A5102009468- Seismic Imaging and Inversion Techniques
- Hydraulic Fracturing and Reservoir Analysis
- Drilling and Well Engineering
- Hydrocarbon exploration and reservoir analysis
- Seismic Waves and Analysis
- Water Quality Monitoring Technologies
- Educational Technology and Pedagogy
- Video Analysis and Summarization
- Reservoir Engineering and Simulation Methods
- Rock Mechanics and Modeling
- Labor market dynamics and wage inequality
- NMR spectroscopy and applications
- Water Quality Monitoring and Analysis
- Simulation and Modeling Applications
Tianjin University
2024
University of Houston
2019-2022
Ningbo University of Technology
2019
China National Offshore Oil Corporation (China)
2012-2013
Chengdu University of Technology
2012
Abstract In this paper, the grey theory, three type of artificial neural network (back-propagation network, radial basis function and generalized regression network) their combination were used to predict pH values in evaluation water quality. Based on measured data from Xielugang Jiaxin with post-hoc analysis for c p prediction, results showed that prediction by using has averaged relative error 0.61%, <0.65, p>0.7.
Abstract Rock in the subsurface composed of rock matrix and pore fluid is a two‐phase medium. So effective elastic parameters are influenced by matrix, structure fluid. Therefore, order to get relationship between porosity rock, influence other factors must be removed. Based on basic theory physics test data, we propose concept equivalent volume introduce Eshelby ellipsoid inclusion fracture theory. With reasonable assumption, Gassmann equation applied deduce establish related including...
The mismatched scales of seismic attributes and geological layering limit porosity estimation directly from data. This can be addressed by utilizing spectral decomposition machine learning techniques. First, we decompose the data into different frequency components. A variety then are extracted. We simultaneously predict logs, filtered to resolutions, using conventional deep algorithms. Methods used include support vector regression (SVR), random forest (RF), multilayer perceptron (MLP). sum...
The assumptions made in rock physics theories introduce many uncertainties into conventional modeling (RPM), which makes it difficult to implement accurate quantitative seismic interpretation workflows. We propose using machine learning algorithms address this issue. First, we build a theoretical model RPM workflow. use Hertz-Mindlin grain contact theory estimate the moduli of frame with optimized parameters. then create synthetic well logs by perturbing properties, such as lithology and...
One of the primary fluid indicators for direct hydrocarbon detection in sandstones using seismic reflectivity is difference between saturated-rock P-wave impedance and rock-frame impedance. This can be expressed terms observed squared a multiplier times square S-wave discrimination parameter that laboratory log measurements suggest varies over wide range. Theoretically, this related to ratio frame bulk shear moduli fluid-saturated rock densities. In practice, empirical determination may...
This study investigates U.S. unemployment rates among individuals aged 25 and older, segmented by four distinct levels of educational attainment. Understanding the interplay between education employment is crucial for effective policy-making long-term economic planning. To capture these dynamics, a regression model utilized to derive equations representing patterns observed in separate time series, each corresponding specific group. In addition this, logarithmic difference analysis applied...
Tight gas glutenite of low permeability exhibits reservoir properties very similar to those tight sandstone, with sweet spots occurring under conditions. The detection poses a challenge seismic methods due porosity and the stiff framework rocks. In this project, scheme extended elastic impedance (EEI) inversion was used detect in bodies formation A from an oilfield northeastern China. It is found petrophysical study that Poisson’s ratio good indicator gas-bearing reservoirs relatively high...
One of the primary fluid indicators for direct hydrocarbon detection using seismic amplitude anomalies is difference between saturated-rock P-wave impedance and rock-frame impedance. This can be expressed in terms observed squared a multiplier times square S-wave discrimination parameter that laboratory log measurements suggest varies over wide range. Theoretically, this simply related to ratio frame bulk shear moduli densities fluid-saturated rock. In practice, empirical determination may...
Fluid substitution of carbonates is more difficult than it in clastics for two reasons. First, there are much uncertainties rock physics modeling, especially how to acquire the moduli carbonate rocks' solid matrix, because most laboratory measurement data came from sand reservoirs and less attention has been paid its study. Second, us model pore geometry due their complex systems, hence evaluate influence on results fluid substitution. In order solve these problems, we firstly present a new...
With a more complex pore system compared with clastic rocks, carbonate rocks have not yet been well described by the present conventional rock physics models concerning its vagary of geometry as influence on elastic properties rocks. To better understand intrinsic effect rocks' properties, we propose factor depicting based in this paper. We start discussion and an analysis about And then, give introduction to new approach modeling construct structure basis Gassmann equation Eshelby-Walsh...
Summary Petrophysical properties such as porosity, saturation, permeability and shale content are important parameters for evaluation detailed characterization of the reservoir. The conventional method porosity estimation is implemented via rock physics modeling seismic inversion. assumptions made in theories inversion methods introduce many uncertainties ambiguities into estimation, which makes it difficult to accurately implement quantitative interpretation workflows. Therefore, we propose...