Prediction of drilling fluid lost-circulation zone based on deep learning

Lost circulation has become a crucial technical problem that restricts the quality and efficiency improvement of the drilling operation in deep oil and gas wells. The lost-circulation zone prediction has always been a hot and difficult research topic on the prevention and control of lost circulation. This study applied machine learning and statistical methods to deeply mine 105 groups and 29 features of loss data from typical loss block M. After removing 10 sets of noise data, the methods of mean removal, range scaling and normalization were used to pre-treat the 95 sets of the loss data. The multi-factor analysis of variance (ANOVA) and random forest algorithm were adopted to determine the 13 main factors affecting the lost circulation. The three typical deep learning neural network models were improved, the parameters in the models were adjusted, the neural network models with different structures were compared according to the PR curves, and the best model structure was built. The pre-treated loss data in 95 sets with 13 features were divided into the training set and test set by a ratio of 4:1. The model performance was evaluated using F1 score, accuracy, and recall rate. The trained model was successfully applied to the G block with severe leakage. The results show that the capsule network model is better than the BP neural network model and the convolutional neural network model. It stabilizes at 300 training rounds, with a prediction accuracy of 94.73%. The improved model can be applied to lost-circulation control in the field and provide guidance on leakage prevention and plugging operations

Liquid phase blockage in micro-nano capillary pores of tight condensate reservoirs

The development of tight condensate gas reservoirs faces complex formation damage mechanisms, seepage characteristics and hydrocarbon phase changes, which are common challenges for both tight gas reservoirs and condensate gas reservoirs. In the near-well area, the liquid phase blockage problem due to water phase retention formed by capillary spontaneous imbibition of invasive water and oil phase accumulation due to retrograde condensation precipitation has become a key obstacle to the efficient development of tight condensate gas reservoirs. Experiments were conducted to evaluate the damage of liquid phase blockage under different conditions near the wellbore area. The results show that when the liquid phase saturation in the near-wellbore area increased to 80.12%, the relative permeability of the gas phase decreased to 0. It is concluded that the mixed wettability of formation rocks, ultra-low water saturation, abundant hydrophilic clay minerals and high capillary resistance of micro-nano pores are the main causes for the easy adsorption and retention of liquid phase. Reduced pressure transmission capacity and irreversible formation damage induced by liquid-phase blockage are the two major controlling factors for the low liquid phase flowback rate. It is suggested that developing a flowback system based on the formation physical properties differentiation to control water phase invasion, and changing wettability or injecting thermochemical fluid to control condensate blocking are feasible methods to relieve liquid phase blockage damage in tight condensate reservoirs.Cited as: Wang, Y., Kang, Y., Wang, D., You, L., Chen, M., Yan, X. Liquid phase blockage in micro-nano capillary pores of tight condensate reservoirs. Capillarity, 2022, 5(1): 12-22. https://doi.org/10.46690/capi.2022.01.0

Minutiae Matching with Privacy Protection Based on the Combination of Garbled Circuit and Homomorphic Encryption

Biometrics plays an important role in authentication applications since they are strongly linked to holders. With an increasing growth of e-commerce and e-government, one can expect that biometric-based authentication systems are possibly deployed over the open networks in the near future. However, due to its openness, the Internet poses a great challenge to the security and privacy of biometric authentication. Biometric data cannot be revoked, so it is of paramount importance that biometric data should be handled in a secure way. In this paper we present a scheme achieving privacy-preserving fingerprint authentication between two parties, in which fingerprint minutiae matching algorithm is completed in the encrypted domain. To improve the efficiency, we exploit homomorphic encryption as well as garbled circuits to design the protocol. Our goal is to provide protection for the security of template in storage and data privacy of two parties in transaction. The experimental results show that the proposed authentication protocol runs efficiently. Therefore, the protocol can run over open networks and help to alleviate the concerns on security and privacy of biometric applications over the open networks

Impact of the National Reimbursement Drug List Negotiation Policy on Accessibility of Anticancer Drugs in China: An Interrupted Time Series Study

Objective: Since 2016, the Chinese government has been regularly implementing the National Reimbursement Drug List Negotiation (NRDLN) to improve the accessibility of drugs. In the second round of NRDLN in July 2017, 18 anticancer drugs were included. This study analyzed the impact of the NRDLN on the accessibility of these 18 anticancer drugs in China. Methods: National hospital procurement data were collected from 2015 to 2019. As measurements of drug accessibility, monthly average of drug availability or defined daily dose cost (DDDc) was calculated. Interrupted time series (ITS) analysis was employed to evaluate the impact of NRDLN on drug accessibility. Multilevel growth curve models were estimated for different drug categories, regions or levels of hospitals. Results: The overall availability of 18 anticancer drugs increased from about 10.5% in 2015 to slightly over 30% in 2019. The average DDDc dropped from 527.93 CNY in 2015 to 401.87 CNY in 2019, with a reduction of 23.88%. The implementation of NRDLN was associated with higher availability and lower costs for all 18 anticancer drugs. We found an increasing level in monthly drug availability (β2 = 2.1126), which ascended more sharply after the implementation of NRDLN (β3 = 0.3656). There was a decreasing level in DDDc before July 2017 (β2 = −108.7213), together with a significant decline in the slope associated with the implementation of NRDLN (β3 = −4.8332). Compared to Traditional Chinese Medicines, the availability of Western Medicines was higher and increased at a higher rate (β3 = 0.4165 vs. 0.1108). Drug availability experienced a larger instant and slope increase in western China compared to other regions, and in secondary hospitals than tertiary hospitals. Nevertheless, regional and hospital-level difference in the effect of NRDLN on DDDc were less evident. Conclusion: The implementation of NRDLN improves the availability and reduces the cost of some anticancer drugs in China. It contributes to promoting accessibility of anticancer drugs, as well as relieving regional or hospital-level disparities. However, there are still challenges to benefit more patients sufficiently and equally. It requires more policy efforts and collaborative policy combination

MAPK-dependent hormonal signaling plasticity contributes to overcoming Bacillus thuringiensis toxin action in an insect host

The arms race between entomopathogenic bacteria and their insect hosts is an excellent model for decoding the intricate coevolutionary processes of host-pathogen interaction. Here, we demonstrate that the MAPK signaling pathway is a general switch to trans-regulate differential expression of aminopeptidase N and other midgut genes in an insect host, diamondback moth (Plutella xylostella), thereby countering the virulence effect of Bacillus thuringiensis (Bt) toxins. Moreover, the MAPK cascade is activated and fine-tuned by the crosstalk between two major insect hormones, 20-hydroxyecdysone (20E) and juvenile hormone (JH) to elicit an important physiological response (i.e. Bt resistance) without incurring the significant fitness costs often associated with pathogen resistance. Hormones are well known to orchestrate physiological trade-offs in a wide variety of organisms, and our work decodes a hitherto undescribed function of these classic hormones and suggests that hormonal signaling plasticity is a general cross-kingdom strategy to fend off pathogens