A machine learning framework for low-field NMR data processing

Low-field(nuclear magnetic resonance)NMR has been widely used in petroleum industry,such as well logging and laboratory rock core analysis.However,the signal-to-noise ratio is low due to the low magnetic field strength of NMR tools and the complex petrophysical properties of detected samples.Suppressing the noise and highlighting the available NMR signals is very important for subsequent data processing.Most denoising methods are normally based on fixed mathematical transformation or handdesign feature selectors to suppress noise characteristics,which may not perform well because of their non-adaptive performance to different noisy signals.In this paper,we proposed a“data processing framework”to improve the quality of low field NMR echo data based on dictionary learning.Dictionary learning is a machine learning method based on redundancy and sparse representation theory.Available information in noisy NMR echo data can be adaptively extracted and reconstructed by dictionary learning.The advantages and application effectiveness of the proposed method were verified with a number of numerical simulations,NMR core data analyses,and NMR logging data processing.The results show that dictionary learning can significantly improve the quality of NMR echo data with high noise level and effectively improve the accuracy and reliability of inversion results.

NMR fluid analyzer applying to petroleum industry

Tremendous progress of developing nuclear magnetic resonance(NMR)fluid analyzer has been witnessed in the oil industry for last two decades.This device allows extensive and accurate exploration of fluid properties,such as its hydrogen content,composition,viscosity,hydrogen index(HI),mud filtrate invasion,gas to oil ratio,average velocity,velocity distribution etc.,in the situations of in situ downhole or surface Petro-pipelines.In this review article,we focus on the design principle,manufacturing,implementation,methodology and applications of NMR fluid analyzer to oil and gas industry.A detailed description of the state-of-art NMR fluid analyzers was firstly given to exhibit their respective characteristics.With these experiences on hand,we introduced a series of NMR fluid analyzers designed by us at China University of Petroleum-Beijing with continuous optimizations,in terms of magnet construction,antenna layout,circuit design and operating surroundings.These systems discussed in this article have been demonstrated to achieve multiple NMR parameter acquisition when the fluid is in stationary or flowing state.In the end,a prototype was fabricated and validated considering a vast of engineering influences,such as variable temperatures in a large range,high pressure,limited volume,detection efficiency,etc.A particular emphasis of this paper is to expedite the measurement efficiency of the NMR fluid analyzer to reduce the operation costs.This dilemma can be Figured out by upgrading both pulse sequence and observational mode.For different fluid states,two rapid pulse sequences were proposed to sufficiently obtain the multi-dimensional NMR correlation map.Meanwhile,two observational modes were developed to take full advantage of the polarization time,during which the individual antenna was systematically switched.Another domain of interest in this review concerns the applications of this new tool.For stationary fluids case,accurate identification of fluid properties is of great value for scheme building in oil and gas exploration process.Particularly,it can acquire the fluid content by different NMR responses of different components.In addition,with Bloembergen theory and Stokes-Einstein equation,not only molecular dynamics and composition,but also oil viscosity can be readily evaluated.Moreover,HI information of crude oils will be speculated through partial least square regression.As for flowing fluids case,velocity is a significant parameter to understand the in situ fluid exploitation and therefore evaluate the productivity of certain oil wells or pipelines.Regarding to the unique magnet and antenna designs in our NMR fluid analyzer;this review adopts two distinct methods to obtain flow velocity at a wide rating scale.The first one is a time-of-flight method adaptive in a homogeneous magnetic field,which is suitable in the case of fluid at high flow velocity.The other one relies on the adjacent echo phase difference at a magnetic field with constant gradient,which is preferred for relatively low flow velocity.In the near future,this tool will be tested underground to offer individual fluid velocities by combining both the stationary and flowing analysis methods.

Low-field NMR inversion based on low-rank and sparsity restraint of relaxation spectra

In this paper,we proposed a novel method for low-field nuclear magnetic resonance(NMR)inversion based on low-rank and sparsity restraint(LRSR)of relaxation spectra,with which high quality construction is made possible for one-and two-dimensional low-field and low signal to noise ratio NMR data.In this method,the low-rank and sparsity restraints are introduced into the objective function instead of the smoothing term.The low-rank features in relaxation spectra are extracted to ensure the local characteristics and morphology of spectra.The sparsity and residual term are contributed to the resolution and precision of spectra,with the elimination of the redundant relaxation components.Optimization process of the objective function is designed with alternating direction method of multiples,in which the objective function is decomposed into three subproblems to be independently solved.The optimum solution can be obtained by alternating iteration and updating process.At first,numerical simulations are conducted on synthetic echo data with different signal-to-noise ratios,to optimize the desirable regularization parameters and verify the feasibility and effectiveness of proposed method.Then,NMR experiments on solutions and artificial sandstone samples are conducted and analyzed,which validates the robustness and reliability of the proposed method.The results from simulations and experiments have demonstrated that the suggested method has unique advantages for improving the resolution of relaxation spectra and enhancing the ability of fluid quantitative identification.

Semen parameters in men recovered from COVID-19

The novel coronavirus disease(COVID-19)pandemic is emerging as a global health threat and shows a higher risk for men than women.Thus far,the studies on andrological consequences of COVID-19 are limited.To ascertain the consequences of COVID-19 on sperm parameters after recovery,we recruited 41 reproductive-aged male patients who had recovered from COVID-19,and analyzed their semen parameters and serum sex hormones at a median time of 56 days after hospital discharge.For longitudinal analysis,a second sampling was obtained from 22 of the 41 patients after a median time interval of 29 days from first sampling.Compared with controls who had not suffered from COVID-19,the total sperm count,sperm concentration,and percentages of motile and progressively motile spermatozoa in the patients were significantly lower at first sampling,while sperm vitality and morphology were not affected.The total sperm count,sperm concentration,and number of motile spermatozoa per ejaculate were significantly increased and the percentage of morphologically abnormal sperm was reduced at the second sampling compared with those at first in the 22 patients examined.Though there were higher prolactin and lower progesterone levels in patients at first sampling than those in controls,no significant alterations were detected for any sex hormones examined over time following COVID-19 recovery in the 22 patients.Although it should be interpreted carefully,these findings indicate an adverse but potentially reversible consequence of COVID-19 on sperm quality.

A confirmed asymptomatic carrier of 2019 novel coronavirus

Since December 2019,the outbreak of infection caused by 2019 novel coronavirus(2019-nCoV)has become a major public health emergency worldwide.Approximately 40%of the confirmed cases of 2019-nCoV infection(judged by positivity of viral RNA testing)were initially asymptomatic but later developed overt clinical symptoms of coronavirus disease-2019(COVID-19).[1]A presumed asymptomatic carrier of 2019-nCoV was also reported.[2]But her infection of 2019-nCoV was not fully confirmed.As far as we know,confirmed 2019-nCoV carriers but without overt clinical symptoms have been not yet reported.