LF field data transmitted to the processing center are quality controlled using predefined data quality displays to ensure a rapid and standard evaluation. The data is then imported with interactive, proprietary software that performs a broad set of automatic and detailed checks to further ensure data quality.

Once the data is imported into the database, a rich suite of analytical and graphical tools are used to evaluate the data with regards to noise, spectral content, and time variability. These analyses include not only the primary low frequency time series, but also include reference measurements and meta-data such as weather information and photographs of the installation and local environment.

Data conditioning and processing

The output of this phase is a clean, comparable data set. Any low frequency anomaly deemed to be associated with a hydrocarbon reservoir is identified and the frequency range which best captures it is defined. Low frequency background noise is also identified at this stage in order to best exclude or at least minimize its effect on the anomaly band. Then, the optimal time window within the full recorded signal is chosen to minimize noise and enhance the low frequency anomaly.

Spectraseis developed RIO, our own software suite designed specifically for efficient LF data management and processing

Spectraseis proprietary methods and methods covered by patent filings include attribute analysis, extraction and inversion methods for low-frequency seismic data.

These include polarization analysis, spectral ratios, normalization and parameterized frequency band integration methods, as well as techniques for directly locating hydrocarbon reservoirs within the subsurface.