Multiscale Fractures Characterization Based on Ant Colony Optimization and Two-Dimensional Variational Mode Decomposition

Abstract

Hydrocarbon exploration in fractured reservoirs requires accurate estimates of fracture characteristics such as fracture orientations and fracture development degrees. The coherence method, which measures the degree of similarity between the multichannel seismic data, can image fractures by detecting variation anomalies in the seismic signals. However, it is weak in precisely positioning fractures and is sensitive to noise. We use an improved ant colony optimization (ACO) algorithm that adopts both coherence data and edge detection data as heuristic factor to refine the coherence data. As a distinctive time–frequency analysis method, variational mode decomposition (VMD) is a flexible method with excellent time–frequency resolution. We propose a measure factor combining mutual information and energy entropy to judge how many intrinsic mode functions to be decomposed are most suitable. Since fracture characterization is similar to image analysis, we propose a novel method combining ACO-coherence with a two-dimensional VMD (2D-VMD) to meticulously depict fractures at different scales and different directions. First, the seismic coherence data are obtained via a dip scanning coherence algorithm. Then, the coherence data are refined by the improved ACO algorithm. We extract the slice along the target stratum from the ACO-coherence data, and the slice is decomposed into different frequency band images using the 2D-VMD method. After applying the method to real seismic data from a typical fractured reservoir, it is clear that the method we propose is capable of revealing fractures at different scales and different directions with high precision.