The precise characterization of subsurface fracture systems, especially sub-seismic fractures below seismic resolution, is critical for developing complex hydrocarbon reservoirs. While ant colony optimization (ACO) introduced “ant tracking” for seismic fracture detection, traditional methods rely on isotropic post-stack attributes, ignoring azimuthal anisotropy—a key indicator of fracture orientation and density. The azimuth-aware anisotropic bayes ACO (Ani-Bayes ACO) integrated pre-stack anisotropy via Bayesian priors but suffered from deterministic constraints and static heuristics, limiting its ability to model conjugate fracture systems or parameter uncertainty. To resolve these limitations, we propose the anisotropy-dynamic ACO (ADACO) algorithm. ADACO replaces deterministic constraints with probabilistic, dynamically evolving fracture parameter distributions: von Mises for orientation and log-normal for density, both parameterized by elliptical fitting credibility. During optimization, a Hidden Markov Model (HMM) globally evaluates path consistency, while elite-path feedback iteratively focuses the distributions. This enables uncertainty-quantified fracture prediction, multi-set tracking, and autonomous adaptation to fracture clustering. Validation in a complex shale gas reservoir showed 85% consistency with drilling data—a significant improvement over Ani-Bayes ACO (46%). ADACO thus provides a robust tool for sub-seismic fracture characterization.

Determining the orientation of in-situ stresses is crucial for various geoscience and engineering applications. Conventional methods for estimating these stress orientations often depend on focal mechanism solutions (FMSs) derived from earthquake data and formation micro-imager (FMI) data from well logs. However, these techniques can be costly, depth-inaccurate, and may lack spatial coverage. To address this issue, we introduce the use of three-dimensional (3D) seismic data (active sources) as a lateral constraint to approximate the 3D stress orientation field. Recognizing that both stress and fracture patterns are closely related to seismic velocity anisotropy, we derive the orientation of azimuthal anisotropy from multi-azimuth 3D seismic data to compensate for the lack of spatial stress orientation information. We apply our proposed workflow to a case study in the Weiyuan area of the Sichuan Basin, China, a region targeted for shale gas production. By integrating diverse datasets, including 3D seismic, earthquakes, and well logs, we develop a comprehensive 3D model of in-situ stress (orientations and magnitudes). Our results demonstrate that the estimated anisotropy orientations from 3D seismic data are consistent with the direction of maximum horizontal principal stress (SHmax) obtained from FMIs. We analyzed 12 earthquakes (magnitude > 3) recorded between 2016 and 2020 for their FMSs and compressional axis (P-axis) orientations. The derived SHmax direction from our 3D stress model is 110° ES (East-South), which shows excellent agreement with the FMSs (within 3.96°). This close alignment validates the reliability and precision of our integrated method for predicting 3D SHmax orientations.

Seismic migration and inversion are closely related techniques to portray subsurface images and identify hydrocarbon reservoirs. Seismic migration aims at obtaining structural images of subsurface geologic discontinuities. More specifically, seismic migration estimates the reflectivity function (stacked average reflectivity or pre-stack angle-dependent reflectivity) from seismic reflection data. On the other hand, seismic inversion quantitatively estimates the intrinsic rock properties of subsurface formulations. Such seismic inversion methods are applicable to detect hydrocarbon reservoirs that may exhibit lateral variations in the inverted parameters. Although there exist many differences, pre-stack seismic migration is similar with the first iteration of the general linearized seismic inversion.

Usually, seismic migration and inversion techniques assume an acoustic or isotropic elastic medium. Unconventional reservoirs such as shale and tight sand formation have notable anisotropic property. We present a linearized waveform inversion (LWI) scheme for weakly anisotropic elastic media with vertical transversely isotropic (VTI) symmetry. It is based on two-way anisotropic elastic wave equation and simultaneously inverts for the localized perturbations (△V_p0/V_p0, △V_s0/V_s0, △ϵ, △δ) from the long-wavelength reference model. Our proposed VTI-elastic LWI is an iterative method that requires a forward and an adjoint operator acting on vectors in each iteration. We derive the forward Born approximation operator by perturbation theory and adjoint operator via adjoint-state method. The inversion has improved the quality of the images and reduces the multi-parameter crosstalk comparing with the adjoint-based images. We have observed that the multi-parameter crosstalk problem is more prominent in the inversion images for Thomsen anisotropy parameters. Especially, the Thomsen parameter δ is the most difficult to resolve. We also analyze the multi-parameter crosstalk using scattering radiation patterns.

The linearized waveform inversion for VTI-elastic media presented in this article provides quantitative information of the rock properties that has the potential to help identify hydrocarbon reservoirs.