Nuclear Magnetic Resonance T2 Distribution Research Articles

Variation in Pore Structure Characteristics with Composition in the High Volatile Bituminous Coal of Binchang Area

Pore structure characteristics and the effect of lithotype and maceral on pore for three types of high-volatile bituminous coals from Binchang area were investigated by combined low-temperature nitrogen adsorption/desorption, nuclear magnetic resonance (NMR), scanning electron microscope (SEM) and maceral analysis. The low temperature N2 adsorption/desorption test results show that: micropores are more abundant than transitional pores with high BET surface area; two types of pore structures can be identified by adsorption/desorption isotherms; Pore morphology is mainly represented by well-connected, ink-bottled, cylindrical and parallel plate pores. NMR T2 distributions at full saturated condition are apparent or less obvious trimodal and three types of T2 distributions are identified; Seepage pores are better developed when compared with the middle-high rank coal. Further research found that the three coal lithotypes are featured by remarkably different pore structure characteristics and maceral contents of coal are linearly correlated to some of pore structure parameters.

Estimating NMR T2 distribution data from well log data with the use of a committee machine approach: A case study from the Asmari formation in the Zagros Basin, Iran

Abstract The Nuclear Magnetic Resonance (NMR) log is one of the most valuable logs in petroleum exploration which is used to precisely evaluate the reservoir and non-reservoir horizons. Along with porosity logs (neutron, density, sonic), NMR log is used to estimate the porosity and permeability of the hydrocarbon bearing intervals. The current study focuses on estimating NMR T 2 distribution data from conventional well log data with the use of artificial intelligent systems. The eight bin porosities of the combinable magnetic resonance (CMR) T 2 distribution alongside with the T 2 logarithmic mean (T 2 LM) values are predicted using the intelligent models developed in this study. The methodology applied here combines the results of the individual models in a committee machine with intelligent systems (CMIS) for estimating the NMR T 2 distribution and T 2 logarithmic mean data. The Fuzzy logic (FL), the adaptive neuro fuzzy system (ANFIS) and artificial neural networks (ANNs) are utilized as intelligent experts of the CMIS. The NN models are developed with four different training algorithms (Levenberg–Marquardt (LM), scaled conjugate gradient (SCG), one step secant (OSS) and resilient back-propagation (RP)) and the best one is chosen as the optimal NN expert of the CMIS. The CMIS assigns a weight factor to each individual expert by the simple averaging and weighted averaging methods. A genetic algorithm (GA) optimization technique is used to derive the weighted averaging coefficients. The results indicate that the GA optimized CMIS performs better than the individual experts acting alone for synthesizing the NMR T 2 curve and T 2 LM data from one specific set of conventional well logs.

An NMR-Based Analysis of Soil–Water Characteristics

Both direct and indirect methods for determining soil–water characteristic curves rely on determination of some empirical coefficients, which may not necessarily represent real microscopic mechanisms. Proton nuclear magnetic resonance (NMR) is a powerful tool for investigating water content and their interaction with solid particles in porous media. The NMR technique is widely used in food science and petroleum. In the present study, proton NMR spin–spin relaxation time (T 2) distribution measurement is integrated with a Tempe apparatus to characterize the hydraulic processes of unsaturated soils, shedding insights into the microscopic mechanisms of pore water distribution and migration in the soil during hydraulic cycles. It is revealed that during a drying process the drainage of pore water occurs sequentially from larger pores to smaller pores, whereas in a wetting process the water invades into the soil sequentially from smaller pores to larger pores. A new procedure is developed which can be used to determine the pore size distribution of the soil based on the NMR T 2 distribution measurements; compared to the traditional methods, the new method is rapid and non-destructive. The new procedure is validated by comparing the new result with the measurement of the mercury intrusion porosimetry.

Characterization of the stress sensitivity of pores for different rank coals by nuclear magnetic resonance

Nuclear magnetic resonance (NMR) experiments of stress sensitivity on the pore and fracture systems of coal samples with different ranks were performed. Pore compressibility was calculated based on the NMR results. The relationship between pore compressibility and effective stress was discussed and a mathematical model for pore compressibility was developed to describe the experimental data. The experimental results showed different characteristics of NMR T2 distributions, which were in good accordance to the diverse pore and fracture structures for the different rank coals. Medium and high rank coals have more developed pore space for adsorption, and the main peak of T2 spectra locate at the low T2 value section; while for the low rank coals, all the pores and fractures are well developed, with peaks corresponding to them are all obvious on the T2 spectra. Furthermore, the pore spaces showed different stress sensitivity for different rank coals. For low rank coals, seepage space changes dramatically as the confining pressure changes, and seepage space is the main controlling factor of stress sensitivity. As the metamorphism degree increasing, adsorption space becomes dominant in the pore and fracture structure of coals. Thus adsorption space in high and medium rank coals decreases significantly with the increase of the confining pressure, and stress sensitivity is controlled by their adsorption space, as suggested by the experimental results. The pore compressibility of the coals decreases with confining pressure increase and the experimental data can be accurately described by the new developed stress dependant pore compressibility model.

Comments on “More general capillary pressure and relative permeability models from fractal geometry” by Kewen Li

Permeability is a crucial parameter evaluating tight sandstone reservoir. Previous permeability estimation methods based on nuclear magnetic resonance (NMR) are commonly suitable for well-sorted, highly porous and unconsolidated sandstone, but incurring large errors when applied to tight sandstone. This study introduces the fractal dimension based NMR permeability estimation for tight sandstone. Core permeability and NMR measurements were performed on thirty tight sandstone samples selected from the Jurassic rocks in the Sichuan Basin, China. We proposed two fractal-based NMR permeability models for tight sandstone in the studying area, which are considered as the modifications of the SDR and T-C models, examining the applications on core plug samples and comparing the results with other permeability models. Results show that tight sandstones have wider T2 distribution and weaker correlation between throat size and pore size than unconsolidated/clean sandstones. The proposed coefficient-based optimal fitting method can obtain more accurate fractal dimensions of micropores and macropores than these achieved by subjective and empirical methods and commonly used T2cutoff method. The proposed models introduced in this research have two advantages: (1) the models have high accuracy since the effective pore structure parameters (porosity, FFI/BVI and T2LM) are adopted. The complex pore structure of tight sandstones is considered by using fractal dimensions. (2) the models are easy to implement by following the concise formats of the Timur-Coates model and SDR model. In practice, the models can be applied to predict permeability of tight sandstone in the lab, or in the field requiring NMR T2 distributions as basic data, integrating core permeability to determine fitting parameters in the models.

Assessment of structural changes of human teeth by low-field nuclear magnetic resonance (NMR)

A technique of low-field pulsed proton nuclear magnetic resonance (NMR) spin relaxation is described for assessment of age-related structural changes (dentin and pulp) of human teeth in vitro. The technique involves spin–spin relaxation measurement and inversion spin–spin spectral analysis methods. The spin–spin relaxation decay curve is converted into a T2 distribution spectrum by a sum of single exponential decays. The NMR spectra from the extracted dentin-portion-only and dental pulp-cells-only were compared with the whole extracted teeth spectra, for the dentin and pulp peak assignments. While dentin and pulp are highly significant parameters in determining tooth quality, variations in these parameters with age can be used as an effective tool for estimating tooth quality. Here we propose an NMR calibration method—the ratio of the amount of dentin to the amount of pulp obtained from NMR T2 distribution spectra can be used for measuring the age-related structural changes in teeth while eliminating any variations in size of teeth. Eight teeth (third molars) extracted from humans, aged among 17–67 years old, were tested in this study. It is found that the intensity ratio of dentin to pulp sensitively changes from 0.48 to 3.2 approaching a linear growth with age. This indicates that age-related structural changes in human teeth can be detected using the low-field NMR technique.

Study of Vuggy Carbonates Using NMR and X-Ray CT Scanning

Summary Most existing nuclear magnetic resonance (NMR) permeability correlations for carbonates assume that vugs do not contribute to permeability. The objective of this work is to improve permeability estimation from NMR responses for carbonates by including vug connectivity. Six carbonate samples from a west Texas field were studied. NMR T2 measurement, mercury porosimetry, thin-section imaging [using optical microscopy and a scanning electron microscope (SEM)], computerized tomography (CT) scanning, and electrical measurements were conducted. The permeability of the samples studied is controlled by the channels that connect vugs. Capillary pressure and NMR T2 measurements show multimodal pore-throat and pore-body-size distributions. A modified Chang model, which includes the tortuosity factor, is proposed and proven to yield a better permeability prediction than the original Chang model. It is also shown that for the samples studied, the tortuosity can be estimated from NMR T2 distribution, hence allowing permeability prediction from the NMR T2 distribution alone.

Evaluation of Nuclear Magnetic Resonance (NMR) Technology to Define Carbonate Pore Networks: ABSTRACT

Within complex carbonate reservoirs, it is difficult to develop porosity-permeability relationships. Nuclear Magnetic Resonance (NMR) technology was evaluated to see if it could help define the petrophysics of carbonates and improve porosity- permeability transforms. Lower San Andres/Glorieta/Upper Clear Fork carbonates from the North Cowden field were used as a test case. They contain diverse pore networks of interparticle, intraparticle, inter moldic, and microporosity developed in limestones and dolostones. NMR technology used to evaluate the carbonate rocks was based on laboratory-derived core analyzer measurements. Sample selection covered a range of porosity and permeability values, as well as different pore network types. NMR porosity was obtained from curve fitting of the echo trains using an unconstrained bi-exponential model. A comparison of [open quotes]T2 distribution[close quotes] (measure of presize) measured by NMR and [open quotes]pore-body-size distribution[close quotes] from thin-sections (made from ends of plugs) show, a strikingly similar pattern. NMR T2 distribution also agrees well with [open quotes]pore-throat-size distribution[close quotes] by mercury injection on the same plug used for the NMR tests. The general porosity-permeability relationship from core data for the North Cowden carbonates is very poor, because of their complex mineralogy, broad pore-size distribution, and range of pore-system configurations. However, an excellentmore » relationship between macro-porosity, derived from NMR core T2 measurements, and core permeability was obtained. The elimination of noneffective microporosity in these rocks is necessary to develop a useful porosity- permeability transform. NMR technology is useful in estimating pore-size distribution and permeability in carbonates.« less