Accurate in-situ stress characterization is essential for hydraulic fracturing design in shale reservoirs, yet 3D geomechanical model calibration still relies on iterative trial-and-error procedures that are computationally intensive and physically opaque. Sensitivity analysis, though widely used to evaluate the influence of elastic parameters, is typically treated as descriptive rather than predictive. This work proposes a sensitivity-driven inversion framework for efficient calibration of horizontal stresses in 3D geomechanical models. Controlled perturbation simulations on a baseline model quantify the responses of maximum and minimum horizontal stresses ($S_H$ and $S_h$) to variations in... More >

Seismic facies classification remains a critical yet challenging task in subsurface characterization due to the complexity of depositional systems and limitations of manual interpretation. This study presents a supervised deep learning workflow for seismic facies prediction using a dip-steered median filtered (DSMF) seismic volume. Ten facies label sets, representing minima and maxima responses, were derived from unsupervised vector quantization (UVQ) clustering and subsequently refined using Thalweg tracking, with 1,500 samples per class. These labels, together with the DSMF volume, were used to extract 3D cubelets (41×41×3) for training convolutional neural networks (CNNs). Three archite... More >

The pore structure of continental shale reservoirs is complex and diverse, exhibiting multi-scale pore size distributions spanning from nanometers to micrometers. In particular, accurate porosity measurement has remained a major challenge in shale reservoir characterization. To achieve accurate porosity determination for continental shale, this study takes the Gulong shale as a case example. Based on the fluid occupancy characteristics of shale pores, the pore space is classified into three types: gas-occupied, water-occupied, and oil-occupied pores. The volumes of these three pore types are measured experimentally via kerosene saturation, ethanol extraction, and solvent washing, respectivel... More >

Since its launch in 2025, Reservoir Science (RS) has completed its first year of development. This editorial reviews the journal’s progress over the past year, analyzes current challenges, and outlines future strategic directions. In the past year, RS has published 18 high-quality papers contributed by 63 authors from 7 countries and regions (as of May 30, 2026). The journal has been indexed in CAS. Adopting an Open Access model (CC BY), RS has established an international editorial board and published research covering reservoir exploration, characterization, CCUS, geothermal energy, underground hydrogen storage, reservoir materials science, environmental science, and artificial intellige... More >