A5086290026- Hydraulic Fracturing and Reservoir Analysis
- Drilling and Well Engineering
- Reservoir Engineering and Simulation Methods
- Groundwater flow and contamination studies
- Seismic Imaging and Inversion Techniques
- Enhanced Oil Recovery Techniques
- Advanced Mathematical Modeling in Engineering
- Hydrocarbon exploration and reservoir analysis
- Advanced Numerical Methods in Computational Mathematics
- Lattice Boltzmann Simulation Studies
- Probabilistic and Robust Engineering Design
- Geological Modeling and Analysis
- Rock Mechanics and Modeling
- CO2 Sequestration and Geologic Interactions
- Composite Material Mechanics
- Heat and Mass Transfer in Porous Media
- Methane Hydrates and Related Phenomena
- Seismic Waves and Analysis
- NMR spectroscopy and applications
- Structural Health Monitoring Techniques
- Urban Stormwater Management Solutions
- Atmospheric and Environmental Gas Dynamics
- Grouting, Rheology, and Soil Mechanics
- Image Processing Techniques and Applications
- Numerical Methods and Algorithms
China University of Petroleum, Beijing
2022-2025
King Fahd University of Petroleum and Minerals
2018-2024
Sinopec (China)
2023-2024
Peking University
2010-2017
University of Southern California
2013-2016
Southern California University for Professional Studies
2014-2015
Stanford University
2015
University of Maryland, College Park
2012
Hong Kong University of Science and Technology
1999-2000
University of Hong Kong
1999-2000
The first Geo-Energy Frontier Forum with the theme of "opportunities and challenges for geo-energy exploration development" was successfully held in Wuhan, recently. forum included 32 sessions, mainly focused on four directions: development reserve, petroleum geophysical exploration, oil gas geology, field engineering. This paper summarizes key findings 22 nd session titled "Reservoir stimulation unconventional resources". A total 17 experts scholars participated presentations, covering a...
The shale gas development process is complex in terms of its flow mechanisms and the accuracy production forecasting influenced by geological parameters engineering parameters. Therefore, to quantitatively evaluate relative importance model on performance, sensitivity analysis required. are ranked according coefficients for subsequent optimization scheme design. A data-driven global (GSA) method using convolutional neural networks (CNN) proposed identify influencing production. CNN trained a...
Summary The porous media community extensively utilizes digital rock images for core analysis. High-resolution (HR) that possess sufficient quality are essential but often challenging to acquire. Super-resolution (SR) approaches enhance the resolution of and provide improved visualization fine features structures, aiding in analysis interpretation properties, such as pore connectivity mineral distribution. However, there is a current shortage real paired microscopic SR training. In this...
Research activities are currently being conducted to study multiphase flow in hydrate-bearing sediments (HBS). In this study, view of the assumption that hydrates evenly distributed HBS with two major hydrate-growth patterns, i.e., pore filling (PF hydrates), wall coating (WC hydrates) and a combination two, theoretical relative permeability model is proposed for gas-water through HBS. Besides, model, change structure (e.g., radius) due effective stress taken into account. Then, validation...
Abstract The probabilistic collocation method (PCM) has drawn wide attention for stochastic analysis recently. Its results may become inaccurate in case of a strongly nonlinear relation between random parameters and model responses. To tackle this problem, we proposed location‐based transformed PCM (xTPCM) displacement‐based (dTPCM) previous parts series. Making use the transform response space, above two methods, however, have certain limitations. In study, introduce time‐based (tTPCM)...
A well production rate is an essential parameter in oil and gas field development. Traditional models have limitations for the estimation, e.g., numerical simulations are computation-expensive, empirical based on oversimplified assumptions. An artificial neural network (ANN) intelligence method commonly used regression problems. This work aims to apply ANN model estimate (OPR), water ratio (WOR), (GOR). Specifically, data analysis was first performed select appropriate operation parameters...
This report presents our new findings in microscopic fluid flow based on digital rocks. Permeability of rocks can be estimated by pore-scale simulations using the Stokes equation, but computational cost extremely high due to complicated pore geometry and large number voxels. In this study, a novel method is proposed simplify three-dimensional simulation multiple decoupled two- dimensional ones, each two-dimensional provides velocity distribution over slice. By approach, expensive equation...
Accurate characterization of the threshold pressure gradient (TPG) in shale oil reservoirs is essential for production. However, oil–water two-phase flow through with narrow pores involves thermal–hydrological–mechanical coupling, and relationship between TPG pore structures under multiple mechanisms has not been adequately modeled mathematically. In this paper, an analytical model derived first by considering combined effects effective stress, temperature, capillary pressure, structures,...
Abstract The accurate prediction of Darcy‐scale permeability (absolute and gas‐water relative permeability) hydrate‐bearing sediments (HBS) plays a crucial role in assessing reservoir potential optimizing recovery strategies. However, the challenges field coring, rigorous conditions encountered laboratory tests, multi‐scale pore structure characteristics HBS complicate understanding relationship between structures HBS. In this study, we propose an innovative upscaling method that integrates...
Statistical prediction is often required in reservoir simulation to quantify production uncertainty or assess potential risks. Most existing quantification procedures aim decompose the input random field independent variables, and may suffer from curse of dimensionality if correlation scale small compared domain size. In this work, we develop test a new approach, K-means clustering assisted empirical modeling, for efficiently estimating waterflooding performance multiple geological...
Digital rock analysis is a promising approach for visualizing geological microstructures and understanding transport mechanisms underground geo-energy resources exploitation. Accurate image reconstruction methods are vital capturing the diverse features variability in digital samples. Stable diffusion, cutting-edge artificial intelligence model, has revolutionized computer vision by creating realistic images. However, its application still emerging. This study explores applications of stable...
Anisotropic meshes are important for efficiently resolving incompressible flow problems that include boundary layer or corner singularity phenomena. Unfortunately, the stability of standard inf–sup stable mixed approximation methods is prone to degeneracy whenever mesh aspect ratio becomes large. As an alternative, a stabilized method considered here. Specifically, robust priori error estimate local jump Q1–P0 introduced by Kechkar & Silvester (1992, Analysis locally finite element Stokes...