Direct optimization of signal-to-noise ratio of CPMG-like sequences in inhomogeneous fields

Adaptive control for downhole nuclear magnetic resonance excitation

Nuclear magnetic resonance (NMR) measurements are performed with the pulse sequence and acquisition parameters set by the operator, which cannot be adjusted in real time according to sample characteristics. In one acquisition cycle, usually thousands of high-power pulses are transmitted and thousands of echo points are acquired. The power consumption cause the RF amplifier to overheat, and large amounts of acquired data may be invalid. Therefore, the optimization of excitation and acquisition processes is necessary to improve measurement efficiency. We explore a scheme for the real-time measurement of the samples by adaptively regulating the pulse sequence, which adapts the variable TE pulse sequence as the reconnaissance mode. The appropriate pulse sequence and reasonable parameters (NE, TE) can be selected according to the relaxation characteristics of the samples.This adaptive control strategy has great significance in guiding both dynamic and static measurements, and it is especially suitable for occasions where low magnetic field gradients and diffusion terms can be ignored. We also design a test circuit for adaptive control, which has the function of automatic parameter adjustment. By adjusting parameters such as the number of refocusing pulses, echo spacing, etc., the effective measurement of the samples can be achieved in practice.

Inline NMR via a Dedicated V-Shaped Sensor

Process monitoring and control require dedicated and reliable measures which reflect the status of the process under investigation. Although nuclear magnetic resonance is known to be a versatile analytical technique, it is only seldomly found in process monitoring. Single-sided nuclear magnetic resonance is one well known approach for being applied in process monitoring. The dedicated V-sensor is a recent approach that allows the inline investigation of materials in a pipe non-destructively and non-invasively. An open geometry of the radiofrequency unit is realized using a tailored coil, enabling the sensor to be applied for manifold mobile applications in in-line process monitoring. Stationary liquids were measured, and their properties were integrally quantified as the basis for successful process monitoring. The sensor, in its inline version, is presented along with its characteristics. An exemplary field of application is battery production in terms of anode slurries; thus, the first results on graphite slurries will demonstrate the added value of the sensor in process monitoring.

Improved design of frequency-swept pulse sequences

Frequency-swept pulses are extensively used in magnetic resonance spectroscopic techniques for the robust manipulation of spins across wide ranges of offset frequencies in the presence of B₁ field variations. Nevertheless, designing pulse sequences consisting of multiple frequency-swept pulses can be challenging, as they often require specific timings and parameter tweaking. In the present work we discuss a simple and general approach for constructing such sequences. We present new and improved pulse sequences for applications including broadband B₁-tolerant CPMG (CHORUS-CPMG), broadband chirped excitation with suppression of homonuclear J-modulation (PROCHORUS), and the further compression of frequency-swept pulse sequences by superposition of pulses which reduces pulse sequence durations by 25-40%. All sequence design strategies are accompanied by mathematical presentations, experimental results, and supporting simulations.

Analytical models of probe dynamics effects on NMR measurements

This paper provides a detailed analysis of three common NMR probe circuits (untuned, tuned, and impedance-matched) and studies their effects on multi-pulse experiments, such as those based on the Carr-Purcell-Meiboom-Gill (CPMG) pulse sequence. The magnitude of probe dynamics effects on broadband refocusing pulses are studied as a function of normalized RF bandwidth. Finally, the probe circuit models are integrated with spin dynamics simulations to design hardware-specific RF excitation and refocusing pulses for optimizing user-specified metrics such as signal-to-noise ratio (SNR) in grossly inhomogeneous fields. Preliminary experimental results on untuned probes are also presented.

Fourier and Laplace-like low-field NMR spectroscopy: The perspectives of multivariate and artificial neural networks analyses

Low field Nuclear Magnetic Resonance (LF-NMR) is a rich source of information for a wide range of samples types. These can be hard or soft solids, such as plastics or elastomers; bulk liquids or liquids absorbed in porous materials, and can come from biomaterials, biological tissues, archaeological artifacts, cultural heritage objects. LF-NMR instruments present a significant advance especially for in situ, ex situ and in vivo measurement of relaxation and diffusion. Moreover, high resolution 1D and 2D spectroscopy, as well as magnetic resonance (MR) imaging are available in these fields. In this work we discuss the advanced analysis of the data measured in LF-NMR from the perspectives of tertiary level that implies the analysis on principal components (PCA), and on the quaternary analysis that uses an artificial neural network (ANN). The principles of PCA and ANN are largely discussed. For the PCA analysis, a series of 52 spectra were analyzed, having been recorded in vivo by LF-NMR. Of these spectra, 38 were generated from normal uterus, 7 by uterus tissue with endometrial cancer, and another 7 were obtained from tissues of women with uterine cervical cancer. The PC1 vs PC2 plot was further analyzed using an artificial neural network, and the results are presented as 2D maps of probability. Furthermore, the perspectives of applying an ANN to solve the problem of Laplace-like inversion are discussed. An example of such ANN was presented and the performance was discussed. Finally, a model of complex ANN, capable to sequentially solve this kind of problems specific to LF-NMR is proposed and discussed.

Downhole Applications of Magnetic Sensors

In this paper we present a review of the application of two types of magnetic sensors—fluxgate magnetometers and nuclear magnetic resonance (NMR) sensors—in the oil/gas industry. These magnetic sensors play a critical role in drilling wells safely, accurately and efficiently into a target reservoir zone by providing directional data of the well and acquiring information about the surrounding geological formations. Research into magnetic sensors for oil/gas drilling has not been explored by researchers to the same extent as other applications, such as biomedical, magnetic storage and automotive/aerospace applications. Therefore, this paper aims to serve as an opportunity for researchers to truly understand how magnetic sensors can be used in a downhole environment and to provide fertile ground for research and development in this area. A look ahead, discussing other magnetic sensor technologies that can potentially be used in the oil/gas industry is presented, and what is still needed in order deploy them in the field is also addressed.