Low-field nuclear magnetic resonance (NMR) acts as an indispensable borehole logging method for the pore size characterization and formation evaluation, including the estimation of the reservoir parameters and fluid discrimination.

The YGH basin , located in the northern South China Sea, is characterized by rapid subsidence rate, high geothermal gradient, and high formation pressure coefficient. The overpressure and low-permeability reservoirs of the YGH Basin is featured with Fine-grained lithology, elevated shale content, minute pore sizes, and complex pore structures . The NMR responses are significantly affected by measurement parameters such as echo spacing. Notable discrepancies exist between the core NMR T₂ spectrum and the NMR logging T₂ spectrum. Key parameters derived from NMR logging, such as the T₂ geometric mean and fractal dimension, fail to accurately represent the true characteristics of the rock, thereby posing substantial challenges for precise permeability evaluation.

For better estimating the reservoir permeability using the low field NMR logging data, we conducted comprehensive petrophysical measurements such as NMR, CT scanning, grain size analysis, and mercury injection capillary pressure(MICP), specifically tailored to the characteristics of overpressure and low-permeability reservoirs. Pore structure parameters were extracted from these petrophysical experiments, and the self-organizing map (SOM) unsupervised clustering method was employed to classify the pore structures of overpressure and low-permeability reservoirs. Based on the principle of phase control, multiple sets of echo spacing core NMR experiments were conducted on representative samples of different pore structure types. Systematic analysis of echo spacing 's impact on T₂ spectra lead to the development of an empirical model relating T₂ geometric mean, fractal dimension, and echo spacing, with a focus on the shortest echo spacing of 0.2 ms. This model provides essential data support for correcting T₂ geometric mean and fractal dimension derived from NMR logging. Building on this research, the traditional Timur formula was refined by fractal dimension, significantly enhancing the accuracy of permeability calculations for overpressure and low-permeability reservoirs.

The research findings indicate that there exists a negative correlation between the T₂ geometric mean value and fractal dimension, with respect to the echo interval. As the pore diameter of the rock diminishes, the porosity intensifies, accompanied by an augmentation in clay content, leading to a greater influence of echo spacing on the geometric mean of T₂ and fractal dimension. By employing an enhanced permeability model, the derived permeability values demonstrate a high degree of consistency with measured data, achieving an average relative error of approximately 15%. This level of accuracy fulfills the criteria for assessing low-permeability reservoirs.

How to cite: Yang, H., Ge, X., Xu, Y., Tang, D., Wu, B., and Wu, Y.: Correction of Echo Spacing and Advanced Permeability Modeling for Key NMR Parameters in Overpressure and Low-Permeability Reservoirs of the YGH Basin, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3687, https://doi.org/10.5194/egusphere-egu25-3687, 2025.

Short T2 relaxation components are typical characteristics of porous media such as soil and rock. The ultra-short TE NMR method based on the CPMG sequence has created conditions for the overall measurement of such samples. In the evaluation of sample heterogeneity and the porous flow, in addition to the overall T2 spectrum, the 1D or multi-dimensional T2 mapping is more needed. Traditional MRI technology based on pulsed gradient field is limited by the gradient spatial encoding time and gradient eddy currents, resulting in relatively long TE, with the shortest TE being about 1.5ms, which is significantly different from the ultra-short TE required for the porous media. 1D spatially resolved T2 mapping based on constant gradient fields is a passive effect brought by the gradient magnetic field of NMR logging tools. The gradient value is not adjustable, making it difficult to regulate the layer thickness.

It is feasible to use traditional MRI gradient system combined with cooling modules to achieve 1D spatially resolved T2 mapping under constant gradient field conditions. The challenge lies in the contradiction between the Larmor frequency range in the sample selection layer direction and the -3dB bandwidth of the radio frequency coil. To address this issue, we used high Q and narrowband radio frequency coils to ensure the SNR. During 1D spatial layer selection excitation, the resonance point is tuned to match different excitation positions of the sample, or the sample position is moved to the fixed excitation frequency. Therefore, there are two technical branches, one is the radio frequency coil tuning method and the other is the sample movement method.

Since porous media have internal gradient fields, excessively high magnetic field strength will introduce internal diffusion relaxation effects. Therefore, this abstract focuses on the non-correction method which is suitable for porous media. It combines actual cases to analyze the technical features and comparison of the two branches of the non-correction method. The advantages of the tuning method are that the sample position is fixed, which is suitable for measurement conditions with peripheral accessories on the sample. The disadvantages are that the sample test length is limited, and the radio frequency hardware is complex. The advantages of the sample movement method are that the test sample length is not limited, and the radio frequency hardware is simple. The disadvantage is that sample movement is not suitable for measurement conditions with peripheral accessories. In applications, the appropriate method can be chosen according to actual needs.

How to cite: Ge, X., Wu, F., and Zhao, J.: Ultra-short TE NMR One-dimensional Spatially Resolved T2 Mapping Method for Porous Media, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3893, https://doi.org/10.5194/egusphere-egu25-3893, 2025.

Lacustrine shale oil resources are crucial for maintaining energy supply. The types and contents of fluids are key factors in estimating the resource potential and oil recovery of organic-rich shales. Accurately identifying the fluid types in shale oil reservoir successions, which are characterized by significant lithological heterogeneity, is a significant challenge. Although numerous methods for determining porosity and fluid saturation have been proposed in previous studies, many are only applicable in limited situations and have limited accuracy. In this research, an advanced logging technique, Combinable Magnetic Resonance logging (CMR-NG), is employed to evaluate fluid types. Two-dimensional Nuclear Magnetic Resonance (2D-NMR) experiments were conducted on reservoir rocks under different conditions (as received, after drying at 105℃, and after kerosene imbibition) to define the fluid types and classification criteria. In addition, the contents (proportions) of various types of fluids were estimated. Subsequently, the contributions of organic matter and mineral compositions were investigated using corresponding Rock-Eval pyrolysis parameters and various mineral contents obtained from X-ray Diffraction. Then, the contents of different fluid types were calculated using CMR-NG (Combinable Magnetic Resonance logging, also known as 2D NMR logging). Based on the fluid classification criteria under experimental conditions and production data, the most favorable model and optimal solution for logging evaluation were selected. Finally, the fluid saturations were calculated for a single well. The results indicate that six fluid types (kerogen-bitumen-Group OH, irreducible oil, movable oil, clay-bound water, irreducible water, and movable water) can be recognized through the applied 2D-NMR test. The kerogen-bitumen-Group OH is mainly affected by pyrolysis hydrocarbon (S2), and irreducible oil is influenced by soluble hydrocarbon (S1). However, due to the effects of underground environmental conditions on the instruments, kerogen-bitumen-Group OH and clay-bound water cannot be detected by CMR-NG. The Q8 and Q9 layers of the Qing 2 Member of the Cretaceous Qingshankou Formation, Gulong Sag, Songliao Basin, China are identified as the most favorable layers for shale oil. This study provides insights into the factors controlling fluid types and contents, offering guidance for the exploration and development of unconventional resources, such as geothermal and CCUS (carbon capture, utilization, and storage) reservoirs.

How to cite: Pang, X. and Wang, G.: Insights into fluid types in unconventional resources reservoirs, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6662, https://doi.org/10.5194/egusphere-egu25-6662, 2025.

The study area is located at the northwest end of Qaidam Basin. The exploration target horizon of the study area is the Paleogene Lower Ganchaigou Formation, which is a set of shore-shallow to semi-deep lacustrine sediments. The rock composition is characterized by the mixed deposition of argillaceous, carbonate and clastic particles.
The main reservoir types are micro- and nano-scale dolomite intercrystalline pores. a large number of intercrystalline pores were formed during the process of penecontemporaneous dolomization. Samples were taken from the drilling cores at a sampling depth of 3100m-4050m. The purpose of this method is to distinguish the movable fluid from the bound fluid by multiple centrifugation and NMR(nuclear magnetic resonance) tests, and to determine the lower limit of the pore throat radius of the movable fluid distribution according to the relation between the fluid and the pore throat, and to determine the lower limit of the physical property through the relation between the physical property and the pore throat radius.
The pore throat distribution range of the samples with carbonate intercrystalline pore in the lower Ganchaigou Formation of Yingxi area in the process of mercury injection was 11 nm to 220 nm, and the pore throat distribution range in the process of mercury ejection was 40 nm to 1500 nm.

Through saturated fluid state NMR test, it is believed that the pore throat radius of intercrystalline pore developed samples is 0-160nm, and the fluid is planar distribution, and the movable fluid accounts for 13.7%. The lower limit of pore throat containing movable fluids radius were determined to be 47nm through the separation point of accumulated curve of saturation state and centrifugal state, and it was analyzed that the lower limit of pore throat containing movable fluids were mainly affected by the median radius.The lower limit of porosity was calculated by substituting the lower limit of pore throat of movable fluid distribution into the fitting formula of the median radius of pore throat and gas porosity. There is a good correlation between permeability and test pressure. The curve of permeability and test pressure shows that when the gas permeability is less than 0.02mD, the permeability decreases rapidly with the increase of pressure, indicating that the gas flow characteristics of samples with permeability below 0.02mD and samples above 0.02mD are quite different.

How to cite: zhang, S., pan, S., wang, G., zhang, X., and fu, J.: Determination of petrophysical property cutoffs of tight lacustrine carbonate reservoir, Qaidam Basin, China, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7711, https://doi.org/10.5194/egusphere-egu25-7711, 2025.

The mineral composition of shale oil reservoirs in Jiyang Depression of Bohai Bay Basin, East China, is complex, the storage space is fine and tiny, and conventional logging  methods have poor applicability. Therefore, nuclear magnetic resonance logging, which can directly obtain pore information, has been widely applied in the Shengli Jiyang shale oil reservoirs. By systematically analyzing the one-dimensional and two-dimensional nuclear magnetic resonance logging data of shale oil wells in Shengli Oilfield, combined with asymmetric Gaussian function fitting technology and clustering analysis methods, the corresponding T2 cut-off values and T1/T2 value range limits for different fluid types were respectively determined. The results indicate that the pore fluid classification results of two-dimensional nuclear magnetic resonance logging are more detailed, and the movable fluid is located in the upper right corner of the spectrum, corresponding to T1/T2 values of 3 to 20. Using this model to calculate effective porosity and movable oil porosity. By comparing the tracer results, it indicates that the effective porosity of the high-yield well sections of the actual production wells was 6% to 13%, and the movable oil porosity was 2% to 6%. In other well sections, the effective porosity was less than 6%, and the movable oil porosity was less than 2%. Based on this as the main basis, the evaluation criteria for sweet spots in Shengli shale oil were established, and the shale sweet spot level was divided.

How to cite: Li, Z., Lin, C., and Liu, P.: Application of nuclear magnetic resonance logging in Shengli shale oil reservoir, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8799, https://doi.org/10.5194/egusphere-egu25-8799, 2025.

A new method for permeability estimation in tight sandstone formations based on the BSS algorithm and NMR data is proposed. BSS algorithm is introduced into the data processing of laboratory and downhole NMR data, and relaxation components with different NMR responses and pore size distributions can be obtained. The influence of pore structure on the percolation capacity is also discussed. The new method achieves great results in tight sandstone formations.

BSS algorithm refers to the process of separating various source signals from the observed signal when the theoretical model of the source signal is unknown and obtaining the best estimation of the source signal model and signal amplitude. When applying the BSS algorithm to NMR data processing, the laboratory and downhole NMR data can be considered as the observed signal, the relaxation components with specific NMR response can be considered as the source signal, and the proportions of different relaxation components can be considered as the signal amplitude. Based on the BSS algorithm, NMR responses and proportions of different components can be obtained.

We applied the BSS algorithm to the laboratory and downhole NMR data. Four pore types with different pore radius can be discriminated and their proportion can be extracted from the laboratory and downhole NMR data. The permeability of tight sandstone formation is affected by many factors and has poor correlations with the porosity. Based on the thin section observation, MICP and NMR analysis, the pore space of tight sandstone formation is complex and can be divided into micropore, mesopore, macropore and megapore. Pore structure is one of the main influential factors of permeability in tight sandstone formations. Relaxation components with the same NMR response and their proportions can be extracted from the BSS algorithm. Four relaxation components referring to different pore types can be obtained from laboratory and downhole NMR data. The permeability of tight sandstone formation is positively correlated with proportions of macropore and megapore, while negatively correlated with proportions of micropore and mesopore. A new permeability estimation method is established based on porosity, geometrical T₂ value, the sum proportion of macropore and megapore, and the sum proportion of micropore and mesopore. The new model achieves great results compared with the conventional models. The new method can be easily extended in other tight sandstone formations where the main influential factors of permeability are porosity and pore structure. Besides, laboratory experiments and core calibration can significantly improve the accuracy of permeability estimation.

How to cite: Liu, J.: A new permeability estimation method based on blind source separation and NMR data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18330, https://doi.org/10.5194/egusphere-egu25-18330, 2025.