Jiangfeng Guo

Nuclear magnetic resonance (NMR) logging is an effective method for evaluating petrophysical parameters and fluid identification, and it is significantly promising for unconventional reservoir exploration and development. However, NMR signal detected is very weak in unconventional reservoir due to low porosity and complex pore structure, which leads to the low data signal-to-noise ratio (SNR) and thus affects the accuracy of T₂ inversion. It is therefore necessary to undertake NMR data noise attenuation before inversion to improve data SNR, so as to enhance NMR inversion accuracy. A noise attenuation method for NMR data based on symplectic geometry mode decomposition (SGMD) was proposed in this paper. The kurtosis was introduced in the SGMD process to determine the optimal decomposition group and then the Pearson correlation coefficient was utilized to choose the optimal number of reconstruction components. The aim is to make the noise separated from the original signal adaptively with an efficient decomposition speed. The effects of the decomposition group and the reconstruction component were analyzed by numerical simulation. The validity and practicality of the proposed method were tested by comparing with the wavelet transform method and the empirical mode decomposition method through numerical simulations, core experiment data, and field NMR data.

Low-field nuclear magnetic resonance (NMR) has broad application prospects in the exploration and development of unconventional oil and gas reservoirs. However, NMR instruments tend to acquire echo signals with relatively low signal-to-noise ratio (SNR), resulting in poor accuracy of T₂ spectrum inversion. It is crucial to preprocess the low SNR data with denoising methods before inversion. In this paper, a hybrid NMR data denoising method combining empirical mode decomposition-singular value decomposition (EMD-SVD) was proposed. Firstly, the echo data were decomposed with the EMD method to low- and high-frequency intrinsic mode function (IMF) components as well as a residual. Next, the SVD method was employed for the high-frequency IMF components denoising. Finally, the low-frequency IMF components, the denoised high-frequency IMF components, and the residual are summed to form the denoised signal. To validate the effectiveness and feasibility of the EMD-SVD method, numerical simulations, experimental data, and NMR log data processing were conducted. The results indicate that the inverted NMR spectra with the EMD-SVD denoising method exhibit higher quality compared to the EMD method and the SVD method.

Nuclear magnetic resonance (NMR) logging, one of geophysical exploration methods, is very sensitive to pore fluid and is promising in unconventional reservoir exploration. However, the volcaniclastic reservoir is characterized by tightness, low porosity, and the micro- and nano-pore development. A number of short relaxation signals acquired by NMR logging instruments may be lost, since the echo spacing is not sufficiently short for downhole NMR measurements. Additionally, paramagnetic minerals in volcaniclastic rocks, such as iron and manganese, increase the internal magnetic field gradient, enhancing diffusion relaxation of pore fluids, and thus leading to the complex relationship between T2 spectra and pore size. Based on the above factors, a region-partitioned T2 spectra correction method in volcaniclastic reservoirs was proposed in this paper. The T2 spectra were divided into short (T2 < 10 ms) and long (T2 ≥ 10 ms) relaxation parts. For short relaxation correction, the relationship model between the normalized interval porosity at TE = 0.6 ms and the normalized T2 spectra signal intensity at TE = 0.1 ms, as well as the relationship model between the signal intensity of the shortest relaxation peak at TE = 0.1 ms and TE = 0.6 ms, was constructed and employed. For long relaxation correction, the internal gradient Gint determined from T2–G spectra was utilized to calculate and remove diffusion relaxation from T2 spectra at TE = 0.6 ms. The proposed method's effectiveness is validated through simulations and field NMR data processing.

Oil recovery in shale reservoirs is low due to the dynamics and wettability characteristics in mixed-wet shale oil reservoirs. Nuclear magnetic resonance (NMR) logging, a nondestructive and noninvasive technique, effectively evaluates the continuous dynamics and wettability in these reservoirs. The NMR numerical investigation can characterize the effects of dynamics and wettability, including varying wet regions and wet angles, on NMR responses, providing new insights into the frequency-dependent of T2-based petrophysical parameters. The NMR relaxation theory for mixed-wet shale oil reservoirs was proposed, and the relevant parameters were determined. The dynamics and wettability were characterized using the Shan Chen Lattice Boltzmann method, with constraints based on digital core technology. For the first time, the random walk method was employed to simulate the effects of water-wet regions with varying proportions, echo spacings, and wet angles on NMR responses in mixed-wet shale oil reservoirs at different frequencies. The proportions of water-wet regions, magnetic field frequencies, and echo spacings significantly influence porosity and T2LM, indicating that pore structure governs the dynamics and wettability and that petrophysical parameters can be characterized by their frequency dependence in mixed-wet shale oil reservoirs.

Despite the increased use of mechanochemistry for chemical reactions few options for reaction monitoring or solid state analysis are available. This work explores using T1 T2* 1H NMR to monitor the reaction between benzil or 4,4’ dimethybenzil with o phenylenediamine. For both reactions, the T1 T2* correlation plots show differences in relaxation times throughout the reaction. This work demonstrates using two different strageties to monitor the reaction progression. In the first case the reaction is monitered by the appearance of signals corresponding to the product, and side product water. In the second case the reaction is monitored by the replacement of the signals corresponding to the starting material, by signals corresponding to the product. This magnetic resonance correlation measurement provides an excellent option for whole sample solid state analysis by virtue of its simplicity and versatility.

In this paper, we present a new approach to monitoring mechanochemical transformations, based on a magnetic resonance method in which relaxation time correlation maps are used to track the formation of the popular metal-organic framework (MOF) materials Zn-MOF-74 and ZIF-8. The two-dimensional (2D) relaxation correlation measurement employed yields a T₁-T₂* spectrum which visually and analytically identifies different ¹H environments in the sample of interest. The measurement is well-suited to analyzing solid mixtures, and liquids, in complex systems. Application in this work to monitoring MOF formation shows changes in signal amplitudes, and their MR lifetime coordinates, within the 2D plots as the reaction progresses, confirming reaction completion. This new measurement provides a simple way to analyse solid-state reactions without dissolution, and there is a logical pathway to benchtop measurement with a new generation of permanent magnet-based MR instruments. The methodology described permits measurement in an MR compatible milling container, which may be directly transferred from the shaker assembly to the MR magnet for in-situ measurement of the entire reaction mixture.