CSEM Data Interpretation Software for Hydrocarbon Detection

The patent segments the large CSEM dataset into multiple manageable components organized in a hierarchical file structure. Data is divided by survey line, receiver, frequency, and field component, with each segment stored in separate files within organized directories. This segmentation allows interpreters to work with specific subsets of data without being overwhelmed by the complete dataset, directly addressing the complexity issue while preserving measurement precision through systematic organization of all data elements.

The patent introduces a new organizational dimension by creating a multi-level hierarchical file structure that adds layers of abstraction between the raw data and the interpreter. This structure organizes data across multiple dimensions (survey line, receiver, frequency, component) and provides automated indexing and cross-referencing systems that navigate this multi-dimensional space, transforming the management of complex multi-dimensional CSEM data into a systematic process.

The patent implements automated feedback mechanisms that track and document each processing step applied to the CSEM data. The system maintains processing logs that record which synthetic datasets were generated, what processing methods were applied, and how they relate to the original measured data. This feedback system automatically updates metadata and cross-references, ensuring that interpreters can trace the complete processing history without manual bookkeeping, thus preventing information loss while enabling multiple processing iterations.

The patent introduces an intermediary processing management system that acts as a mediator between the multiple processing methods and the final interpretation. This intermediary layer automatically generates, organizes, and cross-references synthetic datasets, maintaining a systematic record of all processing operations. It serves as an intermediary database that links measured data, processing parameters, and resulting synthetic datasets, eliminating the need for manual tracking while preserving complete information about data transformations.

The patent applies preliminary action by automatically organizing and pre-processing CSEM data during the acquisition phase. The system performs initial data sorting, quality assessment, and metadata generation immediately upon data collection, preparing the data in an interpretation-ready format before the interpreter begins analysis. This preliminary organization of comprehensive datasets reduces the time required for subsequent interpretation while maintaining full detection accuracy by preserving all necessary data elements in an accessible structure.

The patent replaces manual data management mechanics with automated computational systems. The system automatically sorts, organizes, indexes, and cross-references comprehensive CSEM datasets without manual intervention, substituting mechanical bookkeeping processes with automated software operations. This substitution dramatically reduces interpretation time for large datasets while maintaining detection accuracy by ensuring systematic and error-free data organization and retrieval.