A5050109285- NMR spectroscopy and applications
- Seismic Imaging and Inversion Techniques
- Advanced MRI Techniques and Applications
- Hydrocarbon exploration and reservoir analysis
- Advanced NMR Techniques and Applications
- Advanced Neuroimaging Techniques and Applications
- Hydraulic Fracturing and Reservoir Analysis
- Drilling and Well Engineering
- Image and Signal Denoising Methods
- Model Reduction and Neural Networks
- Petroleum Processing and Analysis
- Geoscience and Mining Technology
- Enhanced Oil Recovery Techniques
- Geological Studies and Exploration
- Geochemistry and Geologic Mapping
- Reservoir Engineering and Simulation Methods
- Geophysical Methods and Applications
- Coal Properties and Utilization
Sinopec (China)
2017-2024
Research Institute of Petroleum Exploration and Development
2019
China University of Petroleum, Beijing
2012-2018
China University of Geosciences
2012-2014
China University of Geosciences (Beijing)
2012
Nuclear Magnetic Resonance (NMR) T2 inversion is the basis of NMR logging interpretation. The regularization parameter selection penalty term directly influences result. We implemented both norm smoothing and curvature methods for inversion, compared results with respect to optimal parameters (α opt) which were selected by discrepancy principle (DP), generalized cross-validation (GCV), S-curve, L-curve, slope L-curve methods, respectively. numerical indicate that DP method can lead an...
Nuclear magnetic resonance (NMR) [Formula: see text] inversion is an ill-posed problem in which regularization techniques are usually adopted to suppress the oscillations caused by noise solutions. The maximum entropy concept provides unbiased way obtain information from incomplete data, and it implicitly imposes a positive constraint on probability distribution, so we used method invert NMR echo data. We have developed simple effective for solving objective function of method. First,...
The sedimentary environment of the marine-continental transitional facies leads to complex reservoir lithologies characterized by rapid changes in lithology, presence thin interbeds, and strong heterogeneity both vertical horizontal directions. resultant difficulties with lithology identification pose challenges evaluation parameters prediction sweet spots. This study investigated reservoirs Permian Longtan Formation area A, southwestern Sichuan. Based on core descriptions, mineral...
Nuclear magnetic resonance (NMR) technology plays a significant role in petroleum exploration. NMR data can be processed using inversion methods to reflect the relaxation information of all components. We have developed new double-parameter regularization (DPR) method for data, whose terms consist Tikhonov and maximum entropy regularization. The objective function DPR was solved Levenberg-Marquardt method, proportional coefficient parameter obtained an iteration procedure, optimum selected...
Conventional logging methods have limitations in the evaluation of tight sandstone reservoirs. The multi-dimensional nuclear magnetic resonance (NMR) method has advantage that it can simultaneously measure transverse relaxation time (T2), longitudinal (T1) and diffusion coefficient (D). In this paper, we simulate NMR measurements with different wettability saturations by random walk obtain magnetization decays Carr–Purcell–Meiboom–Gill pulse sequences wait times (TW) echo spacings (TE) under...
The residual l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> norm is commonly used to measure the fitting error for a nuclear magnetic resonance (NMR) spectrum inversion. However, solution of objective function with sensitive noise. When 1 ≤ p <; 2, less In this letter, we develop method NMR inversion based on hybrid xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> /l norm, which behaves like small residuals and large residuals....
Evaluating the permeability and irreducible water saturation of tight sandstone reservoirs is challenging. This study uses distribution functions to fit measured NMR T2 distributions extract parameters for characterizing pore size distribution. These are then used establish prediction models reservoirs. Results comparing by Gauss Weibull show that fitting accuracy with function higher. The physical meaning statistical defined nonlinear using radial basis (RBF) method. Correlation...
The evaluation of oil content and mobility in shale reservoirs is the key to optimization "sweet spot" available resources. In order address challenge quantitative reservoirs, a combined multi-temperature pyrolysis NMR experimental platform procedure are innovatively designed implemented this paper. experiments reveal T2 distribution characteristics hydrocarbon components different reserve states. Accordingly, cutoff values determined, method based on logging for total movable established....
In-situ stress orientation is a key parameter in studying oil and gas migration accumulation, analyzing the stability of borehole wall during drilling, carrying out horizontal well design, fracturing reconstruction pattern layout water injection development. Accurately predicting in-situ reservoirs utmost importance for exploration It most effective commonly used method to evaluate by using induced fracture breakout imaging logging data. However, cases where or cannot be formed evaluated...
Coal bed methane and shale oil &gas are both important unconventional gas resources, whose reservoirs typical non-linear with complex various mineral components, the logging data interpretation model difficult to establish for calculate contents, empirical formula cannot be constructed due mineral. The radial basis function (RBF) network analysis is a new method developed in recent years; technique can generate smooth continuous of several variables approximate unknown forward model....
Two-dimensional (2D) nuclear magnetic resonance (NMR) inversion operates with massive echo train data and is an ill-posed problem. It very important to select a suitable method for the 2D NMR processing. In this study, we propose fast, robust, effective that improves computational efficiency of process by avoiding estimation some unneeded regularization parameters. Firstly, combines window averaging (WA) singular value decomposition (SVD) used compress obtain values kernel matrix....