Model-Driven Processing of Passive Seismic While Drilling Data Acquired Using Distributed Acoustic Sensing Without...

Area of Science:

• Geophysics
• Seismology
• Petroleum Geoscience

Background:

• Conventional Seismic While Drilling (SWD) relies on measured drill bit signatures for processing passive seismic data.
• Acquiring pilot signals is crucial for correlating passive seismic recordings and determining source trigger times in traditional SWD.
• Challenges arise in SWD processing when pilot signals are unavailable, necessitating inference of source timing and signature from recorded wavefields.

Purpose of the Study:

• To present an advanced processing workflow for Distributed Acoustic Sensing (DAS) based SWD data acquired without pilot signals.
• To transform passive SWD data into active seismic equivalents for simplified subsurface characterization.
• To demonstrate the recovery of reliable velocity and structural information from DAS-based SWD data in a cross-well setting.

Main Methods:

• Developed a processing workflow guided by travel time and seismic modeling.
• Transformed passive SWD data into active seismic data equivalents.
• Applied travel time tomography and cross-well imaging to the transformed data.

Main Results:

• Successfully processed a SWD dataset acquired with DAS in a cross-well setting without pilot signals.
• Demonstrated the ability to infer source timing and signature from the recorded wavefield.
• Recovered reliable velocity and structural information from the DAS-based SWD data.

Conclusions:

• The presented workflow enables simplified and scalable deployment of passive seismic while-drilling workflows.
• Reliable subsurface velocity and structural information can be obtained from DAS-based SWD data even without pilot measurements.
• The method facilitates advanced subsurface characterization using passive seismic data acquired during drilling operations.