Acoustic Remote Detection Logging for Heterogeneous Reservoirs

Acoustic Remote Detection Logging can extend the investigation range of conventional borehole logging from the immediate vicinity of the borehole to several meters and even tens of meters, providing complementary information for formation evaluation in reservoirs with heterogeneity such as fracture–cavity systems and thin interbeds. Such complex anomalous bodies may reduce the effectiveness of conventional rock-physics log interpretation. Overall, the current work still faces two main issues: the lack of geology-constrained 3D models and the lack of more efficient and transferable interpretation tools, which makes it difficult to establish a stable relationship between complicated reflected wavefields and subsurface heterogeneity.

This study focuses on Acoustic Remote Detection Logging and develops geology-constrained 3D heterogeneous modeling and response analysis. First, a 3D stochastic medium is generated using the spectral synthesis method to produce correlated random fields, which are then mapped to elastic-parameter perturbation fields. Then, a bisection-based thresholding scheme is applied to satisfy a target volume fraction (or porosity), and local-maximum detection is used to determine seed points and spatial distributions for cavities, enabling 3D construction of fracture–cavity heterogeneity. Cavity geometry and scale parameters are constrained by statistical characteristics derived from existing geological and logging data. Finally, CUDA-based parallelization is introduced to improve the efficiency of full 3D model generation and support rapid construction of high-resolution reservoir models.

Based on forward simulations of Acoustic Remote Detection Logging responses excited by dipole shear-wave sources, we design parameter combinations covering formation porosity and fracture–cavity geometric parameters, and summarize the results into response charts/templates for interpretation. These charts provide quantitative relationships between fracture parameters and key waveform features, supporting comparative identification and interpretation of fracture development, orientation, and spatial position under different geological scenarios. In addition, we explore using a model for feature discrimination under chart-based constraints, thereby providing auxiliary support for comparative evaluation and interpretation of fracture parameters.