A study on the temperature sensitivity of NMR porosity in porous media based on the intensity of magnetization Dedicated to the special issue “Magnetic Resonance in Porous Media”

The measurement of nuclear magnetic resonance(NMR)porosity is affected by temperature.Without considering the impact of NMR logging tools,this phenomenon is mainly caused by variations in magnetization intensity of the measured system due to temperature fluctuations and difference between the temperature of the porous medium and calibration sample.In this study,the effect of temperature was explained based on the thermodynamic theory,and the rules of NMR porosity responses to temperature changes were identified through core physics experiments.In addition,a method for correcting the influence of temperature on NMR porosity measurement was proposed,and the possible factors that may affect its application were also discussed.

Reservoir evaluation using petrophysics informed machine learning:A case study

relationships between logging data and reservoir parameters.We compare our method’s performances using two datasets and evaluate the influences of multi-task learning,model structure,transfer learning,and petrophysics informed machine learning(PIML).Our experiments demonstrate that PIML significantly enhances the performance of formation evaluation,and the structure of residual neural network is optimal for incorporating petrophysical constraints.Moreover,PIML is less sensitive to noise.These findings indicate that it is crucial to integrate data-driven machine learning with petrophysical mechanism for the application of artificial intelligence in oil and gas exploration.

Transfer learning for well logging formation evaluation using similarity weights

Machine learning has been widely applied in well logging formation evaluation studies.However,several challenges negatively impacted the generalization capabilities of machine learning models in practical imple-mentations,such as the mismatch of data domain between training and testing datasets,imbalances among sample categories,and inadequate representation of data model.These issues have led to substantial insufficient identification for reservoir and significant deviations in subsequent evaluations.To improve the transferability of machine learning models within limited sample sets,this study proposes a weight transfer learning framework based on the similarity of the labels.The similarity weighting method includes both hard weights and soft weights.By evaluating the similarity between test and training sets of logging data,the similarity results are used to estimate the weights of training samples,thereby optimizing the model learning process.We develop a double experts’network and a bidirectional gated neural network based on hierarchical attention and multi-head attention(BiGRU-MHSA)for well logs reconstruction and lithofacies classification tasks.Oil field data results for the shale strata in the Gulong area of the Songliao Basin of China indicate that the double experts’network model performs well in curve reconstruction tasks.However,it may not be effective in lithofacies classification tasks,while BiGRU-MHSA performs well in that area.In the study of constructing large-scale well logging processing and formation interpretation models,it is maybe more beneficial by employing different expert models for combined evaluations.In addition,although the improvement is limited,hard or soft weighting methods is better than unweighted(i.e.,average-weighted)in significantly different adjacent wells.The code and data are open and available for subsequent studies on other lithofacies layers.

Blood oxygen level–dependent functional magnetic resonance imaging can evaluate the efficiency of transcatheter arterial chemoembolization in hepatocellular carcinoma

Hepatocellular carcinoma(HCC) is among the most common malignant tumors worldwide, and transcatheter arterial chemoembolization(TACE) technology has become the first-line treatment for advanced HCC. Another important, recently developed technique is blood oxygen level–dependent functional magnetic resonance imaging(BOLD-fMRI), which utilizes hemoglobin as an endogenous contrast agent and measures deoxygenated hemoglobin content by sampling the oxygen content of tissues, thus reflecting the hemodynamics and pathophysiologic changes in body organs. Currently this technology is being used in patients with liver tumors;that is, it serves as an important tool in follow-up after TACE. The present paper summarizes these developments.

Development of Radio Frequency Heating Technology for Shale Oil Extraction

With the shortage of energy and the rise of crude oil in the world, the development of oil shale is gaining more attention globally. To solve the problem of traditional heat conduction with low efficiency and high cost for oil shale, a new technology called radio frequency (RF) heating (microwave heating) is introduced in this paper. Radio frequency electromagnetic (microwave) can do work directly on medium molecule of oil shale and change into heat energy, the transmission of which allows both inner and outer molecules heating simultaneously without heat conduction. Meanwhile, oil shale is a poor microwave absorbing material and microwave absorbents must be added to reach pyrolysis temperature. By this means, shale oil could be heated at a higher speed and kerogen will gradually be cracked into gas and oil. Then shale oil and gas will flow into the production wells through fractures generated by heating and be pumped up to the surface.

Prospects of borehole NMR instruments and applications Dedicated to Professor Chaohui Ye on the occasion of his 80th birthday

Borehole nuclear magnetic resonance(NMR)is a powerful technology to characterize the petrophysical properties of underground reservoirs in the petroleum industry.The rising complexity of oil and gas exploration and development objectives,as well as the novel application contexts of underground reservoirs,have led to increasingly demanding requirements on borehole NMR technology including instrument design and related processing methods.This mini review summarizes the advances and applications of borehole NMR instruments along with some future possibilities.It may be helpful for researchers and engineers in the petroleum industry to understand the development status and future trends of borehole NMR technology.

A potential NMR-based wettability index using free induction decay for rocks

The wettability of reservoir rocks saturated with oil and water is one of the most important factors influencing petrophysics and oil recovery.Minerals with different wettability constitute the overall heterogeneous wettability in rocks.Variations in sample composi-tion can be detected by nuclear magnetic resonance(NMR)measurements.In this paper,the method of using the magnetic susceptibility contrast between rock skeleton and saturated fluid to estimate wettability is proposed.The theoretical feasibility was firstly analyzed,and then the internal gradients caused by magnetic susceptibility contrasts were employed to interpret wettability alteration before and after ageing process in rocks.It was discovered that water and oil in the same pores experienced different internal gradients after ageing,which were associated with the differences in magnetic susceptibility con-trasts.After that,the free induction decay measurement was performed to acquire mag-netic susceptibility contrasts of artificial sandstone samples with the intermediate-wet condition.A refined NMR wettability index was presented and correlated with the Amott wettability tests.The experimental results demonstrate that the new method for deter-mining wettability is feasible.

Numerical simulation study on the effect of temperature on the restricted diffusion in porous media

It is of great significance to study how temperature affects the restricted diffusion in pores for an accurate evaluation of reservoir physical properties by using nuclear magnetic resonance(NMR)diffusion-transverse relaxation(D-T2)spectrum under reservoir temperature conditions.In this paper,we simulate the restricted diffusion and twodimensional(2D)NMR D-T2 spectra of water molecules at different temperatures using random-walk method.The one-dimensional(1D)restricted diffusion simulation results show that the diffusion coefficient in the pore at room temperature decays with the diffusion time and eventually reaches a plateau.Under the condition of long-time diffusion,the ratio of restricted diffusion coefficient to bulk diffusion coefficient at different temperatures tends to be the same constant.With the increase in temperature,the simulated D-T2 spectra also gradually move upward.The simulated D-T2 spectra at all temperatures are consistent with the Pade interpolation equation.In addition,the results calculated by Pade interpolation equation demonstrate that the degree of temperature influence on the D-T2 spectrum of rock is quantitatively related to the pore radius,porosity and cementation index.

Terahertz-dependent PM2.5 monitoring and grading in the atmosphere

Rapid industrialization and economic development have led to serious pollution in the form of fine particulate matter(PM2.5,particulate matter with a diameter of less than 2.5 μm). In China, PM2.5 has been one of the most debated topics in councils of government and issues of public concern. Terahertz(THz) radiation was employed to measure the PM2.5 in the atmosphere from September 2014 to April 2015 in Beijing. Comparison of the PM2.5 level from the website with THz absorbance revealed a significant phenomenon: THz radiation can be used to monitor PM2.5 in the atmosphere. During Asia-Pacific Economic Cooperation(APEC) 2014, "APEC Blue" was also recorded in a THz system. The relationship between absorbance and PM2.5 demonstrates that THz radiation is an effective selection for air pollution grading. Based on the absorbance spectra, the elemental compositions were studied by two-dimensional correlation spectroscopy(2 DCOS) in conjunction with X-ray fluorescence.Several single absorption peaks were revealed and caused by sulphate from coal combustion, vehicle exhaust emissions and secondary reactions. Furthermore, mathematical algorithms, such as the BPANN and SVM, can process the THz absorbance data and greatly improve the precision of the estimation of PM2.5 mass. Our results suggest that THz spectroscopy can not only reveal the component information for pollution source determination, but quantitatively monitor the PM2.5 content for pollution level evaluation. Therefore, the use of THz radiation is a new method for future air pollution monitoring and grading systems.

Non-contacting characterization of PM2.5 in dusty environment with THz-TDS

Dear Editors,Nowadays,many developing countries(such as China)are experiencing severe air pollution due to the rapid urbanization and industrialization.PM2.5,which refers to the particulate matter with an aerodynamic diameter of 2.5mm or less,is the most important causation of air pollution in cities[1].