Full-waveform inversion using deviated well distributed acoustic sensing vertical seismic profiling data: A case study

ABSTRACT With the development of fiber-optic seismology, distributed acoustic sensing (DAS) has made significant progress in vertical seismic profiling (VSP). The integration of full-waveform inversion (FWI) with DAS data acquired through well-bore optical fibers presents a promising frontier for subsurface characterization. Although the successful implementation of FWI can yield precise velocity models essential for reservoir monitoring and imaging, its application to DAS data has been limited predominantly to vertical wells. In such conventional approaches, the strain rate measurements from DAS are typically converted to vertical particle velocities at corresponding channel locations before applying standard FWI algorithms. However, this methodology faces significant limitations when extended to deviated wells, wherein the conversion to vertical particle velocity becomes inapplicable. Addressing this challenge, our study introduces a novel FWI strategy that enables the processing of DAS VSP data across various well configurations. The core innovation lies in the conversion of DAS measurements into scalar particle displacement, an approach that maintains the essential phase information while accommodating amplitude and frequency variations. Through the rigorous derivation of the relationship between DAS data and particle displacement in wavefields, we establish that the fundamental distinction between these measurements resides solely in their frequency components and relative amplitudes, with phase characteristics remaining intact. This displacement-based conversion method offers unprecedented flexibility, allowing for the application of conventional FWI to DAS data from deviated wells through appropriate amplitude adjustments based on wave velocity and incident angles at channel positions. We demonstrate this approach with a comprehensive set of DAS VSP data collected from an offshore inclined well, where the DAS data are directly fed into the FWI algorithm after amplitude scaling and simple preprocessing. FWI reduces data misfit and enhances velocity updates, and the inverted model provides an improved prestack depth migration image along with angle-domain common-image gathers.