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The Read Wavelet from file module loads a seismic wavelet from a plain text or DAT file, optionally truncates and tapers it, and makes it available as a wavelet item for use in subsequent processing steps such as matched filtering, deconvolution, or convolutional modelling. The module reads the amplitude samples as a single-column list of floating-point values and constructs an internal gather representation of the wavelet.
Use this module when you have an extracted or modelled wavelet stored as an ASCII file and need to supply it to a filter, convolution, or inversion module in the processing flow. The output provides both the raw (input) wavelet and the truncated and tapered (output) wavelet for comparison.
Path to the ASCII wavelet file (.dat or .txt). The file must contain a single column of floating-point amplitude values, one sample per line. The total number of lines determines the wavelet length together with the Sample rate parameter.
Sample interval (s) of the wavelet stored in the input file. Default: 0.001 s (1 ms). This must match the actual sample interval of the wavelet in the file; setting it incorrectly will stretch or compress the wavelet in time and produce incorrect results when it is applied in convolution or filtering modules.
Duration (s) from the start of the wavelet beyond which samples are zeroed out. Default: 15 s (equivalent to 15 / Sample rate samples). In practice, set this to the true length of the meaningful part of the wavelet to remove low-level noise or artefacts at the tail of the wavelet file. For example, for a 100 ms wavelet sampled at 1 ms, set Truncate to 0.1 s.
Length (s) of the Hamming taper applied at the end of the truncated wavelet to avoid sharp discontinuities. Default: 0.05 s (50 ms). The amplitude is smoothly ramped from its value to zero over this window. A shorter taper preserves more of the wavelet energy but leaves a harder edge; a longer taper reduces spectral leakage at the cost of wavelet duration.
Selects whether the module executes on the CPU or an available GPU.
Enables distributed processing across multiple compute nodes in a cluster.
Minimum number of traces dispatched to each compute node per batch during distributed execution.
When enabled, limits the number of threads used on each cluster node to the value set in Number of threads.
Optional text appended to the distributed job name to distinguish this run in the cluster queue.
When enabled, allows manual assignment of CPU core affinity for processing threads via the Affinity parameter.
CPU core affinity mask applied when Set custom affinity is enabled.
Number of CPU threads used for parallel execution. Set to the number of available physical cores for best performance.
When enabled, the module passes data through unchanged without reading the wavelet file. Use this to temporarily bypass wavelet loading in a workflow without disconnecting the module.
The raw wavelet as read directly from the ASCII file, without any truncation or tapering applied. Connect this output to a display module to verify the wavelet shape and amplitude before processing.
The processed wavelet after truncation and Hamming taper application. Connect this output to the wavelet input of a matched filter, convolution, or deconvolution module to apply the wavelet in the processing flow.