Advancing Hydraulic Fracture Monitoring: Elastic Full Waveform Inversion With Moment Tensor Implementation Using Das And/or Geophones

Hydraulic fracture monitoring (HFM) is critical to optimizing reservoir stimulation and maximizing hydrocarbon recovery. Traditional microseismic methods rely primarily on kinematic data, involving manual time-picking and waveform editing, which limits robustness under low-to-moderate signal-to-noise ratios (SNR). This paper presents a novel methodology integrating elastic full waveform inversion (eFWI) with moment tensor inversion (MTI), leveraging fused Distributed Acoustic Sensing (DAS) and geophone data. The hybrid approach harnesses the full seismic wavefield, eliminating the need for manual picking and enabling high-resolution source mechanism characterization. We develop a 3D elastic wave propagation solver incorporating moment tensor sources and apply an adjoint-based inversion framework for simultaneous velocity, anisotropy, event location, and moment tensor estimation. Sensitivity and resolution matrix analyses guide sensor deployment and assess parameter recoverability. Validation with synthetic and field data demonstrates strong waveform reconstruction and accurate moment tensor recovery. The method differentiates tensile, shear, and hybrid fracture mechanisms, providing critical insights for optimizing hydraulic fracturing design and reducing seismic risk. Our results highlight the transformative potential of eFWI-MTI fusion in advancing HFM capabilities and reservoir management.