserve integrity, (2) extraction of seismic data while recording metadata about the original format, and (3) creation of normalized representations. This segmentation allows the system to maintain original data integrity through metadata preservation while generating processed normalized data for efficient interoperability.
Solution Approach 2:
The patent introduces normalized seismic data as an intermediary layer between original format-specific files and processing applications. The normalization process creates a universal intermediate representation that preserves the essential characteristics of original data while enabling efficient processing and interoperability, effectively mediating between data integrity requirements and processing efficiency needs.
Data Source
AI summary
A method includes obtaining a digital seismic file, obtaining a digital seismic file, and performing autodetection of parameters of the digital seismic file. The method further includes extracting seismic data from the digital seismic file according to the parameters to generate normalized seismic data. The method further includes scanning the normalized seismic data to obtain metadata that includes geographic file boundaries and mapping the normalized seismic data to a parent virtual survey based at least in part on the geographic file boundaries being in a geographic region of a parent virtual survey. The method additionally includes storing, in a target store, the normalized seismic data and metadata, the normalized seismic data in a stored relationship with the parent virtual survey in the target store.