Search

In terms of the collaborative optimization of CO2flooding for Enhanced Oil Recovery (EOR) and CO2sequestration, previous studies have co-optimized both cumulative oil production and CO2sequestration by various algorithms. However, these solutions fail to optimize the CO2injection schemes for high-water cut oil reservoirs. This paper presents an optimization methodology for CO2flooding and sequestration in high-water cut oil reservoirs. The production optimization was carried out by adjusting the injection and production rate. To solve the proposed objective functions, the simultaneous perturbation stochastic approximation (SPSA) algorithm is applied in this paper, and the CMG-GEM module is utilized to simulate the reservoir production performance. A typical high-water cut reservoir in the Shengli oilfield was used to verify the feasibility of the presented methodology. In this paper, the production performance and net present value (NPV) for continuous gas injection under different water cuts were analyzed. The optimal timing of transforming from water flooding to gas displacement for the high-water cut reservoir was optimized. In addition, the optimal water–gas ratios for Water-Alternating-Gas (WAG) flooding were determined. The sensitivity of NPVto gas injection price and carbon subsidy was analyzed. The results show that when the gas price is 0.178 $/m3and the carbon subsidy is 0.0169 $/m3, the optimal timing of transforming from water flooding to gas injection should be earlier than the time when the water cut is 0.82. Through the combination ofNPV, cumulative oil production rate, and CO2sequestration volume for WAG flooding, the optimal WAG ratio should be 1:2. The presented method in this paper considers various economic indicators and can optimize CO2flooding and sequestration in high-water cut oil reservoirs efficiently, which can provide some guidance for the design of CO2flooding schemes in high-water cut oil reservoirs.

The outbreak of coronavirus disease (COVID‐19) coincided with the season of influenza A pneumonia, a common respiratory infectious disease. Therefore, this study compared ultrasonography and computed tomography (CT) for the diagnosis of the two diseases. Patients with COVID‐19 or influenza A infection hospitalized at our hospital were included. The patients were examined by ultrasonography every day. The CT examination results within 1 day before and after the day of the highest ultrasonography score were selected as the controls. The similarities and differences between the ultrasonography and CT results in the two groups were compared. There was no difference between the ultrasonography and CT scores (P= .307) for COVID‐19, while there was a difference between ultrasonography and CT scores for influenza A pneumonia (P= .024). The ultrasonography score for COVID‐19 was higher than that for influenza A pneumonia (P= .000), but there was no difference between the CT scores (P= .830). For both diseases, there was no difference in ultrasonography and CT scores between the left and right lungs; there were differences between the CT scores of the upper and middle lobes, as well as between the upper and lower lobes of the lungs; however, there was no difference between the lower and middle lobes of the lungs. Ultrasonography is equivalent to the gold standard CT for diagnosing and monitoring the progression of COVID‐19. Because of its convenience, ultrasonography has important application value. Furthermore, the diagnostic value of ultrasonography for COVID‐19 is higher than that for influenza A pneumonia.

This paper presents a new semi-analytical model to estimate the bottom-hole pressure drop for a water-alternating-CO2injection well in a horizontal, linear, homogenous tight oil reservoir with constant-pressure boundary. In this model, the conventional Buckley-Leverett (B-L) equations are modified to consider the interaction between CO2and oil or water. The Laplace transformations and Stehfest inversion algorithm are employed to solve the model. Through the comparison of pressure profile between proposed and numerical models at different times, and the match of pressure drop with experiments and numerical simulation data collected from published paper, the model accuracy is validated. The sensitivity analysis indicates that with the reduction of CO2-oil interfacial tension and the increase of CO2slug size, the water injectivity will be improved. The water injectivity strongly depends on the reservoir permeability. When the formation permeability is lower than 0.075 mD, the injectivity will decline drastically. [Received: December 12, 2017; Accepted: June 6, 2018]

Background: The advantages of spleen stiffness in prediction of high-risk varices (HRV) in cirrhosis patients have been confirmed. Recently, a new device utilizing a 100 Hz probe dedicated to spleen stiffness measurement (SSM) was developed.Objectives: To validate the clinical applicability of SSM@100 Hz in predicting HRV by comparing it with other non-invasive tests (NITs).Design: A prospective cohort study.Methods: A total of 171 cirrhosis patients who underwent esophagogastroduodenoscopy (EGD) examination were included in this study. SSM using a 100 Hz probe and liver stiffness measurement using a 50 Hz probe were performed. Additionally, 22 healthy controls underwent spleen stiffness evaluation using the 100 Hz probe.Results: The failure rates of spleen stiffness examination in patients with cirrhosis and in healthy controls were 2.9% and 4.5%, respectively. The means of SSM values were 56.4 ± 21.6 and 13.8 ± 6.7 kPa in cirrhosis and controls. SSM increased proportionally with the severity of esophageal varices. The area under receiver operating characteristic (ROC) for spleen stiffness in predicting HRV was 0.881 (95% confidence interval 0.829–0.934), with a cutoff value of 43.4 kPa. The accuracy, false negative rate and EGD spare rate were 86.5%, 2.5% and 24.3%, respectively. For HRV prediction, SSM was comparable to expanded Baveno VI and VII and superior to other NITs. As to viral versusnon-viral cirrhosis and compensated versusdecompensated cirrhosis, the cut-off and performance of SSM were different.Conclusion: SSM@100 Hz demonstrates high accuracy in predicting HRV with a low missed HRV rate. Our findings suggest that SSM@100 Hz can be used independently due to its simplicity and effectiveness. However, further studies are needed to determine appropriate cutoff values based on the cause of cirrhosis and liver function.Trail Registration: ChiCTR2300070270.

ObjectiveWe aimed to evaluate the performance of the newly developed deep learning Radiomics of elastography (DLRE) for assessing liver fibrosis stages. DLRE adopts the radiomic strategy for quantitative analysis of the heterogeneity in two-dimensional shear wave elastography (2D-SWE) images.DesignA prospective multicentre study was conducted to assess its accuracy in patients with chronic hepatitis B, in comparison with 2D-SWE, aspartate transaminase-to-platelet ratio index and fibrosis index based on four factors, by using liver biopsy as the reference standard. Its accuracy and robustness were also investigated by applying different number of acquisitions and different training cohorts, respectively. Data of 654 potentially eligible patients were prospectively enrolled from 12 hospitals, and finally 398 patients with 1990 images were included. Analysis of receiver operating characteristic (ROC) curves was performed to calculate the optimal area under the ROC curve (AUC) for cirrhosis (F4), advanced fibrosis (≥F3) and significance fibrosis (≥F2).ResultsAUCs of DLRE were 0.97 for F4 (95% CI 0.94 to 0.99), 0.98 for ≥F3 (95% CI 0.96 to 1.00) and 0.85 (95% CI 0.81 to 0.89) for ≥F2, which were significantly better than other methods except 2D-SWE in ≥F2. Its diagnostic accuracy improved as more images (especially ≥3 images) were acquired from each individual. No significant variation of the performance was found if different training cohorts were applied.ConclusionDLRE shows the best overall performance in predicting liver fibrosis stages compared with 2D-SWE and biomarkers. It is valuable and practical for the non-invasive accurate diagnosis of liver fibrosis stages in HBV-infected patients.Trial registration numberNCT02313649; Post-results.

This prospective multicenter study confirmed that the performance of two-dimensional shear-wave elastography is superior to other noninvasive methods for noninvasive assessment of cirrhosis.

A kind of adaptive filter algorithm based on the estimation of the unknown input is proposed for studying the adaptive adjustment of process noise variance of boost phase trajectory. Polynomial model is used as the motion model of the boost trajectory, truncation error is regarded as an equivalent to the process noise and the unknown input and process noise variance matrix is constructed from the estimation value of unknown input according to the quantitative relationship among the unknown input, the state estimation error, and optimal process noise variance. The simulation results show that in the absence of prior information, the unknown input is estimated effectively in terms of magnitude, a positive definite matrix of process noise covariance which is close to the optimal value is constructed real-timely, and the state estimation error approximates the error lower bound of the optimal estimation. The estimation accuracy of the proposed algorithm is similar to that of the current statistical model algorithm using accurate prior information.

To estimate production behaviors of inclined well in multilayer heterogeneous carbonate gas reservoir, two semi-analytical models for different formation distribution patterns are proposed, which are named as model I and model II. For model I, the inner region of each layer is fractured-vuggy porous medium, while the outer region only contains matrix. For model II, the inner and outer regions are consisted of matrix and fractured-vuggy porous mediums, respectively. To solve the model, Laplace transformation, Fourier transformation and inversion, Duhamel convolution, and Stehfest numerical inverse are applied. The validities of these models are verified through the comparisons with the published datum, which include well bottom-hole pressure (BHP) and gas production rate of individual layer for vertical and inclined wells in multilayer homogenous gas reservoir. Furthermore, by matching the well BHP data collected from a field case, the applicability of model is validated. The influences of prevailing factors, such as the radius ratio between inner and outer regions, horizontal–vertical permeability ratio, and inclination angle, on production behaviors are analyzed. The results show that influenced by the diverse formation distribution patterns, the variation of radius ratio between inner and outer regions has opposite effect on the well BHP for models I and II. Formation anisotropy and inclination angle have minimal effects on the well BHP of model I, but have significant impacts on model II. To keep the well BHP with a relatively high value, for model I and model II, the penetrate inclination angles should be greater than 50 deg and 55 deg, respectively.

Based on the existing research on cellular automata traffic flow model, this paper proposed an improved model for mixed traffic flow in real-time traffic data environment in China. Driver's characteristic is defined according to the NS model and the FI model. In accordance with the mixed traffic flow, a cellular automaton traffic model is proposed. In this model, vehicles are defined in different lengths and different maximum speed, and mixed on single lane and bi-lane with periodic boundary condition. The traffic flow characteristics are analyzed and discussed by computer numerical simulation.

C27H20FN3S2Sn, monoclinic, P21/n(no. 14), a= 15.631(4) Å, b= 9.865(3) Å, c= 17.256(3) Å β= 108.335(11)°, V= 2525.8(10) Å3, Z= 4, Rgt(F) = 0.0398, wRref(F2) = 0.0917, T= 298 K.